master copy of the document

Dynamic Simulation of Gas-Lift Wells and Systems

API RECOMMENDED PRACTICE 19G11 (RP 19G11)DRAFT #12, January 15, 2011

American Petroleum Institute1220 L. Street, NorthwestWashington, DC 20005

API

Issued by

AMERICAN PETROLEUM INSTITUTE

Production Department

FOR INFORMATION CONCERNING TECHNICAL CONTENTS OF THIS PUBLICATION CONTACT THE API PRODUCTION DEPARTMENT, 2535 ONE MAIN PLACE, DALLAS, TX 75202 - (214) 748-3841. SEE BACK COVER FOR INFORMATION CONCERNINGHOW TO OBTAIN ADDITIONAL COPIES OF THIS PUBLICATION.

Users of this publication should become familiar with its scope and content. This publication is intended to supplement rather than replace individual engineering judgement.

Official Publication

API

Reg. U.S. Patent Office

Copyright @ l993 American Petroleum Institute

API RP 19G11 Dynamic Simulation of Gas-Lift Wells and Systems Page 1

ForewordThis Recommended Practice (RP) is under the jurisdiction of the API Committee on Standardization of Production Equipment (Committee 19).

This document presents Recommended Practices for Dynamic Simulation of Gas-Lift Wells and Systems. Other API Specifications, API Recommended Practices, and Gas Processors Suppliers Association (GPSA) documents may be referenced and should be used for assistance in design and operation.

API Recommended Practices may be used by anyone desiring to do so, and diligent effort has been made by the Institute to assure the accuracy and reliability of the data contained therein. However, the Institute makes no representation, warranty, or guarantee in connection with the publication of any API Recommended Practice and hereby expressly disclaims any liability or responsibility for loss or damage resulting from their use, for any violation of any federal, state, or municipal regulation with which an API Standard may conflict, or for the infringement of any patent resulting from the use of an API Recommended Practice or Specification.

Note:

This is the first edition of this recommended practice.

Requests for permission to reproduce or translate all or any part of the material published herein should be addressed to the Director, American Petroleum Institute, 1220 L Street NW, Washington DC 20005-4070

This Recommended Practice shall become effective on the date printed on the cover but may be used voluntarily from the date of distribution.

All rights reserved. No part of this work may be reproduced, translated, stored in a retrieval system, or transmitted by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior

written permission from the publisher. Contact the Publisher, API Publishing Services, 1220 L Street, NW, Washington, DC 20005

Copyright © 2009 American Petroleum Institute


Policy

API PUBLICATIONS NECESSARILY ADDRESS PROBLEMS OF A GENERAL NATURE. WITH RESPECT TO PARTICULAR CIRCUMSTANCES, LOCAL, STATE, AND FEDERAL LAWS AND REGULATIONS SHOULD BE REVIEWED.

API IS NOT UNDERTAKING TO MEET THE DUTIES OF EMPLOYERS, MANUFACTURERS, OR SUPPLIERS TO WARN AND PROPERLY TRAIN AND EQUIP THEIR EMPLOYEES, AND OTHER EXPOSED PERSON, CONCERNING HEALTH AND SAFETY RISKS AND PRECAUTIONS, NOR UNDERTAKING THEIR OBLIGATIONS UNDER LOCAL, STATE, OR FEDERAL LAWS.

NOTHING CONTAINED IN ANY API PUBLICATION IS TO BE CONSTRUED AS GRANTING ANY RIGHT, BY IMPLICATION OR OTHERWISE, FOR THE MANUFACTURE, SALE, OR USE OF ANY METHOD, APPARATUS, OR PRODUCT COVERED BY LETTERS PATENT. NEITHER SHOULD ANYTHING CONTAINED IN THE PUBLICATION BE CONSTRUED AS INSURING ANYONE AGAINST LIABILITY FOR INFRINGEMENT OF LETTERS PATENT.

GENERALLY, API STANDARDS ARE REVIEWED AND REVISED, REAFFIRMED, OR WITHDRAWN AT LEAST EVERY FIVE YEARS. SOMETIMES A ONE-TIME EXTENSION OF UP TO TWO YEARS WILL BE ADDED TO THIS REVIEW CYCLE. THIS PUBLICATION WILL NO LONGER BE IN EFFECT FIVE YEARS AFTER ITS PUBLICATION DATE AS AN OPERATIVE API STANDARD OR, WHERE AN EXTENSION HAS BEEN GRANTED, UPON REPUBLICATION. STATUS OF THE PUBLICATION CAN BE ASCERTAINED FROM THE API AUTHORING DEPARTMENT (TEL. 214-220-911 1). A CATALOG OF API PUBLICATIONS AND MATERIALS IS PUBLISHED ANNUALLY AND UPDATED QUARTERLY BY API, 1220 L ST., N.W., WASHINGTON, D.C. 20005.


TABLE OF CONTENTS API.................................................................................................................................................................1AMERICAN PETROLEUM INSTITUTE...............................................................................................................2

PRODUCTION DEPARTMENT......................................................................................................................................2

API................................................................................................................................................................ 2

COPYRIGHT @ L993 AMERICAN PETROLEUM INSTITUTE................................................................................................2

FOREWORD................................................................................................................................................... 1

POLICY.......................................................................................................................................................... 2

TABLE OF CONTENTS..................................................................................................................................... 3

TERMS AND ABBREVIATIONS......................................................................................................................... 5

ABBREVIATIONS USED IN THIS DOCUMENT, AND THEIR MEANINGS.............................................................11

DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS..........................................................................14

1. API RP 19G11..........................................................................................................................................14Introduction.................................................................................................................................................14

2. SUMMARY OF RECOMMENDED PRACTICES FOR DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS...................153. INTRODUCTION TO DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS.........................................................33

Document Objectives...................................................................................................................................33Dynamic Simulation - Definition and Basic Concepts...................................................................................34Difference between Steady-State and Dynamic Simulation Techniques......................................................44

4. TYPICAL GAS-LIFT WELL AND SYSTEM OPERATIONS............................................................................................50Continuous gas-lift.......................................................................................................................................50Intermittent gas-lift.....................................................................................................................................53Gas-assisted plunger lift..............................................................................................................................56Dual gas-lift.................................................................................................................................................58Single-point gas-lift......................................................................................................................................61Auto gas-lift.................................................................................................................................................62Riser gas-lift.................................................................................................................................................63Gas-lift for gas well deliquification..............................................................................................................64Gas-lift unloading........................................................................................................................................65Use of gas-lift for well kick-off.....................................................................................................................66Use of gas-lift for wellbore clean-up............................................................................................................67Gas-lift system distribution..........................................................................................................................67Use of un-dehydrated gas............................................................................................................................68Use of non-hydrocarbon gases such as CO2 and N2......................................................................................68Naturally Flowing Gas-Lift Wells..................................................................................................................69

5. RECOGNIZE WHEN DYNAMIC SIMULATION IS BENEFICIAL....................................................................................70


Use dynamic simulation to determine and respond when a well or system may be unstable.....................70Use dynamic simulation to determine when to use gas-lift to re-start wells...............................................72Use dynamic simulation to determine when to start gas-lift in a flowing well............................................73Use dynamic simulation to determine the need to start gas-lift due to liquid loading in gas wells..............74Use dynamic simulation to aid in optimizing intelligent and complex well completions..............................78Use dynamic simulation to aid in understanding when cross flow and/or commingling occur....................81Use dynamic simulation to optimize gas-lift well and system shut-in and start-up operations...................83

6. INFORMATION REQUIRED FOR DYNAMIC SIMULATION.........................................................................................87Fluid properties............................................................................................................................................87Well Profile and Well Schematic..................................................................................................................89Inflow performance relationship..................................................................................................................90Boundary Conditions...................................................................................................................................91

7. APPLICATION OF DYNAMIC SIMULATION...........................................................................................................92Integrated modelling...................................................................................................................................92Real-time modelling.....................................................................................................................................93Use of dynamic simulation modelling for gas-lift system management......................................................95Appropriate dynamic simulation techniques and their implementation......................................................98

8. INFORMATION PROVIDED BY DYNAMIC SIMULATION.........................................................................................105Slugging flow:............................................................................................................................................105Water effects on corrosion and hydrates:..................................................................................................110Production chemistry:................................................................................................................................126Gas-lift valve performance:........................................................................................................................131Well equipment:........................................................................................................................................139Well design:...............................................................................................................................................143

9. CASE HISTORIES.........................................................................................................................................147Case History 1: Penguins Gas-Lift...............................................................................................................147

THE PHASES OF CLEARING MEG FROM THE GAS-LIFT LINE AND CROSSOVERS, AND THE UNLOADING OF THE BASE OIL FROM THE ANNULI WERE MODELLED IN AN ITERATIVE FASHION TO DETERMINE THE REQUIRED PROCEDURES TO REMAIN WITHIN THE SYSTEM LIMITATIONS......................................................................................................................................................149

Case History 2: Transient Gas-Lift Analysis in ERD and non-ERD Wells......................................................15010. References........................................................................................................................................167


Terms and Abbreviations

Terms Used in this Document, and Their Definitions

1. Beaning up: The process of increasing the wellhead choke size to adjust the flow rate.

2. Black oil correlations: The black-oil model assumes that the reservoir fluids consist of three phases: oil, water, and gas. These are defined with a minimum of information (specific gravity, gas-oil ratio, and water cut), with gas dissolving in oil and oil vaporizing in gas. Water is assumed to be inert. Use correlations to determine the fluid properties at different pressures and temperatures (P-T).

3. Boundary conditions: The fluid type, flow rate, pressure, and temperature values assigned to the selected model boundaries (inputs, outputs, and surrounding environment of the model) used in solving the differential equations that apply to dynamic simulation.

4. Bull heading: This is a process to forcibly pump fluids into a wellbore to stop the well from flowing.

5. Commingling: This is a process where fluids from different productive formations are combined and produced them through a single conduit.

6. Cross flow: This describes the flow of reservoir fluids from one productive formation into another.

7. de Waard Model: This is a CO2 corrosion model that is commonly used in Industry.

8. Distributed IPR: This methodology is used to divide the reservoir’s productive intervals into zones and calculating individual IPR’s for each separate zone.

9. Drift-flux models: This is a model that treats the two phases as a mixture. Gas is assumed to be drifting along with liquid and the gas velocity can be described by a slip relation.


10. Dry tree: This describes wellhead equipment that is not in contact with the sea water. It has all tree components housed in a chamber or encapsulated by a subsea vessel, or it is located in a production/drilling platform using a dry tree riser.

11. Dynamic simulation: This refers to multiphase flow transient numerical simulation.

12. Dynamic water and gas coning: This refers to the change in oil-water or gas-oil interface profiles in the near wellbore area as a result of reservoir pressure depletion during production life , and/or as a result of drawdown on wellbore production pressure above a critical value.

13. Field life cycle: This refers to changes in operating conditions from the moment the field is opened to production until it is closed and abandoned.

14. Flashing: This refers to the process of rapidly reducing the pressure of a hydrocarbon sample to lower pressure and temperature in steps to determine its components at each step.

15. Flow assurance: This refers to ensuring successful and economical flow of hydrocarbon streams from the reservoir to the point of sale.

16. Flow regime: This is the prevailing gas, oil, and water geometrical distribution when flowing through a pipe.

17. Flow regime classes: These are the common flow regimes for gas-liquid mixtures such as bubble flow, dispersed bubble flow, plug flow, slug flow, froth flow, mist flow, churn flow, and annular flow.

18. Forchheimer IPR model: This is an inflow performance relationship model developed by Forchheimer and widely accepted and applied in gas wells.

19. Hydrates: Gas hydrates are solid ice-like crystalline compounds formed by water and natural gas molecules at high pressures and low temperatures.


20. Hydrodynamic slugging: These slug flow conditions are caused by gas flowing at a fast rate over a slower flowing liquid phase. The gas will form waves on the liquid surface, which may grow to bridge the whole cross-section of the line. This creates a blockage on the gas flow, which travels as a slug through the line.

21. Intelligent wells: This refers to well completions where data recording and well control can be perform remotely. A well equipped with monitoring equipment and flow control components can be adjusted to optimize production remotely, either automatically or with operator intervention.

22. Joule Thompson cooling: The Joule–Thomson effect describes the temperature change of a gas when it is forced through a valve or porous medium while the entire system is kept insulated so that no heat is exchanged with the environment. The change may be positive or negative. For each gas, there is an inversion point that depends on P-T, below which it is cooled and above which it is heated. The magnitude of the change of temperature with pressure depends on the Joule-Thomson coefficient for each particular gas. The Joule-Thomson effect often causes a temperature decrease as gas flows through pores of a reservoir to the wellbore. At room temperature, all gases except hydrogen, helium, and neon cool upon expansion by the Joule-Thomson process.

23. Kick-off: This refers to bringing an off production well back to production when there are only formation fluids in the wellbore.

24. Kick-off water cut limit: This is the water cut critical value that does not allow a natural flowing well to start without gas-lift. Above the water cut limit, the right amount of gas lift gas needs to be injected to start production.

25. Liquid hold up: This refers to the liquid stored in well and flowlines at certain production conditions. When gas flows at a greater velocity than the liquid, slippage takes place and liquid hold up occurs.

26. Mechanistic models: These mathematical models describe the multiphase flow mechanisms (including related fluid properties and physical relationships) using physical flow equations for each of the phases within the system.


27. Multi-lateral completions: These are well completions which have more than one wellbore branch radiating from the main borehole.

28. Multi-layer completions: These are well completions that have more than one producing reservoir layer.

29. Multi-pointing: This refers to the situation where gas-lift injection gas enters the production stream from more than one point.

30. Non-Darcy skin: This refers to a rate dependant skin effect which is due to turbulent flow conditions taking place near the wellbore. The fluid flow in this case deviates from Darcy's law, which assumes laminar flow in the reservoir. Non-Darcy turbulent flow and associated skin are typically observed in high-rate gas wells when the flow converging to the wellbore reaches flow velocities exceeding the Reynolds number for laminar flow.

31. NORSOK M-506 model: This refers to a CO2 corrosion model that is commonly used in Industry.

32. Quasi-dynamic IPR: This is an inflow production relationship (IPR) model where variables such as pressure, temperature, permeability, and skin can be input as time-series.

33. Real-time modelling: Real-time data captured by a Supervisory Control and Data Acquisition (SCADA) systems is input in a dynamic simulator which is used to monitor, advise, and control the production/injection system to obtain optimum flow assurance and production. The main objective in developing the on-line model is to decrease the operational cost of the system by optimizing production, by improving the rules used to control the inflow into the wellbore, and by decreasing the time necessary to model required alternatives to select an optimum.

34. Riser gas-lift: This refers to the process where gas-lift injection gas is injected at the base of the riser.

35. Snake-type wells: This is a horizontal wellbore profile which has frequent up and down slope sections.


36. Slugging flow: This refers to a multiphase flow regime characterized by a series of liquid plugs (slugs) separated by relatively large gas bubbles. In severe slugging conditions, the gas bubble occupies almost the entire cross-sectional area of the pipe. The resulting flow alternates between high-liquid and high-gas composition zones.

37. Steady state simulation: These simulations are designed to give insight into the steady-state behavior of the system by using a dynamic simulator. When opening the well to production, the time required to obtain steady state conditions is calculated and the values of the key variables (P-T and rate) are validated. Also, the simulation runs will indicate if no steady state conditions are reached.

38. Sub-surface safety valve: This is a valve installed at a certain depth in the wellbore that can be closed remotely to isolate the tubing above the valve and wellhead from reservoir fluids in an emergency or planned shutdown.

39. Superficial velocity: This refers to the velocity of a single component (oil, water, gas) in a multi-component flowing situation, taking into account the full cross-sectional area of the pipe.

40. Terrain-induced slugging: This refers to a slugging condition generated by changing elevations in the pipeline which follow the ground, seabed, and/or riser. Liquid can accumulate at low points of the pipeline until sufficient pressure builds up behind it. Once the liquid is pushed out of the low point, it will form a slug.

41. Thornhill-Craver equation: This is a commonly accepted equation used to predict the rate of gas passage through a given orifice size.

42. IFE “Top of Line” Model: This is a CO2 corrosion model that focuses on the top of a horizontal pipe. It considers variations in water condensation rates which have a larger effect on the corrosion rate in the top of the line than variations in the CO2 partial pressure.

43. Transient flow: This refers to flow where the velocity and pressure change over time.


44. Unloading: This refers to the process of displacing initial annular and/or tubing fluids in the well when gas-lift injection gas is started.

45. Vogel IPR model: This inflow performance relationship model, developed by Jack Vogel, is widely accepted and applied in oil wells.

46. Wax gelation: The deposit formed on the pipe wall is not purely solid wax, but is in the form of a gel consisting of a network of solid wax crystals, which traps a large amount of oil inside. This gel deposit grows in thickness and also ages with time because of the diffusion of the wax molecules from the oil flowing toward the cold wall. Gels are defined as a substantially dilute cross-linked system, which exhibits no flow when in the steady-state. By weight, gels are mostly liquid, yet they behave like solids due to a three-dimensional cross-linked network within the liquid. It is the cross links within the fluid that give a gel its structure (hardness) and contribute to stickiness.


Abbreviations used in this Document, and Their Meanings

1 D Grid One Dimension Grid

BHP Bottom Hole Pressure

BHT Bottom Hole Temperature

CCE Constant Composition Expansion

CPU Central Processing Unit

Cv Valve Flow Coefficient

CVD Constant Volume Depletion

DTHYD Difference between Hydrate Formation Temperature and Fluid Temperature

E&P Exploration and Production

EOS Equation of State

EOT End of Tubing

ERD Extended Reach Drilling

ESP Electrical Submersible Pumps

FEED Front End Engineering Design

GL Gas-Lift

GLV Gas-Lift Valve

GLM Gas-Lift Mandrel

GLR Gas Liquid Ratio

GOR Gas Oil Ratio

HDI Hydraulic Diaphragm Insert pump

HIPPS High Integrity Pressure Protection Systems

HTGC High Temperature Gas Chromatography

ICD Inflow Control Devices

ICV Intelligent Control Valves

ID Internal Diameter

IPC Intake Pressure Curve

IPO Injection Pressure Operated gas-lift valves

IPR Inflow Performance Relationship

IRDV Intelligent Remote Downhole Valve

k Permeability

k-h Permeability-Thickness

LCM Lost Circulation Material


LDHI Low Dosage Hydrate Inhibitors

MD Measured Depth

MEG Mono Ethylene Glycol

MeOH Methanol

MODU Mobile Offshore Drilling Unit

n-D Non-Darcy

NPV Net Present Value

OD Outside Diameter

O&G Oil and Gas

PBR Polished Bore Receptacle

PR78 SRK-P Peng Robinson 1978, Soave-Redlich-Kwong, with Peneloux volume correction

Pcf Casing Pressure

pH Measure of Acidity or Alkalinity

Piod Gas-Lift Valve Injection Pressure at Depth

PI Productivity Index

PL Plunger Lift

PPO Production Pressure Operated gas-lift valve

Pres Reservoir Pressure

Ptf Tubing Pressure

P-T Pressure-Temperature

PvoT Gas-Lift Valve Opening Pressure at Temperature

PVT Pressure-Volume-Temperature

Pwf Flowing Bottom Hole Pressure

Qg Gas flow rate

Qo Oil flow rate

Qw Water flow rate

SSD Sliding Sleeve Door

SCADA Supervisory Control and Data Acquisition

SSSV Sub-Surface Safety Valve

SCSSV Surface Control Sub-surface Safety Valve

STP Standard Temperature and Pressure 101.3 kPa and 15.56 oC (14.7 psi and 60 °F)

TD Total Depth

Tf Fluid Temperature

THP Tubing Head Pressure

Thyd Hydrate formation Temperature

Tres Reservoir Temperature

Trvl Valve Stem Travel


TVD True Vertical Depth

TOL Top of Line

VPC Valve Performance Clearinghouse

WAT Wax Appearance Temperature

WC Water Cut

WGR Water Gas Ratio

WHP Well Head Pressure

WHT Well Head Temperature


Dynamic Simulation of Gas-Lift Wells and Systems

1. API RP 19G11

IntroductionThis API Recommended Practice covers the application of dynamic simulation for gas-lift wells and systems. Dynamic simulation is an important tool to assist in the design, operation, surveillance, troubleshooting, and diagnosis of gas-lift processes. Most gas-lift design and diagnosis programs have used steady-state models. This may lead to inappropriate designs and inefficient operations because gas-lift wells and systems are seldom steady. Gas-lift wells usually exhibit dynamic pressure and flow rate fluctuations. It is important to understand the dynamic behavior of wells and systems so they can be more appropriately designed, operated, and diagnosed.

Until recently, dynamic simulation systems were not readily available for use in industry, so the Supplier/Manufacturer and User/Purchaser Companies were required to rely on steady-state models. However, within the last few years, dynamic simulation systems have become more readily available, and their use has proven valuable in many instances. This is especially important as gas-lift operations have become more challenging with extended reach wells, deviated/horizontal wells, multi-lateral wells, deep water and sub-sea completions, and long sub-sea flow lines and risers. These operations are expensive and it is essential that they be designed and operated in an optimum fashion.

This document contains nine chapters to assist the gas-lift industry in understanding and applying dynamic simulation for gas-lift wells and systems:

1. Summary of Recommended Practices for Dynamic Simulation of Gas-Lift Wells and Systems. This contains a brief summary with cross references to the recommended practices found in Chapters 2 – 7.

2. Introduction to Dynamic Simulation of Gas-Lift Wells and Systems. This describes the objectives of the document, defines dynamic simulation and its basic concepts, and describes the differences between steady-state and dynamic simulation.

3. Typical Gas-Lift Well and System Operations. This describes fifteen different typical gas-lift well and system configurations and how dynamic simulation may be used to enhance their design and operation.


4. Recognize When Dynamic Simulation is Beneficial. This describes various typical gas-lift well and system operating conditions or problems where dynamic simulation can be used to better understand and design solutions.

5. Information Required for Dynamic Simulation. This describes the information that needs to be available to successfully use dynamic simulation models.

6. Application of Dynamic Simulation. This describes specific applications where dynamic simulation can be used to improve gas-lift well and system performance.

7. Information Provided by Dynamic Simulation. This presents some of the specific information and results that can be provided by dynamic simulation models.

8. Case Histories. This provides a summary of relevant case histories where dynamic simulation has been successfully employed for gas-lift wells and systems.

9. References. This provides a bibliography of references where dynamic simulation has been employed for gas-lift wells and systems, as well as for other general production system applications such as wax, hydrates, and flow assurance. Some references are also provided to help to understand dynamic simulation principles.

2. Summary of Recommended Practices for Dynamic Simulation of Gas-Lift Wells and Systems

This chapter contains a summary and description of the recommended practices contained in this document.

The recommended practices are organized by the chapters where they are presented. This chapter contains a cross reference to the detailed chapter(s) where each recommended practice is discussed and described.

After reading this chapter, the reader should understand the recommended practices that need to be followed to successfully use and deploy dynamic simulation of gas-lift wells and systems. A reference on where to turn in the document for more detailed information is provided.


Ch.

Sect.

Practice Number

Summary of Recommended Practices


Ch.

Sect.

Practice Number


II Introduction to Dynamic Simulation of Gas-Lift Wells and Systems

a Document Objectives

1 Create best practice recommendations for the application of dynamic simulation in gas-lift wells and systems in order to optimize well/system integrity, operations, life cycle design, and production.

2 A broad range of artificial lift including gas well liquid loading and natural flowing systems are addressed as appropriate.

3 Most of the dynamic simulation recommendations are not only specific to gas-lift systems but they can be implemented in other type of production systems.

4 This document is designed to gain a general understanding of dynamic simulation, areas of application, and added value and benefits.

b Dynamic Simulation - Definition and Basic Concepts

1 Dynamic simulation is the common term for multiphase flow transient numerical simulation used for modelling the hydraulic and heat transfer from the reservoir to the facilities.

2 Use multiphase flow transient numerical simulation techniques in wells and production systems to facilitate optimal economic design, operation, maintenance, safety, and environmental protection.

3 Dynamic simulation should be used during all stages of the operational well/system life cycle to predict multi-phase flow behavior and “what-if” analysis.

4 Evaluate well and pipeline flow interaction by dynamic model integration.

5 Multi-discipline teams or cross-discipline experience is required to build and integrate the well and production system model from the reservoir to facilities.

6 In gas-lift systems, the maximum benefits of dynamic simulation are obtained when the model is applied for real-time


Ch.

Sect.

Practice Number


production optimization.

c Difference between Steady-state and Dynamic Simulation Techniques

1 Dynamic simulation is recommended to analyze transient operations.

2 Validate the model for steady state and transient conditions to ensure accuracy of the simulation.

3 Use dynamic simulation to determine periods of flow stability and instability.

4 Use dynamic simulation to define flow regimes and estimate Pressure/Temperature profiles in the well/system.

5 Use dynamic simulation when combined oil and gas production systems and conditions as listed in Section II are encountered.

III Typical Gas-Lift Well and System Operations

a Continuous Gas-Lift

1 Design continuous gas-lift wells to lift as deep as possible, as stable as possible, and to obtain optimum gas-lift performance.

2 Use dynamic simulation to confirm the design will allow deep and stable operation.

3 Use dynamic simulation to diagnose the causes of instability in continuous gas-lift wells.

4 Use dynamic simulation to check for multi-pointing where more than one entry point is open, all or part of the time.

5 In gas-lift systems, the maximum benefits of dynamic simulation are obtained when the model is applied in real-time.

b Intermittent Gas-Lift

1 Design intermittent gas-lift wells to inject the optimum amount of gas per cycle at the optimum cycle frequency.


Ch.

Sect.

Practice Number


2 Use dynamic simulation to determine if input “choke” control or time-cycle control is more appropriate to control gas injection.

3 Use dynamic simulation to design and diagnose inefficiencies in the intermittent gas-lift operation.

c Gas-Assisted Plunger Lift

1 Use dynamic simulation to design and diagnose inefficiencies in the plunger-assisted gas-lift operation.

d Dual Gas-Lift

1 Design a dual gas-lift well to unload to the desired operating valve in both strings.

2 Dynamic simulation will estimate the amount of lift gas entering each of the tubing strings from the common annulus.

3 Use dynamic simulation to evaluate and troubleshoot the operation of a dual gas-lift well.

e Single-Point Gas-Lift

1 Single point gas-lift is a special form of continuous gas-lift, with only one possible point of gas entry. No unloading valves.

2 Use dynamic simulation to design and operate single point injection wells.

3 Use dynamic simulation to troubleshoot and diagnose causes of instability.

f “Auto” Gas-Lift

1 Use dynamic simulation to troubleshoot and diagnose causes of instability.

2 Use dynamic simulation to determine the optimum injection rate and/or back pressure.

3 Use dynamic simulation to properly design and operate auto gas-lift systems.

g Riser Gas-Lift


Ch.

Sect.

Practice Number


1 Use dynamic simulation to evaluate the design and diagnose problems, pressure fluctuations, or flow rate slugs that may upset facilities on the platform.

2 Use dynamic simulation to define the economic life of the riser system and the optimum time to switch to wellhead and/or downhole injection.

h Gas-Lift for Gas Well Deliquification

1 Use dynamic simulation to evaluate the design of the unloading system.

2 Use dynamic simulation to evaluate the lift gas injection rate to determine if the total injected plus produced gas will remain at or above the critical gas flow rate.

3 Use dynamic simulation to assist in the diagnosis of problems in wells where the well is beginning to experience liquid loading due to insufficient gas injection.

i Gas-Lift Unloading

1 Use dynamic simulation to evaluate the design of unloading gas-lift mandrel depths and set pressures of the unloading valves.

2 Use dynamic simulation to evaluate the liquid and gas flow rates through the gas-lift valves during the unloading process, to evaluate if valve port or seat damage may occur.

3 Use dynamic simulation to determine if the well will unload to the desired depth.

4 Run the dynamic simulator with the steady state design, and determine if the well will unload successfully. If it will not, reiterate the design and re-evaluate.

j Use of Gas-Lift for Well Kick-Off

1 Use dynamic simulation to determine if a gas-lift well can be started in “normal” operation. If not, a special kick-off process must be developed, analyzed, and followed.


Ch.

Sect.

Practice Number


2 Use dynamic simulation to determine if the well will flow naturally after it has been kicked off.

3 Use dynamic simulation to predict the well’s parameters for which kick-off of naturally flowing wells is required after a shut-in period.

k Use of Gas-Lift for Wellbore Clean-Up

1 Use a dynamic simulator to determine the gas-lift injection pressure and rates needed to remove completion fluids from the wellbore, and the time required to clean-up the well.

l Gas-Lift System Distribution

1 Use a dynamic simulator to evaluate changes in the distribution of gas to the wells served by the system.

m Use of Un-Dehydrated Gas

1 Use a dynamic simulator to evaluate the potential for hydrate formation when a pressure drop exists in the system.

2 Use dynamic simulation to evaluate the benefits of dehydrating the gas.

n Use of Non-Hydrocarbon Gases such as CO2 and N2

1 Use a dynamic simulator to help understand the characteristics that may be result from the differing properties of non-hydrocarbon gases.

o Natural Flowing Gas-Lift Wells

1 Use dynamic simulation to aid in the evaluation of the optimum time to switch from natural flow to gas-lift.

IV Recognize When Dynamic Simulation is Beneficial

a Use Dynamic Simulation to Determine and Respond when a Well or System may be Unstable

1 Use dynamic simulation to help identify the causes of unstable transient conditions, such as decreasing reservoir pressure,


Ch.

Sect.

Practice Number


increased water cut, over-sized tubing for current fluid production, decreased total gas liquid ratio, or increased back pressure.

2 Use dynamic simulation to aid in identifying where and when slugging is initiated.

3 Use dynamic simulation to identify unstable transient conditions during the design phase for well tubulars.

4 Use a dynamic simulator to evaluate alternatives to stabilize an unstable well.

b Use Dynamic Simulation to Determine when to use Gas-Lift to Re-Start Wells

1 Use dynamic simulation to evaluate the reasons to initiate gas-lift, such as high water cut, low bottom-hole pressure, poor well inflow performance, or high back pressure in the surface facility.

2 Use a dynamic simulation model to match the well’s current flowing conditions with the measured field data and run a sensitivity analysis for a range of different conditions.

3 Use dynamic simulation to determine if a well can be put back online without the need of gas-lift.

c Use Dynamic Simulation to Determine when to Start Gas-Lift in a Flowing Well

1 Use dynamic simulation to help define the optimum time to switch from natural flow to gas-lift.

2 Use a dynamic model to predict the optimum injection point and the required amount of lift gas for optimum well performance.

d Use Dynamic Simulation To Determine The Need To Start Gas-Lift Due To Liquid Loading In Gas Wells.

1 Use dynamic simulation to predict the reasons for liquid loading with water and condensate.


Ch.

Sect.

Practice Number


2 Use dynamic simulation to provide a better understanding of multiphase flow and its role in liquid loading. The onset of liquid loading is triggered by film flow reversal rather than droplet flow reversal.

3 Use dynamic simulation to help obtain realistic values of reservoir abandonment pressures.

4 Use dynamic simulation to aid in modelling and selection of the optimum deliquification method: velocity strings, chemical injection, plunger lift, gas lift, or pumps.

e Use Dynamic Simulation To Aid in Optimizing Intelligent And Complex Well Completions.

1 Use dynamic simulation to aid in optimizing the design of intelligent wells. Various well completion options can be compared.

2 Use dynamic simulation to aid hardware selection for extended reach, maximum contact reservoir wells and multi-laterals.

3 Use dynamic simulation to optimize recovery from complex intelligent wells.

4 Use dynamic simulation to help reduce well intervention costs by upfront design to allow well reconfiguration without the need for physical intervention.

5 Intelligent wells/completions benefit from real-time production information and control, which is supported by dynamic simulation.

f Use Dynamic Simulation To Aid in Understanding When Cross Flow And/Or Commingling Occur

1 Use dynamic simulation to aid in understanding transient flow conditions and cross flow occurrences in multi-layer, multi-laterals, and multiple zone horizontal wells. It is possible for cross flow to occur between zones during well shut-in and while the well is flowing.

2 Dynamic simulation may be used to help optimize design and operation of multi-layer or multi-lateral well completions.


Ch.

Sect.

Practice Number


3 It is important to model the well trajectory. Create enough pipe segments to precisely estimate and optimize commingled production from each zone of interest.

4 Model each zone as a separate source/well so that fluid production, cross flow, and fluid movement from each zone can be evaluated for different flowing bottom-hole pressures.

5 Dynamic simulation may be used to help evaluate commingling different production zones or producing them separately for proper reservoir management.

g Use Dynamic Simulation To Optimize Gas-Lift Well And System Shut-In And Start-Up Operations

1 Ensure that shut-in and start-up flow assurance dynamic simulation studies are performed on the full well system to avoid errors in the flowline-riser-facilities design.

2 The shut-in and start-up conditions need to be included in the reservoir-to-facility production system model to define the interactive behavior.

3 Use a dynamic simulator to help configure an automated control system to address unstable operations caused by shut-in, start-up, and the gas-lift operations.

V Information Required for Dynamic Simulation

a Fluid Properties

1 Use black oil models only for specific applications, as they are based on the properties of hydrocarbon mixtures from one specific region, and are only valid for a specific range of pressures and temperatures.

2 Use fully compositional fluid models for dynamic simulation.

b Wellbore Profile and Well Schematic

1 Accurately input well trajectory. Limiting the number of points to describe the well profile can lead to errors in slugging


Ch.

Sect.

Practice Number


predictions.

2 Accurately input well geometry. Use diameters with associated depth intervals in the model.

3 Input any relevant well equipment; valves, chokes, nipples, with their pressure drop characteristics, internal diameters, and depths.

4 Input an accurate well completion design including all casings and annular fluids, cement and formation thicknesses, and heat transfer coefficients for each constitutive material; to estimate the radial heat losses in the wellbore.

5 The use of the “overall heat transfer coefficient” to estimate heat losses in the wellbore is not recommended.

c Inflow Performance Relationship At Inflow Point

1 Input an accurate, standard inflow performance relationship (IPR) for the type of reservoir, for design and forecasting purposes, i.e. “what if” scenarios.

2 Use a quasi-dynamic IPR when the dynamic model is used for matching measurements. The selected variables, e.g. skin, non-Darcy skin, and permeability, can be input as time-series so the impact of the transient behavior can be reflected.

3 Use the distributed IPR approach when necessary for well clean-up, multi-laterals, and extended reach wells. This requires dividing the productive interval into segments or zones and calculating individual IPR’s.

d Boundary Conditions

1 Specify reservoir pressure and temperature for every inflow point and bottom node boundary. These can be input as time-series if necessary.

2 Specify wellhead pressure and temperature, assuming the model stops in the wellhead. These can be input as time-series, if necessary.

3 Specify the well’s initial conditions and fluid contents and the associated pressures and temperatures, including soil


Ch.

Sect.

Practice Number


temperature gradient, surface-subsea temperature gradient, and ambient temperature.

4 Specify for the risers, a detailed temperature profile from sea surface to mud line, including variations in water current velocities. This is recommended when there is potential for hydrates or production chemistry problems.

5 Enter any planned changes in the wellhead and surface injection pressures, or in gas-lift rate as time-series so that their impact on the transient behavior can be reflected.

VI Application of Dynamic Simulation

a Integrated Modelling

1 Define the limits and composition of the model based on the study objectives.

2 Gas-lift and naturally flowing wells are parts of systems that need to be modelled, covering the range from reservoir to facilities.

3 Model a single well and validate the model when it is at an early design stage and/or when the initial troubleshooting is focused on a particular well.

4 Make the model as simple or as complex as required. For instance, the annulus can also be included and the counter-current heat transfer effect of injecting a relatively cold lift gas and producing a hot reservoir fluid in the tubing can be evaluated.

5 Use dynamic simulation to assist in proper design of the casing, tubing, and wellhead to withhold the generated stresses produced at start-up.

6 Use an integrated dynamic simulation to evaluate interactions between components in the production system.

7 Couple the dynamic simulator model with a dynamic near-wellbore reservoir simulator if a strong reservoir-wellbore interaction exists.

b Real-Time Modelling

1 Use real-time online dynamic simulation and animation to generate responses at a frequency consistent with observations.


Ch.

Sect.

Practice Number


2 Use real-time, online dynamic simulation output to evaluate and improve well shut-in and start-up procedures.

3 Use a real-time online dynamic simulator model to evaluate hydrate formation potential that may result from well shut-in and start-up.

4 Use the online dynamic simulator as an advisor and a data source by creating virtual instruments where no functioning instrumentation exists.

5 Use online real-time dynamic simulation when a range of operating behaviours wider than covered by other methods, is required.

6 Use the real-time online dynamic simulator as a training tool for personnel involved in design, operation, troubleshooting, and optimization.

7 Use online real-time dynamic simulation to assist in performing routine production operations as listed in Chapter 6.

c Use Of Dynamic Simulation Modelling For Gas-Lift System Management

1 Use a dynamic simulation model to evaluate if the mandrel spacing and unloading valve designs will work and unload as intended.

2 Use dynamic simulation to evaluate the causes of unstable operation.

3 Use a dynamic simulator to adjust the operating parameters until the unstable performance of a well can be matched, demonstrating possible causes.

4 Once the cause(s) of instability have been determined, adjust operating parameters, and evaluate the changes.

5 A dynamic simulator can assist in finding the best operation of a gas-lift well, when the true optimum gas injection rate is not available.

6 Use a dynamic simulator to determine the optimum gas


Ch.

Sect.

Practice Number


injection rate and pressure for riser gas-lift.

7 If it isn’t possible to mitigate slugging, use a dynamic simulator to predict the size and arrival time of slugs so action can be taken to avoid upsets to the production facilities.

d Appropriate Dynamic Simulation Techniques And Their Implementation

1 Use dynamic simulation to assist in understanding flow behavior for technical, operational, and health, safety, environment (HSE) integrity during the field life cycle.

2 Steady state techniques are most appropriately for steady state conditions.

3 Dynamic simulation techniques are most appropriately applied for dynamic conditions but should apply to steady state.

4 Optimize combined use of both techniques without compromising the quality of the design and the operational integrity of the system.

5 Use dynamic simulation to examine conditions of potential risk and catastrophic failure.

6 Use steady state techniques to provide a system design which can then be evaluated with dynamic techniques.

7 Use dynamic techniques to take into account time dependant operating practices.

8 Use dynamic analysis to establish operational guidelines to avoid production chemistry problems during shut-in, start up, and ongoing operations.

9 Initially build a dynamic model to analyse the start-up and shut-in operations. Define the time required to reach stable flow. Input the validated stable correlations into steady state software models to use their capabilities.

10 Use dynamic simulation to optimize the design of individual components in the production system and integrate them.


Ch.

Sect.

Practice Number


11 Build the most simple dynamic simulation model required for the particular simulation objectives. The part of the total gas-lift system to be modelled depends on the study objectives defined in Chapter 6.

12 Use a quasi-dynamic IPR if the interaction between the near-wellbore reservoir and the well plays a dominant role in the dynamic behavior of the system. Cases where the dynamic wellbore/reservoir interactions may be strong are listed in Chapter 6.

13 Integrate the dynamic simulator with geo-science and/or risk simulation and decision analysis software to obtain a technical-operative information management system to improve field development decisions.

VII Information Provided by Dynamic Simulation

a Slugging Flow

1 Use a dynamic simulator to properly define any slugging flow conditions as well as flow stability.

2 Use dynamic simulation to properly define hydrodynamic slugging conditions which are generated by slip between the liquid and gas phases.

3 Use dynamic simulation to define terrain and/or well trajectory induced slugging.

4 Use dynamic simulation to define the severity of slugging conditions generated by risers, which are an integral part of offshore and subsea production and well servicing systems.

5 Use dynamic simulation to define where slugs originate, their causes, and their size and frequency.

6 Use dynamic simulation to understand the potential problems for stable multiphase flow, as listed in Chapter 7.

b Water Effects On Corrosion And Hydrates


Ch.

Sect.

Practice Number


1 Use dynamic simulation to define water accumulation at any point in the system, and its impact on hydrodynamic and terrain induced slugging, for liquid loading conditions and related internal corrosion susceptibility.

2 Use a dynamic simulator to determine the following components at each location in the system: gas, vapor, oil/condensate droplets, water droplets, oil/condensate film, and water film. If water is present at the surface of the pipe, it may induce a corrosive environment.

3 Use a dynamic simulator with corrosion models to identify not only the areas of the well and flowline with the highest risk for corrosion but also the corrosion rates.

4 Use a dynamic simulator to define the corrosion mitigation plan which is dependent on the changing operating conditions.

5 Use dynamic simulation to predict inhibitor distribution and estimate the type and amount of inhibitor required to eliminate or minimize corrosive condition.

6 Use dynamic simulation to analyse how the flow conditions will affect the structure and strength of protective corrosion product layers.

7 Use dynamic simulators to obtain information required to develop risk-based corrosion susceptibility profiles.

8 Use dynamic simulation to estimate when, where, and under which conditions hydrates may form in a production system based on the difference between a hydrate temperature and fluid temperature.

9 Use dynamic simulation to reduce uncertainty by rigorous screening of various inhibition options.

10 Use dynamic simulation to compare different hydrate control methodologies such as insulation, active heating, and inhibition.

11 Use dynamic simulation to aid in determining the best inhibitor injection location.


Ch.

Sect.

Practice Number


12 Use dynamic simulation to aid in estimating the amount of inhibitor.

13 Use dynamic simulation to track the amount of inhibitor in the water and gas phases in the well/pipeline to ensure enough is available for inhibition purposes.

14 Use dynamic simulation to aid in developing operating guidelines to ensure the right amounts of injection and distribution of inhibitors for all operating modes.

15 Use dynamic simulation in the design phase to aid in developing a production system with an acceptable level of risk.

c Production Chemistry

1 Use dynamic simulation to evaluate production chemistry issues and develop cost-effective field production strategies and operating integrity. There are increased risks associated with long sub-sea tiebacks, dry tree risers, and extended export pipelines in cold ambient water temperatures.

2 Use dynamic simulation to aid in analyzing the effects of high wax content crudes. Wax gelation is less common in steady-state flow than wax deposition, but it can have even greater impact during transient operations such as shutdowns and start ups.

3 Use dynamic simulation to calculate where and when fluid temperatures fall below wax appearance temperature (WAT) and the wax deposition rate.

4 Use dynamic simulation to predict the need for the operating situations listed in Chapter 7.

5 Use dynamic simulation in the design phase to develop a production system with an acceptable level of risk.

6 Use dynamic simulation during the design process to provide key performance indicators for profiling well-pipeline temperatures and wax build-up.

7 Use dynamic simulation in real-time, online well-pipeline


Ch.

Sect.

Practice Number


monitoring such as pigging operations.

d Gas-Lift Valve Performance

1 Use a valve performance model to obtain gas throughput vs. upstream and downstream pressure.

2 Use a valve performance model to aid in evaluating conditions during unloading.

3 Use a valve performance model during the design phase to evaluate the performance of port size of the valve.

4 Use a valve performance model during the simulation phase to predict performance with the given valve characteristics.

e Well Equipment

1 Use dynamic simulation to define where the sub-surface safety valve (SSSV) should be located.

2 Use wax/hydrate dynamic modelling to define the equipment location points where wax and hydrates can form.

3 Use dynamic simulation to assist in establishing operational guidelines to avoid/minimize wax/hydrates deposition by inhibitor injection and plan remedial wax prevention and cleaning schedules.

4 Use dynamic simulation to evaluate the separator backpressure effect.

5 Use dynamic simulation to evaluate the riser effects and pressure required to efficiently lift fluids through the riser.

f Well Design

1 Use dynamic simulation to aid in designing wells and total production systems for the field life cycle.

2 Use dynamic simulation to predict slugging flow and estimating water accumulation.

3 Use dynamic simulation to aid in predicting the amount of lift gas required and the optimum injection location; riser base,


Ch.

Sect.

Practice Number


wellhead, or downhole.


3. Introduction to Dynamic Simulation of Gas-Lift Wells and Systems

Document ObjectivesThe application of multiphase flow transient numerical simulation (dynamic simulation) techniques in wells and production systems has become an important methodology to ensure:

Wells/field life cycle sound engineering design,

Optimal operation guidelines,

Optimization of investment and operating costs,

Production optimization, and

Minimization of risk, safety hazards, and environmental impact.

The development of oil and gas fields continues to progress towards increasingly hostile environments requiring sub-sea and deepwater facilities and more complex well completions. The use of long horizontal, multi-layer, multi-lateral, big-bore, and intelligent wells have become more prevalent and are no longer the exception. High pressure, high temperature (HP-HT) reservoirs and deepwater, cooler environments present more complex production chemistry and flow assurance problems. Therefore, there are requirements to more accurately model these systems.

The main objective of this document is to create recommended practices for the application of dynamic simulation in gas-lift wells and systems and present guidelines to facilitate the application of this technique to optimize well/system integrity, operations, life cycle design, and production. Although the primary focus is on gas-lift, the document addresses a broad range of artificial lift and natural flowing systems and topics (e.g. gas well liquid loading). In principle gas-lift is an extension of natural flowing systems. Furthermore, most of the dynamic simulation recommendations are not only specific to gas-lift system issues (e.g. stable flow, hydrates, waxes, corrosion, liquid loading, and complex wells) but can be implemented in other types of production systems (e.g. natural flowing wells).


This document is designed for managers, production technologists, reservoir engineers, facilities engineers, production engineers, well testing engineers, well analysts, operators, and researchers who want to gain a general understanding of dynamic simulation, areas of application, added value, and benefits. This document also compares transient versus steady state techniques and provides readers with the required understanding of when and how dynamic simulation techniques should be applied.

Dynamic Simulation - Definition and Basic ConceptsThe term “dynamic simulation” has been used and misused. “Dynamic simulation” is defined and used as a short cut for multiphase flow transient numerical simulation. Some problem-solving schemes inter-relating the solutions given by steady state techniques at different snapshots in time are sometimes called dynamic simulation techniques, but these are not truly transient or dynamic considering that there is not continuous analysis of the multiphase phenomena. That is, what is happening between the selected time snapshot points is unknown. It is also important to understand the differences between “dynamic behavior” which describes changes in real time and “transient behavior” which describes changes over time.

The dynamic simulation techniques were pioneered by the nuclear industry to predict two-phase flow transient behavior with the accepted accuracy required to analyze nuclear reactors since dynamic instabilities could lead to plant collapse. The computer techniques were adapted to the oil and gas industry in 1980 (first pipeline simulator was made from a reactor model) and the advance of computer technology enhanced the current use of this technique.

Dynamic simulation is a proven technique applied for over 25 years by facilities engineers for pipeline and slug catcher design. The application of multiphase flow transient numerical simulation in wells is a new practice which requires different understanding and expertise. Multi-discipline teams or cross-discipline experience are required to properly build and integrate the well model (with the corresponding reservoir inflow performance boundary conditions) into the total production system model.

The development of offshore, subsea, and deepwater fields and the use of more sophisticated drilling techniques and well completions require more robust pressure, temperature, flow regime, and liquid hold-up predictions. The unique features and flow assurance requirements, along with the high associated capital costs, clearly merit detailed dynamic analysis in wells and integrated production systems. The multiphase flow transient conditions must be fully evaluated and understood for a sound engineering design and safe operations.


Dynamic simulation provides the possibility of building a virtual well model that can be used to analyse "what if" case scenarios and predict specific results. It is used to understand transient well/system behavior and determine the optimum process to eliminate/minimize transient problems that cannot be fully predicted by using steady state analysis techniques[1]. Furthermore, once the dynamic well model is validated, it can be used as a virtual gauge and/or a virtual downhole temperature survey during production/injection operations.

Well dynamic simulation should be used during feasibility and conceptual studies and at any stage of the well life cycle to "virtually" run through a complete case scenario and predict the well multi-phase flow behavior (including liquid hold-up, pressure and temperature trends, and profiles). New field development complex operational situations require this technique to optimize technical, operational, and HSE integrity during design and operation of production systems[2}.

Dynamic simulation is capable of modelling the well/system multi-phase flow behavior from the static initial conditions (zero rates) to the steady state flow conditions, confirming whether these conditions can be reached. Therefore, the area of applicability is increased over steady-state techniques. See Table II-1.

Table II-1 – Main areas of application of Dynamic Simulation


Dynamic simulation results are tipically used to support project decisions in the following areas:Flow assurance threat Wells Pipelines Process Facilities

Flow delivery through field-life

• Verification of planned production• Maximum pressure and temperature• Production optimization• Complex wells (Intelligent, Multi-lateral. Multi-layer, etc.)• Artificial lift design – GL, ESP, PL, etc.• Optimal routing to pipelines• Gas-Lift compressors shut-down• Ability to re-start• Time to re-establish full flow potential• Crossflow• Commingling fluids• Water accumulation• Liquid loading• Watercut limit• Reservoir depletion

• Pipeline packing / unpacking• Start-up / Shut-in• Operation of twin parallel lines• Application of multiphase pumps• Product composition from comingled fields• Component tracking (i.e. MEG)

• Control stability• Production optimisation• Hot oil circulation• Subsea separation

Liquid surges • Flow stability• Liquid loading• Velocity strings• Optimal use of Gas-Lift

• Slug break-up• Designing successful pigging operations

• Vessel sizing• Surge control

Hydrates & Wax • Hydrates potential (when, where)• Wax potential (when, where)• Inhibitor deployment• SSSV placement• Wax scrapper runs frequency

• Design of insulation / bundle / heating medium• Inhibitor deployment• Water accumulation

• Handling wax volumes

Integrity & Safety • Production operations• Well clean-up• Well testing• Well control operations• Well blowout/killing operations• Workover operations• Drilling operations• Water accumulation• Annular P-T increased when fluids trapped (no venting)

• Pressurization or depressurization within material limitations• Identification of high corrosion risk areas• Location and conditions of reverse flow

• Flare system requirements and capabilities• Identification of leaks from routine data• HIPPS systems

Dynamic simulation does not replace steady-state techniques but completes the areas not fully covered by these methods. The use of steady-state techniques to describe transient events is not recommended. The earlier dynamic simulation is adopted in the life of a project, the better design and economic decisions can be made, speeding-up and enhancing the whole study process[3-4]. See Fig. II-1. Furthermore, the original dynamic model can be updated and upgraded when more data is available[5] and can be used in real-time after commissioning[6].


Figure II-1 – Dynamic simulation wheel

Dynamic simulation techniques use a one dimensional (1-D Grid) transient multi-phase flow numerical simulator program capable of modelling the hydraulic and heat transfer effects at any point and time in wells, pipelines, risers, and networks – from the reservoir to the facilities[7-8]. Equipment such as valves, chokes, packers, compressors, separators, and controllers can be included in the model. Annular flow and counter-current heat transfer effects can be modelled when necessary. Fluid composition is input as a fluid file and a proper fluid characterization[9] is necessary. The simplistic black-oil input is optional but only recommended for particular applications.

Several dynamic simulation models exist and have been available for over two decades. These include the Two-Phase Model (Gas-Liquid), extended Three-Phase Model (Gas-Oil-Water), and Drift-Flux Models which are the most adopted ones. The Two-Phase and extended Three-Phase models are based on complex one-dimensional multi-fluid representations of the multiphase hydrodynamics, whereas Drift-Flux models are based on a drift-flux formulation which treats the two phases as a mixture. Gas is assumed to be drifting along with liquid where the gas velocity can be described by a slip relation. Drift-flux models are simpler models developed to be fast to compute and avoid convergence problems when the well models are coupled with reservoir simulators[10].

Two-Phase and extended Three-Phase models[11] have been verified over a wide range of applicability and they have been accepted by the industry as usable simulators for transient multiphase flow of oil, water and gas in wells and pipelines. The Three-Phase (or Two-Phase if three phases are not required) simulators are able to quantitatively predict complex and varied physical phenomena such as slugging and compositional tracking in typical well and pipeline configurations. Therefore, the Three-Phase simulator is used as an example only for the dynamic simulator descriptions presented below. It is recommended to evaluate all the available software packages before making a selection.

The numerical solution scheme shown here is a semi-implicit integration method which allows for relatively long time steps with efficient run times. A set of coupled first order, non-linear, one dimensional partial differential equations, with rather complex coefficients are used:

• Five mass conservation equations

– Gas


– Hydrocarbon bulk

– Hydrocarbon droplets

– Water bulk

– Water droplets

• Two momentum conservation equations

– Gas + droplets

– Liquid bulk

• One energy conservation equation

– Mixture (only one temperature)

• Constitutive equations

The closure laws for mass, momentum, and energy transfer are semi-mechanistic and require experimental verification. Small and large scale flow loops were used to verify the example Three-Phase simulator. No flow loop can represent all possible multiphase flow situations but the test loop combines a vertical elevation (riser) higher than 50 m (164 ft), working pressures as high as 90 bar (1,300 psi), internal diameters from 25.4 to 304.8 mm (1 to 12 inch), and a maximum total length of 1000 m (3280.84 ft) with the possibility of changing the slope in defined sections[12].

The one-dimensional pipe geometry is divided in sections. See Fig. II-2.


Figure II-2 – Wellbore Model Pipe Sectioning

Each section length has to be longer than half or shorter than twice the length of the adjacent section. Section length is selected based on a compromise between accuracy and simulation run time depending on the case under study. The longer the section length, the smaller the simulation time but the accuracy is lower. Mass transients generally travel much slower than pressure transients, therefore to obtain more stable simulation runs, a staggered grid is used: variables such as pressure, temperature, and liquid hold-up are calculated at the center of the section, and boundary variables such as flow rates, flow patterns, and velocities are calculated at the section boundaries. See Fig. II-3.


1 2 543

1 2 543

1,2,3,…,5 (inside) : section volumes

1,2,3,…,6 (outside): section boundaries

6

P, T and liquid Hold-up are calculated at the volume center

Qg, Qo, Qw, flow regime and velocities are calculated at the section boundaries

Figure II-3 – Section Volume and Section Boundaries

To rigorously calculate the radial temperature for each pipe section, a wall is associated to describe the number of radial concentric layers (casings and annular space fluid properties) based on the well completion schematic. See Fig. II-4.

Steel

Cement

Formation

MD 4935.9 m

MD 3153.8 m

BRANCH: WELL-LOWWALL: Tubing-3

MD 2766.1 m BRANCH: WELL-LOWWALL: Tubing-2

MD 1432.2 m

BRANCH: WELL-UPPWALL: Tubing-1

Figure II-4 – Walls: Well Completion Schematic

Properties include thickness, density, thermal capacity, and conductivity. In addition, the temperature and outer convective heat transfer coefficients of the surroundings are required.


Two basic flow regime classes are modelled. See Fig. II-5:

• Distributed (bubble and slug flow)

• Separated (stratified and annular mist flow)

Figure II-5 – Dynamic simulator flow regime groups

Transitions between the regime classes are determined on the basis of a minimum slip concept, in combination with additional criteria. Flow is divided into gas, vapor, oil, and water droplets, and oil and water film. Changes in fluid composition in the direction of flow are determined based on pressure and temperature changes.

Initial conditions should be defined:

• Start with the well full of drilling fluids (mud, brine, and/or diesel), or

• Start with the well filled with production fluids; water and oil to a certain fluid level and gas.

If the well is connected to a flowline, the flowline initial conditions should be defined:

• Start with the flowline filled with gas (empty), or

• Start with the flowline filled with water or any liquids.

Stratified flow

(Annular flow)

Dispersed bubble flow

Slug flow

SEPARATED

DISTRIBUTED


Boundaries conditions should be defined:

• Reservoir

• Topsides (i.e. ambient temperature and wind velocities), and

• Surroundings (i.e. sea floor, sea current velocities, and soil temperatures).

The reservoir boundary input is explicit. The reservoir parameters are given at steady state reservoir conditions, which is adequate when the “predictive” approach is used. The available IPR models in the dynamic simulator are:

• Constant productivity index

• Forchheimer model (gas wells)

• Single Forchheimer model (high pressure gas wells)

• Vogel equation (oil wells in gas saturation drive reservoirs)

• Vogel combined with PI (oil wells where reservoir pressure is above Bubble Point)

• Backpressure (gas wells)

• Normalized (saturated oil wells)

• Tabulated IPR curved (any preferred IPR input)

Software models allow for a quasi-dynamic, time-series boundary input (quasi-transient IPR input) for the key reservoir properties such as pressure, temperature, mechanical skin, non-Darcy skin, permeability, and net pay [1]. This option is relevant when the “matching” approach is used and the model is validated by matching with measured data. Nevertheless, the best option to gather all the well-reservoir dynamic interaction is to couple the dynamic well model to a near-wellbore[13-14-15] or full reservoir dynamic simulator[16], but this adds complexity to the simulations. The quasi-dynamic IPR input will help to pre-define the key variables required to match the data.

Some simulators offer different visual outputs and numerous variables can be selected to analyze the results:

• Trend plots – show the change in a parameter versus time at a specific location


• Profile plots – show the change in a parameter along the flow path over a period of times, at a specified frequency

• The viewer – shows a video-like animated representation of a parameter as it changes continuously with time within a simplistic pipe model. See Fig. II-6.

Plot 1 = Initial Conditions

Plot 2 = Brine arrival at surface (Gas in grey)

Plot 3 = LCM (Mud) being produced

Plot 4 = Clean-up completed (residual liquid in rat hole)

Figure II-6: Well Clean-up with LCM Viewer Snap-Shots Sequence


Difference between Steady-State and Dynamic Simulation TechniquesDue to its historical development and the type of operational conditions, the analysis of multiphase flow phenomena can be divided into two different techniques:

• Steady State Techniques

• Dynamic Simulation (Transient) Techniques

Steady State techniques can be divided in two different methodologies:

• Empirical Methods

• Mechanistic Methods

The Empirical Methodology (originated in the early 1950’s) is based on correlations developed from data collected by the researcher. These correlations are equations used for prediction purposes for a defined range of operating conditions. Some correlations perform better than others and a number of different correlations may be needed to predict the hydraulic conditions of the resulting flow regime. Selecting the best set of correlations affects the accuracy of the predictions. For a good selection process, the specific conditions for which the correlations were develop needs to be known. Extrapolation beyond these conditions may make the process unreliable. Empirical Methods do not address the complex physical phenomena that occur in multiphase flow.

Since the mid 1970’s, progress has been made to understand the physics of multiphase flow in wells and flowlines, and several multiphase flow mechanistic models became available to simulate wells and pipelines under steady state and transient conditions. Mechanistic models try to mathematically describe the multiphase flow mechanisms including related fluid properties and physical relationships.

Mechanistic models may be more accurate and applicable to a wider range of fluids and operating conditions than empirical models.

Nevertheless. some mechanistic models have been formulated separately for wells, pipelines, vertical and horizontal flow, one, two or three-phase, and for the prediction of specific steady state or transient conditions such as the onset of slug flow and annular flow. Furthermore, as with the empirical correlations, some of the mechanistic models have been developed and verified using small diameter pipes/tubing (<101.6 mm) (< 4”), so this has to be also taken into account in big diameter wells.


Therefore, an evaluation of the existing empirical and mechanistic models needs to be performed and the specific conditions for which the models were develop needs to be known. The most popular empirical and mechanistic correlations are listed in alphabetical order in Table II-2 which includes a brief “recommended applications” column detailing which are the mechanistic correlations:

Table II-2 – Most Popular Multiphase Flow Correlations

These empirical and mechanistic models are used as correlations in steady state software packages, as listed in the software’s selection options. One of the


advantages of dynamic simulation is that it does not use correlations to connect two nodes in the system. Instead, it solves the set of coupled 1st order, non-linear, one dimensional partial differential equations at the given boundary conditions, for every grid section in the direction of flow between the two nodes, versus time. In this case, grid section length and therefore number of sections influence the accuracy of the simulation; the longer the section the shorter the simulation time but the lower the accuracy.

Another relevant advantage of dynamic simulation techniques is that they do not

use the flow regime map to define the type of flow. The flow regime map approach is not rigorously accurate. Flow regime transitions cannot be reduced to two defining parameters, gas and liquid velocity. In the Three-Phase dynamic simulator, P-T and Liquid Hold-up are interrelated. Phase transfer is a function of P and T. The Three-Phase interface mass transfer model takes into account condensation, evaporation, and retrograde condensation.

Even though they are case dependant, the limitations of traditional steady state techniques, when analysing steady state flow cases, are:

• Unable to predict terrain-induced slugging flow induced by risers, flowlines, and horizontal or deviated wells with terrain ups and downs

• Unable to perform stability analysis

• Unable to evaluate transient gas/condensate, gas well liquid load-up issues

• Use and selection of the best flow correlations: even though correlations and selection options have been improved.

The risk taken when using simplified techniques is higher if the well completion design generates terrain induced slugging and even higher if there are phase changes in the system. Steady state techniques may underestimate maximum wellhead temperatures, and may give incorrect wellbore temperature gradients or profiles. They do not capture the effects of fluid vaporization and condensation on the overall fluid temperature.

The main limitation of traditional steady state techniques is that they do not provide fully accurate engineering solutions for cases that are transient in nature:

• Flow behavior during well start-up and shut-down

• Stable flow

• Flow behaviour during rate changes

• Flow behaviour during well clean-up

• Flow behaviour during well testing

• Flow behaviour during liquid loading

• Flow behaviour during gas-lift unloading


• Dynamic behaviour of plunger lift

and

• Perform flow assurance studies

- Production chemistry

- Corrosion

- Chemical injection

A good comparison of steady state versus dynamic simulation techniques is flow stability prediction. As highlighted above, steady state techniques are not designed to predict stable flow if the production system contains a riser and/or the wells are horizontal or deviated. In these cases, one of the main applications of dynamic simulation is to define if the flow is going to be stable in each of the probable well/system design options. The multiphase flow slugging conditions must be evaluated and understood for a sound engineering design and safe operation. An incorrect prediction of stable flow can lead to selection of the incorrect tubing size. The right tubing size may eliminate the slugging conditions. To eliminate or minimize slugging conditions, it is necessary to know what is creating the slugging flow conditions and where they originate. Dynamic simulation can define and establish the size and frequency of the gas bubble (slugging severity). See Fig. II-7.

Figure II-7 – Slugging flow: front and tail of the gas bubble

Tracking the development of the individual slugs along the well and flowline is necessary to estimate the volume of the liquid surges out of the system.


The main potential problem areas for stable multiphase flow are:

• Terrain

• Inclination / elevation

• Rate changes

• Condensate–liquid content in gas

• Shut-in / Start-up

• Risers

For subsea and deepwater, the fluid behavior in the well, flowline, and riser may actually dictate the required artificial lift method, not the wellbore environment itself.

Ensuring stable flow or minimizing unstable flow is one of the recommended practices for well production optimization. Dynamic simulation offers a sound engineering technique to predict slugging, select the best method to eliminate or minimize slugging, and optimize production.

Dynamic simulation should be applied when the following individual or combined oil and gas production systems and conditions are encountered:

• Horizontal-inclined wells[17]

• Production-injection systems with risers[18]

• Tubing and annular flow with relevant counter-current heat transfer effects[19]

• Fluid composition that will significantly change in the flow path upstream of the system output point due to flashing or condensation[20]

• Commingling fluids in multi-layer, multi-lateral wells[21]

• Intelligent well completions using well control and production optimization equipment[22]

• Gas-lift wells which require prediction of stable flow and optimization [23-24-25-26-27-

28-29-30]

• Plunger lift used for gas well deliquification[31]

• Gas wells with liquid loading[32-33]

• ESP wells which required prediction of stable flow and optimization[34-35-36]

• Transient conditions such as flow behaviour during well start-up and shut-down[27]

• Flow assurance including production chemistry and corrosion[37-38-39-40]

• Well testing including wellbore storage and segregation effects[41-42-43]


• Well clean-up for removal of drilling and/or completion fluids from the wellbore[41-43-44-50]

• Well control including blowouts and killing procedures.[45-46]

• Workover evaluation analyzing fluid displacement (annulus-tubing, tubing-annulus)[47]

In gas-lift systems, the maximum benefits of dynamic simulation are obtained when the model is applied in real-time[48-49]


4. Typical Gas-Lift Well and System Operations

A variety of gas-lift system configurations and operational practices are in use throughout the industry. Each of these has unique characteristics and requires special considerations when using dynamic simulation techniques to model well performance. This chapter provides an overview of each operation, discusses both the steady state and dynamic aspects of each, and provides recommendations for how dynamic simulation can be used to address the dynamic aspects these operations.

Continuous gas-liftContinuous flow gas-lift is one of two major classes of gas-lift systems. In the continuous gas-lift process, relatively high pressure gas is injected downhole into the fluid column. This injected gas joins the formation gas to lift the fluid to the surface by one or more of the following processes:

Reduction of the fluid density and the column weight so the pressure differential between the reservoir and wellbore will be increased. See Fig. III-1-A.

Expansion of the gas so it pushes liquid ahead of it, which further reduces the column weight, thereby increasing the differential between the reservoir and the wellbore. See Fig. III-1-B.

Displacement of liquid slugs by large bubbles of gas acting as pistons. See Fig. III-1-C.


Fig. III-1: Continuous Gas-Lift Production Processes

4.1.1 Steady-state aspects

Continuous gas-lift is intended to be a continuous, steady process. These processes include the gas-lift injection pressure and rate, the gas-lift injection rate from the annulus into the tubing, the pressure profile in the tubing, and the pressure drawdown on the formation. However, some or all of these processes are usually not steady, and they can be very unstable, leading to significant well problems and loss of production.

4.1.2 Dynamic aspects

Often, due to operational issues, the gas-lift injection rate and pressure are not stable. In some cases, the injection rate can be controlled and made to be stable, but unless it is controlled, it will often vary with time and production processes.

Even if the injection rate is controlled, the injection pressure may fluctuate due to conditions in the well. This is most often caused by an imbalance


between the injection rate at the surface and the gas flow rate from the annulus to the tubing through the gas-lift valve or orifice.

This may be exacerbated if a well is “multi-pointing,” that is if it is injecting through more than one valve, through a valve and an orifice at the same time, or through a hole(s) in the tubing and a valve or orifice. This can be caused by inappropriate gas-lift valve design relative to the current operating conditions of the well.

Any unstable (dynamic) ituation in a continuous gas-lift well is less efficient han continuous, stable gas-lift. Therefore, steps are needed to reduce or eliminate instability.

4.1.3 Dynamic simulation

Dynamic simulation can be used in two primary ways on continuous gas-lift wells.

a. Design

Design of continuous gas-lift wells is discussed in API RP 11V6. For continuous gas-lift design, a design program (or manual process) is used to determine the spacing of the gas-lift mandrels, the setting of the gas-lift valves, the sizing of the gas-lift valve or orifice flow path, and the desired gas-lift injection rate and pressure. Typically, this design is performed in stages, with the mandrels being spaced when the well is first drilled and completed, or recompleted after a workover. The valves are run when it is necessary to place the well on gas-lift, or when the valves need to be changed to improve operation. The injection pressure is normally essentially fixed for a given field. But the injection rate can be, and often is, changed frequently by the field operator, or by circumstances in the field.

A dynamic simulator can be used to evaluate a design by running the simulator with the intended mandrel spacing, valve configuration, injection pressure, and injection rate. The dynamic simulator can give an indication if the planned design will unload properly and produce continuous, stable operation or if the well will be unstable. If it will not unload as intended, or if it will be unstable, the design can be modified until the predicted performance of the well is stable. If the dynamic simulator can be included in an optimization program, the program can automatically modify various parameters such as the valve or orifice port/choke size, and the gas-lift injection rate, to determine the best design for continuous, stable operations48-49.


b. Problem diagnosis

When a continuous gas-lift well is on production, it may not unload as desired, or it may be unstable as indicated above. A dynamic simulator can be used to help diagnose the cause(s) of the problem, and to indicate how the design or operation may need to be changed to stabilize the well.

In an automation system, a dynamic simulator can be automatically run on each gas-lift well whenever a problem is detected by the surveillance system. Problem diagnoses and recommended solutions can be presented to the operating staff on a routine basis.

Intermittent gas-liftIf a well has a low reservoir pressure or a low producing rate, it can be produced by a form of gas-lift known as intermittent lift. This is the second major classification of gas-lift systems. As its name implies, this system produces intermittently or irregularly and is designed to produce at the rate at which fluid enters the wellbore from the formation.

In the intermittent flow system, fluid is allowed to accumulate and build up in the tubing at the bottom of the well. Periodically, a large quantity of high pressure gas is injected into the tubing very quickly underneath the column of liquid and the liquid column is pushed rapidly up the tubing to the surface. This action is similar to firing a bullet from a rifle by the expansion of gas behind the rifle slug. The frequency of gas injection in intermittent lift is determined by the amount of time required for a liquid slug to enter the tubing. The length of the gas injection period will depend upon the time required to push one slug of liquid to the surface. Normally, a standing valve is installed beneath the gas-lift valve to prevent pressure and gas flow back into the low pressure formation. This method of lift is a cyclic operation and the cycle can be divided into four periods:

Inflow period. During this period, the liquid flows from the formation into the well bore and collects in the tubing above the standing valve and the gas-lift valve. The gas-lift valve is closed during this period and the surface tubing pressure is reduced to a minimum to allow the maximum inflow rate. See Fig. III-2-A.

Lift period. When sufficient liquid has collected in the tubing, the gas-lift valve opens and injects high pressure gas to lift the slug to the surface. Some fallback occurs due to liquid coalescing in a film on the wall of the tubing and liquid droplets in the gas slug which lack sufficient velocity to travel to the surface. See Fig. III-2-B.


Production period. Fluid is produced at the surface. A rapid drop in tubing pressure pulls in gas from the casing. No inflow occurs during this period. See Fig. III-2-C.

Pressure reduction period. After the gas-lift valve closes and the slug flows through the wellhead and to the separator, the lift gas pressure is dissipated and the inflow period begins again. The intermitting cycle is controlled by regulating the frequency of injection, the gas flow rate during injection, and the total quantity of gas injected during each lift period. See Fig. III-2-D.

There are two primary means of intermittent gas-lift control, using a choke control or timer control. In choke control, gas is slowly injected into the casing from the surface, with the injection rate controlled by a surface choke or control valve. In timer control, a surface control valve is periodically opened and closed on a time cycle.

The advantage of choke control is that it causes a minimum impact or upset to the overall pressure of the surface injection system. The disadvantage is that the downhole injection process can only be modified by changing the operating gas-lift valve. The advantage of timer control is that the frequency and volume of each intermittent gas-lift slug can be controlled at the surface. The disadvantage is that the sudden rate and pressure changes on the surface can upset other wells in the system.


Fig. III-2: Intermittent Lift Cycle


Intermittent gas-lift is, by its very nature, a dynamic process. However, for it to be successful, each intermittent cycle must be consistent in its frequency and gas injection volume.

And intermittent gas-lift wells must be unloaded using the same process as is used for continuous gas-lift wells.


For an intermittent gas-lift well to be successful, its dynamic aspects of injection frequency and volume per cycle must be correctly operated.

The gas injection frequency must be designed and operated to permit an optimum amount of liquid inflow from the formation to the tubing during each cycle. If the frequency is too high, not enough liquid will have accumulated in the tubing, production will be minimum, and gas will be wasted. If the frequency is too low, an excessively large slug of liquid will be produced into the tubing. This can place an excessive amount of back pressure on the formation, thus inhibiting inflow from the formation to the


wellbore; and it can be difficult for the gas to lift the excessively large slug of liquid to the surface.

The gas injection volume per cycle must be correct to lift the volume of liquid to the surface. If it is too small, the liquid may not reach the surface and it may fall back to the bottom of the well. If it is too large, gas will be wasted.


Dynamic simulators can be used in a manner similar to that described for continuous gas-lift.

a. Design

Design of intermittent gas-lift wells is discussed in API RP 11V10. A dynamic simulator can be used to evaluate the design of an intermittent gas-lift well, determine if it will unload properly, and determine if it will operate properly from the operating gas-lift valve.


A dynamic simulator can evaluate the current operation of an intermittent gas-lift well. The simulator can determine if the injection frequency and gas injection volume per cycle are correct, or if changes should be made to optimize production per cycle, and the volume of gas injection per cycle.

Gas-assisted plunger liftOne special application of intermittent flow gas-lift is termed gas-assisted plunger lift, or plunger assisted intermittent lift. In these applications, the intermittent gas-lift installation is equipped with a plunger and related accessory equipment. The plunger traverses the length of the tubing string in a cyclic manner, providing an interface between the lifting gas and the produced liquid. The plunger sweeps more of the liquid film from the tubing wall, minimizing the liquid fallback. Although sand or solids in the tubing could prevent the plunger from operating successfully, plungers are commonly used to control paraffin deposits. Plungers may not work well in highly deviated or cork-screwed wells.


Fig. III-3 shows a down-hole plunger installation with the gas-lift valve located below the plunger. The surface wellhead equipment shows the lubricator/catcher to hold the plunger for its short time at the top.

There are at least two issues with plunger lift that need attention. First, the plunger must be designed so it can successfully pass through the upper gas-lift mandrels as it rises and falls in the tubing. Second, adding the plunger increases the cost and complicates the operation of the well, and many operators find that the added production that can be achieved by the lifting of the plunger is not sufficient to justify the added cost and complexity.

Fig. III-3: Gas-Assisted Plunger Lift



Gas assisted plunger lift is an enhanced form of intermittent gas-lift. The desired steady aspects of intermittent gas-lift pertain here as well. The goal is to time the injection cycles to optimize liquid inflow from the formation and control the injection volume per cycle to optimally lift the plunger and the liquid above it.

However, this is more difficult than normal intermittent gas-lift because the release and fall of the plunger must be coordinated with the gas-lift injection frequency and volume per cycle.


The dynamic aspects are similar to normal intermittent gas-lift, except now the dynamic aspects of catching, releasing, and timing the fall of the plunger must be taken into consideration.


As with normal intermittent gas-lift, a dynamic simulator can be used to assist with design and problem diagnosis. Dynamic simulators do not offer a plunger option but they have the option to simulate pig runs in pipelines. Dynamic simulators allow using the pig as a plunger in a wellbore. Modelling plunger lift wells could be difficult and may not be justified except when the optimization recommendations can be extrapolated to a big number of wells.

Dual gas-liftIn certain cases, wells are completed as dual gas-lift producers. This is generally driven by the desire to reduce drilling and completion costs where multiple formations are located in close vertical proximity to one another. Such installations are difficult to operate in conjunction with intermittent gas-lift applications. For this reason, dual gas-lift installations can be considered a special application of continuous gas-lift.

Dual gas-lift is defined as the producing of two zones from the same wellbore by gas-lift without commingling the well fluids in the wellbore. A variety of wellbore configurations exist for achieving dual gas-lift. The most common involves the use


of a single bore packer to isolate the upper zone from the lower zone and a dual bore packer to isolate the upper zone from a common gas-filled annulus. Such a completion is depicted in Fig. III-4.

Fig. III-4: Schematic of Dual Gas-lift Installation

In an attempt to reduce the interference issues which arise from injecting gas through a common casing-tubing annulus, dual gas-lift installations are often equipped with production pressure operated gas-lift valves. However, many other approaches are also used. This is discussed in detail in API RP 19G9.



Operation of a dual gas-lift well is intended to be continuous and stable, just like a single-string gas-lift well. However, due to the interference that can occur between the two sides of the dual, it is even more difficult to obtain stability.

4.4.2 Dynamic Aspects

Dual gas-lift can experience all of the dynamic aspects of single-string continuous gas-lift. But these are often compounded by the interference between the two zones. One typical problem is gas being over injected in one side of the dual while the other side is starved for gas.

4.4.3 Dynamic Simulation

As with single-string continuous gas-lift, dynamic simulation can be used to assist with design and problem diagnosis.

a. Design

Design of dual gas-lift wells is discussed in API RP 19G9. In principle, the design issues are similar to those of single-string wells. The differences are:

Usually one side of the dual is used for unloading. From this stand-point, it is similar to a single-string continuous gas-lift well.

The amount of gas injection must be shared between the two sides of the dual. To achieve this, the gas flow passage through the operating gas-lift valves or orifices must be carefully designed and controlled.

A dynamic simulator can be used to evaluate a dual gas-lift design, in a manner similar to that of a single-string gas-lift well. The dynamic simulator can define the amount of gas-lift gas going into each of the tubing strings from the total amount of gas injected in the common annulus and therefore total production can be optimized. The primary issues are:

Will the well unload to the bottom valve, which is normally installed slightly above the dual packer?

Will the desired amount of gas be injected into each side of the dual?

Will this injection be at the desired depth in both sides of the dual?


Will the injection pressure and rate be continuous and stable?


A dynamic simulator can be used to diagnose problems in dual gas-lift wells.

Is gas being injected into both sides of the dual?

Is it being injected at the desired depth?

Is the well stable?

If the well is not performing correctly, what needs to be done to modify the design or the operation to correct the problem(s)?

Single-point gas-liftSingle-point gas-lift is a special application of continuous gas-lift systems in which a single point of injection is installed downhole in the well. It can also be applied at the wellhead or at the base of a riser. Usually the design uses some form of orifice (no moving parts), with no unloading valves installed above that depth.

Such installations are often preferred in applications where reliability is of prime importance, as with subsea producers where interventions can be costly or impractical. By limiting injection to a single depth, these installations eliminate the possibility of re-opening upper valves during normal operation. Also, the need to re-enter the well to replace failed unloading valves is eliminated. Using an orifice as the operating valve also increases the life of the device.

In most applications, a significantly higher operating pressure is required to unload the well to this single depth. Also, the lack of unloading valves may result in a shallower operating point and reduced draw-down versus conventional applications. This depends on compressor capacity economics.

The steady-state aspects, dynamic aspects, and dynamic simulation of a single-point gas-lift well are similar to those for a continuous gas-lift well, with the following exceptions:

There are no unloading valves, so these don’t need to be considered.

There is only one point of injection, so multi-point injection doesn’t need to be considered.

Often this technique is used for sub sea wells so it can be more difficult to diagnose problems, since it can be difficult to obtain information on well-head injection pressure and other parameters.

Dynamic simulation is necessary to properly design and operate gas-lift single point injection wells and systems due to the reduced system’s flexibility. There is a


minimum surface injection rate required for the orifice to maintain sufficient annular backpressure for continuous downhole gas injection. This minimum injection rate depends on orifice size and flowing tubing pressure which is a function of the wellhead pressure, tubing size, IPR, reservoir pressure, and water cut.

Auto gas-lift Auto gas-lift is a term that refers to continuous gas-lift systems that use gas from a gas-bearing formation to lift fluids from another zone in the same well. The lift gas is produced downhole and allowed to enter the tubing through some form of gas-lift valve or flow control device, as depicted in Fig III-5. Because of the dependency between gas passage and the changing inflow performance of the gas bearing zone over time, it is often desirable to use intelligent flow control devices as the injection point in such wells. This allows operators to adjust the size of the orifice to provide appropriate gas passage as the gas bearing zone is depleted.

Fig. III-5: Schematic of Auto Gas-lift Well

The steady-state aspects, dynamic aspects, and dynamic simulation of an auto gas-lift well are similar to those items for a continuous gas-lift well, with the following exceptions:


There are no unloading valves, so these don’t need to be considered.

There is no surface injection, so this doesn’t need to be considered.

There is only one point of injection, so multi-point injection doesn’t need to be considered.

If a gas-lift valve or orifice is used to control the rate of gas injection into the producing well, there is little adjustment that can be performed, other than possibly controlling the back pressure on the producing well.

If an intelligent flow control device is used to control the rate of gas injection into the producing well, it may be possible to control this valve to optimize the well’s production and minimize pressure fluctuations.

Dynamic simulation can be used to help determine the optimum injection rate and/or back pressure to hold on the well.

Like in single point injection gas-lift, dynamic simulation is necessary to properly design and operate auto gas-lift systems due to the reduced flexibility.

Riser gas-liftIn some sub-sea installations, gas is injected at the base of the riser to assist with artificially lifting the well. This may be done in addition to injecting gas downhole or at the wellhead of the subsea well. Furthermore, if it is too difficult or expensive to inject gas in the well or at the wellhead, riser gas-lift may be the sole form of gas-lift used in the system. Depending on the economics, riser gas-lift may be used during the 1st part of the field life cycle, and after the critical limit for reservoir depletion and/or water cut increase, gas-lift can be performed at the wellhead or downhole in the well.

Use of riser gas-lift can reduce the complexity of artificially lifting such wells while reducing the cost of completing them. In addition, the injection of gas at the base of the riser may help to mitigate instability problems which are common in subsea wells containing long flowlines and/or long risers. Risers are terrain slugging generators. Furthermore, riser gas-lift may benefit several wells connected to the same riser while wellhead/downhole gas-lift only directly benefits the particular well.

Ideally riser gas-lift is like continuous gas-lift. It may use unloading valves in the riser, or it may use single-point injection at the base of the riser. A significant issue is that the liquid and gas that is entering the base of the riser, from the sub-sea flowline that brings fluid from the wellhead to the riser, may be unstable. There may be long slugs of liquid followed by long slugs of gas in the flowline. This can complicate control of gas injection into the riser base.


An important use of dynamic simulation is to understand the pressure and liquid/gas rate fluctuations in the flowline as they arrive at the riser base. Then, the simulator can be used to determine how to control the gas injection into the riser to assist in producing the liquid and gas up the riser and to assist in mitigating the large pressure and rate fluctuations or surges that can occur in the riser.

Based on reservoir depletion and/or water cut increase, dynamic simulation can be used to define the length of time that riser gas-lift can economically be applied in the system, and to select the optimum time to switch to wellhead and/ordownhole well injection, or to perform both.

Gas-lift for gas well deliquificationContinuous flow gas-lift may be used for deliquifying gas wells that experience liquid loading. Liquid loading occurs when liquids (normally water but sometimes condensate as well) accumulate in the wellbore below the end of tubing in the casing, or in the tubing itself. The liquid, being much heaver than the gas, holds back pressure on the formation and inhibits gas flow into the wellbore and up the tubing. Liquid will accumulate if the gas flow velocity is lower than the critical velocity that is needed to carry the liquid out of the well.

Deliquification is a process used to remove liquids from the wellbore so gas can freely flow. Many methods are used, including plungers, chemical systems, gas-lift, pumping systems, and others.

In gas-lift applications, the volume of gas injected is designed such that the combination of formation gas and injected gas will exceed the critical rate needed to prevent liquid loading. While gas-lift may not lower the flowing bottom hole pressure as much as an optimized pumping system, there are a number of advantages to using gas-lift for deliquification, including the ability to produce solid-laden fluids, the ability to operate at high GLR’s, and insensitivity to well trajectory.

The goal of such systems is to inject gas at a continuous, stable rate that is just high enough to exceed the critical velocity. Ideally, the gas can be injected below or near the bottom of the perforated interval so that all or most of the liquid is removed and kept from holding a back pressure on the formation. While enough gas is needed to reach the critical velocity, too much gas will be wasteful and may actually inhibit production due to excessive pressure losses in the production tubing.

A concern is that the amount of gas to achieve critical flow in the casing below the end of the tubing will be higher than the amount required in the tubing, since the cross-sectional area is larger. Therefore, if enough gas is injected to achieve


critical flow in the casing, it may be too much for the tubing. If the right amount is injected to achieve critical flow in the tubing, it may not be enough to lift liquids out of the casing below the end of tubing. A potential mitigation strategy is to install a dip tube below the production packer to act as a velocity string.

A gas-lift system in a gas well may require unloading valves. It may use an operating gas-lift valve or an orifice for the actual gas injection into the tubing.

A dynamic simulator can be used to help design the unloading process, select the depth of gas injection, determine the OD of a dip tube, and choose the rate of gas injection to just reach critical velocity without injecting too much. It can be used to help diagnose problems in wells where the well may be unstable or is beginning to experience liquid loading due to insufficient gas injection.

The steady-state aspects, dynamic aspects, and dynamic simulation of gas-lift for gas well deliquification are explained in detail in Chapter IV-D.

Gas-lift unloadingThe initial unloading process of a gas-lift well is the period of the well’s life during which the health of the artificial lift system is at its greatest risk. This is because the entire volume of fluids in the casing-tubing annulus must be displaced through the gas-lift valve ports or orifices, placing the valves at risk of flow cutting and subsequent failure. In addition, the unloading process is inherently unstable which can result in large variations in pressures and fluid rates/volumes into the production system. For these reasons, it is desirable to study this process in great detail prior to performing the operation in the field.

In most cases, the unloading process is designed using steady-state methods or programs. The gas-lift mandrels are spaced using these methods. The gas-lift valves are chosen, sized, and set using these programs. The unloading process is designed using these processes, or rules of thumb. This is not sufficient to fully understand the process.

The unloading process is and must be dynamic. First, liquid in the tubing/casing annulus is displaced through the valves in the well by applying gas pressure to the annulus. When the top valve is uncovered, gas can flow through it and begin to lighten the weight of liquid in the tubing. This can allow the level of liquid in the annulus to be depressed to the second valve. The process of moving to the second (and subsequent) valves, which requires the closing of the upper valve(s), is dynamic.

An important role of dynamic simulation is to model the unloading process, both during its design and subsequently during its operation. During design, the simulator can help to determine the best depths for each gas-lift mandrel, the best


liquid and gas flow characteristics of each gas-lift valve, and the best closing pressure of each gas-lift valve. A way to do this is to run the simulator with the design that has been calculated, and have it determine if the well will unload successfully with this design. If it will not, the design must be modified until successful unloading can occur. It is far better to run this process in advance with the simulator, rather than trying the unloading process in the field and potentially damaging the well and/or not unloading as desired.

During operation, the simulator can help determine if the unloading process worked as intended to unload the well to the desired operating depth, without damaging any of the unloading valves in the process. If an unloading valve is damaged (caused to leak), the well will not be able to work below this depth and will forever be inefficient.

Use of gas-lift for well kick-offAfter a well has been unloaded and placed on production, it will be necessary to re-start the well from time to time, following shut-in periods. This process is commonly referred to as “kick-off”27.

In gas-lift wells, unless the tubing, a mandrel, a valve, or an orifice are leaking fluid from the tubing back into the tubing/casing annulus, no fluids need to be displaced from the annulus through the valves, as in the unloading process. However, kick-off has some similarities to initial unloading. Like the unloading process, kick-off requires the well to step down to the operating point through a series of unloading valves. Also, like the unloading process, the kick-off process is inherently unstable. In such applications, dynamic simulation is useful for:

Determining if the well will flow naturally after it has been kicked-off. Some wells merely need to be started and then they will flow naturally without the need for gas injection.

Predicting the water cut limits for kick-off of naturally flowing wells after a shut-in period. In other words, which wells will need to be kicked off using gas-lift so they can return to natural flow, and when due to water increase/reservoir pressure depletion ratio a healthy natural flowing well will need gas-lift kick-off27. This practice:

– eliminates deferred production problems due to waiting for a workover rig

– helps to design natural flowing wells as future gas-lift wells, with optimum mandrel locations with dummy gas-lift valves which will be changed for the right gas-lift valves at the optimum time in the well’s life cycle.

Determining the required injection rate schedule to successfully return the well to production. Many operators merely begin normal operation (injecting gas),


when a well needs to be kicked off and returned to production. Questions which should be considered are:

- Is too much gas being used?

- Is gas been robed from other gas-lift wells in the system?

- Is there enough gas to put the well back online?

Use of gas-lift for wellbore clean-upWellbore clean-up is defined as the period when drilling debris, frac sand, and completion fluids need to be produced out of the well, along with produced hydrocarbons. The minimum rate and time required to clean-up the well are important. Well clean-up is a transient operation, starting with the well closed (zero rate) and the wellbore full of drilling fluids, and finishing when the well is at steady state conditions free of contaminants. Dynamic simulation is required to estimate optimum injection rate and time for well clean-up.

It may not be necessary or desired to use conventional gas-lift for this process. For example, it may be desired to not install gas-lift valves in the mandrels during this process. If normal gas-lift can’t be used, it may be necessary to inject nitrogen at a high pressure through a special shear orifice or circulating valve installed in the bottom mandrel.

A dynamic simulator can be used to help determine the gas injection pressure(s) and rate(s) needed to achieve the desired production rates to clean the debris, sand, and completion fluids out of the wellbore. The desired production rate will also depend of the time required to clean-up the well. This information is provided by the dynamic simulator41-43-44-50.

Gas-lift system distributionVarious configurations of injection gas distribution systems exist in the field. Because of the interdependency between production system components, the availability of injection gas and supply pressure can be affected by the operating regimes of adjacent wells and production equipment in such systems. For this reason, it is useful to model the performance of gas-lift wells in the context of the entire gas distribution system.

Often this modelling is performed with steady-state systems, but clearly there are dynamic effects that occur when wells are added to a distribution system, removed from the system, or their injection rates are changed. To understand this process, a field-wide simulator is needed that can model the performance of the entire gas distribution system, the source(s) of gas into the system, and the wells which are served by the system.


This dynamic simulator can help define how to control the distribution of gas to the wells served by a gas distribution system to optimize total production rate when there is a change in the supply of gas into the system, or a change in the demand for gas from the wells served by the system.

This process may be complicated if the injection rate into some wells can not be adjusted when there is a system upset. This may occur if some wells can not be changed since they may become unstable, if some wells are duals or intermittent, or if some are on well test and must be held constant during the test.

Use of un-dehydrated gasWhile it is recommended to always inject dry, dehydrated gas, it is not always possible to do so. Injection of un-dehydrated gas can lead to a number of problems including the formation of hydrates in the injection system and the flow cutting of gas-lift valves. Such issues should be studied to determine operating practices which may mitigate their occurrence.

Of particular importance is the formation of hydrates. These may form wherever a pressure drop occurs in the system, such as across a surface control valve or choke. A dynamic simulator can be used to understand the hydrate formation potential of the wet gas, help diagnose problems that can arise due to hydrate formation, and recommend procedures to mitigate these problems. More details are given is Chapter VI-D, on appropriate simulation techniques, and in Chapter VII-B on hydrates. Hydrate formation may be mitigated by dehydrating the gas, injecting methanol or another chemical in the gas, or heating the gas injection line or control valve.

Dynamic simulation can be use to evaluate the benefits of dehydrating the gas by comparing the results of using dehydrated versus wet gas-lift gas in the system. The annulus can be included in the model and the amount of liquid condensing in the annulus can be observed, as well as any annular flow effects affecting well performance.

Use of non-hydrocarbon gases such as CO2 and N2

In certain situations, wells may be gas-lifted using an inert gas such as CO2 and N2. For example, nitrogen is often used to start wells for initial clean-up and testing when a high pressure hydrocarbon gas source is not available. Similarly, in a CO2

flood, the nearly pure injection CO2 or the mixture of hydrocarbon gas and CO2

returning to the production station can be used to gas-lift the producing wells. Due to the specific properties of these gasses, special considerations should be taken


when simulating, analyzing, and designing such installations. Chapter VII-B gives details on CO2 corrosion.

Naturally Flowing Gas-Lift WellsIn certain situations, when wells can naturally flow initially but it is forecast that gas-lift will be required later in the well life cycle (due to water cut increase and/or reservoir pressure depletion), the wells are completed as gas-lift wells but with dummy gas-lift valves installed in the mandrels. When economically viable, this procedure eliminates the need for costly workover operations. A wireline unit is used to retrieve the dummy valves and install the required gas-lift valves designed for the producing conditions at the time of the operation.

Dynamic simulation may be used to define the economically optimum time to switch from natural flow to gas-lift. Furthermore, in areas where the natural flowing well needs to be shut-in and kicked off frequently (i.e. hurricane prone areas), the kick-off water cut limit can be defined using dynamic simulation and a safe well shut-in can be performed ensuring that the well can be put back online without the need of gas-lift. If the water cut is already above the amount where kick-off will be needed, the optimum gas-lift scenario can be planned in advance.


5. Recognize When Dynamic Simulation is Beneficial

More and more wells are being placed on artificial lift due to reservoir depletion, native water production increase, or water flood support increase. Generally more than one method of lift may be used; and individual methods may be classified from excellent performance to poor. In a depletion reservoir, high initial production rates may occur with rates declining quickly due to declining reservoir pressure and changes in inflow parameters. In this case a preferred artificial lift method may be continuous gas-lift. Normally, after natural flow, gas-lift is the preferred artificial lift system if enough gas is available. In offshore and subsea wells, gas-lift is the most used artificial lift system.

To estimate the optimum time to switch from natural flow to gas-lift, and to make gas-lift work efficiently, a good modelling tool is required. Basically there are two different types of modelling tools available; steady state and dynamic. The advantage of dynamic modelling, even though it is more complex, is it is helpful in understanding transient behavior of fluid flow and flow instability inside the tubing, annulus, and flowline. Chapter II-C, compares in detail the steady state and dynamic simulation techniques.

Use dynamic simulation to determine and respond when a well or system may be unstable.

- How to recognize instability.

There are several potential causes of instability in a naturally flowing well: decreasing reservoir pressure, increasing water cut, over-sized tubing for the current fluid production, decreasing total gas-liquid ratio, and increasing back pressure in the surface gathering system. To recognize and rectify these problems, a tool is needed to model the well in its current flowing conditions. The model may either be a steady state or dynamic model but certain flowing conditions warrant dynamic modelling to understand liquid loading, phase separation, and gas velocity issues due to multiphase fluid flow up the production tubing. Usually most completions are not vertical and may be highly deviated where theoretical correlations are not capable of accurately predicting the actual fluid flow results.

Even more in-depth analysis may be required for gas-lifted wells as there are additional reasons for unstable flow due to:


inefficient lifting caused by a leak through shallow unloading gas-lift valves

insufficient injection gas rate for the fluid rate and the tubing size

operating orifice not properly sized thus transmitting large volumes of gas into the tubing.

Dynamic simulation can help identify the reason(s) for unstable flow and estimate where and when slugging is originating. Furthermore, dynamic simulation can establish the size and frequency of the slugging severity.

- How to recognize the situations where instability may arise.

Well production trends, and surface tubing and casing pressure and temperature measurements, may indicate the probable onset of instability. Gradual decline in produced fluid with increased annulus pressure may indicate liquid loading. See Fig. IV-1.

Fig. IV-1: Well Production Trend – Rate (Green), Pressure (Red), Temperature (Blue)

If tubing pressure starts fluctuating and there is a gradual increase in the pressure band, this may be an indication of gas separation and liquid fall back in the tubing. Reduced total gas liquid ratio may indicate that the well needs gas-lift assistance to maintain stable flow.

- Determine how to stabilize unstable wells.

To stabilize a well, it is important to identify the root cause for the instability (e.g. annular heading).

Use accurate field data to build the dynamic well model and analyse the causes for instability. There may be one or multiple causes that make the well unstable and it is important to address all the probable causes and rectify them to make the well perform efficiently. The dynamic simulator can be used to analyze the reason(s) for unstable flow and evaluate the best solution(s) to stabilize the well.


Some of the solutions that can be evaluated are:

– Reduce tubing size (during well design or workover operation)

– Increase back pressure (this will reduce maximum production rate)

– Optimize gas injection (where? how much?)

– Automate real-time gas-lift (using an online dynamic simulator)

Use dynamic simulation to determine when to use gas-lift to re-start wells. This can be due to:

- High water cut

- Low bottom-hole pressure

- Poor well inflow performance

- High back pressure in surface facilities

- Other issues.

Fig. IV-2: Well Unloading - Dynamic Simulation

Use a dynamic simulator to match the well’s current flowing conditions with the measured field data and run sensitivity analyses for a range of different water cuts, reservoir pressures, and other inflow condition changes that are expected, like change in the productivity index or skin. Properly matched well performance


characteristics will validate the model and should give a clue about the onset of instability due to changes in water cut, reservoir pressure, or other inflow parameters. See Fig. IV-2. If the well-reservoir interaction is strong, it may be necessary to couple the well model with a reservoir model to properly predict the decline rate and water break through with time.

Use dynamic simulation to define the kick-off water cut limit (the water cut above which unloading is needed) to plan a safe well shut-in. If the water cut is below the limit, the well can be put back online without gas-lift. If the water cut is above the kick-off limit, the optimum gas-lift scenario can be planned in advance.

Use dynamic simulation to determine when to start gas-lift in a flowing well.A dynamic simulator may be used to analyse natural flowing wells for optimization opportunities and to help determine when to start gas-lift. The purpose of gas-lift is to achieve reduced flowing bottom-hole pressure so the reservoir can deliver the desired production rates. A dynamic model can predict the optimum injection point and the required amount of lift gas for optimum well performance, and to start gas-lift. See Fig. IV-3.

Fig. IV-3: Well Dynamic Simulation Output Comparison


Use dynamic simulation to determine the need to start gas-lift due to liquid loading in gas wells.

A major issue with gas well production is liquid loading, usually with water but sometimes with condensate or a combination of water and condensate. Depending on the reservoir inflow characteristics, the well may experience loading issues sooner or later in the well’s life cycle, either due to reservoir pressure depletion, decreased gas rate, or increased liquid production. In Fig. IV-4, it is assumed that the end of tubing (EOT) does not extend to the mid-perforations so that there is a section of casing from the EOT through the perforations.

Fig. IV-4: Life history of a gas well.

Initially the well may produce at a high rate so the flow regime is mist flow in the tubing. However it may be in bubble, transition, or slug flow below the EOT. As time increases and production declines, the flow regimes from the perforations to the surface will change as the gas production declines. Flow at the surface may remain in mist flow until the conditions change sufficiently so the flow exhibits transition flow. At this point the well production becomes erratic, progressing to slug flow as the gas rate continues to decline. This transition will often be accompanied by a marked increase in the decline rate. Eventually, the unstable slug flow at the surface will transition to a stable, fairly steady, lower production rate. This event occurs when the gas rate is too low to carry liquids to the surface and simply bubbles through a stagnant liquid column. If corrective action is not taken, the well will continue to decline and will eventually die.


Dynamic simulation can be used to predict the onset of liquid loading. Well completion design also affects liquid loading, depending on provisions made for the type of artificial lift, and available infrastructure resources such as electric power, lift gas, and wellbore accessibility.

- Dynamic simulation can predict the following for a gas well:

Onset of liquid loading

When to simulate various deliquification methods

Best deliquification method with the existing completion

Better completion options for recompletion/work-over

When to use a hydrate inhibitor.

- Method to predict when the gas well will load and die.

To plan and design for liquid loading, it is necessary to predict when it may occur. Generally the Turner, et. al. critical velocity concept and steady state techniques are used to predict the onset of liquid loading. These are reasonably accurate for near vertical wells. See Fig. IV-5.

Fig. IV-5: Liquid Transport in Vertical Wells

Liquid is lifted by the gas flow as individual particles, and as a liquid film along the tubing wall by the shear stress at the interface between the gas and the liquid. Turner, et. al. developed a simple correlation to predict the critical velocity in near vertical gas wells assuming the droplet model.

The critical velocity is defined as the minimum gas velocity in the production tubing required to move droplets upward. Two variations of the correlation were developed; one for the transport of water and one for condensate. Although


critical velocity is the controlling factor, these correlations are easily converted into a more useful form for computing a critical flow rate and a critical tubing diameter. See Fig. IV-6.

Fig. IV-6: Minimum Gas Rate for Unloading the Well

These correlations can be used to compute the critical gas flow rate required to transport either water or condensate. See Fig. IV-7. When both liquid phases are present, the water correlation is recommended.


Fig. IV-7: Completions Effects on Critical Velocity

Fig. IV-8 shows the typical steady state stability analysis using the tubing performance and IPR reservoir deliverability curves.

Fig. IV-8: Tubing performance curve in relation to well deliverability curve.


Dynamic Simulation provides an understanding of multiphase flow and the role of parameters such as pressure-temperature gradients, deviation, and tubing size, as well as the effect of inflow performance on liquid loading32-33. Transient multiphase flow modelling offers new insights into the mechanisms of liquid loading. The onset of liquid loading is triggered by film flow reversal rather than droplet flow reversal, when the droplet drag force no longer exceeds the droplet gravity force. Dynamic simulation matches actual liquid loading better than the Turner model in that it provides a more realistic description of liquid loading. Dynamic simulation is used to obtain realistic values of reservoir abandonment pressure based on actual surface data measurements.

To predict when the gas well will load and die, it is required to accurately model and history match the well with current field data. Run the dynamic model with time series for expected reservoir pressure decline, gas/liquid fraction changes, and surface boundary condition changes.

- Deal with liquid loading in gas wells.

Based on the dynamic simulator’s prediction of onset of liquid loading and the amount of liquid production, select the optimum tubing internal diameter and/or apply artificial lift using either plunger lift, chemical, gas-lift, or pumps. Run simulations to select and optimize the proper deliquification method that is suitable for the gas well based on economics and available resources. Based on the uplift predictions and work-over/recompletion costs, decide on the most suitable deliquification method and apply to the existing completion or add to the new recompletion design.

Use dynamic simulation to aid in optimizing intelligent and complex well completions.

Intelligent well completion technology was developed as part of the global industry trend toward improving reservoir productivity. This technology enables multiple reservoirs to be intersected by a single well and controlled remotely. The ability to manage reservoirs remotely also reduces potential well intervention costs. Although most intelligent well completions have been installed in offshore wells, service providers have begun installing them on land as well. An intelligent well is equipped with sensors/monitoring equipment and completion components that can be remotely adjusted to optimize production. This optimization typically involves flow control that takes place down hole via remote control from the surface, without physical intervention.


While there are exceptions, the key components of a typical intelligent completion are:

1. Flow control devices, which are usually hydraulically-operated control valves used to control flows into and out of the reservoir.

2. Feed-through isolation packers that enable hydraulic control lines to be fed through to subsurface control valves.

3. Down-hole sensors which report pressure, temperature, and flow rates back to the surface.

4. Control systems comprising hydraulic and/or electrical surface systems used to monitor and control subsurface conditions.

Production from multiple zones historically required complicated completions with multiple packers and multiple tubing strings, assuming the wellbore could accommodate two or three tubing strings. If this was not feasible or cost-effective, a sequencing of production was implemented, starting with the bottommost (highest-pressure) zone, and then moving to the upper reservoirs as the lower ones depleted, to avoid cross-flow. Intelligent well completions enable the operator to alternately produce the lower and upper reservoirs, accelerating total production and increasing the net present value of the well.

Furthermore, reduced well intervention costs can make a significant difference, given the expense of rig time, especially in deepwater and subsea wells, and deferred production caused by schedule delays. The ability to reconfigure wells remotely reduces the need for physical intervention.

To deal with intelligent well completions, the dynamic simulator needs to model down-hole equipment such as inflow control devices, safety shut-down systems, and hydraulic control valves/devices. See Fig. IV-9. Dynamic models are capable of using simple control valves to represent and simulate the same effect of those devices when the particular flow coefficients (Cv) of the devices are known.


Fig. IV-9: Remote Well Control Device

Dynamic simulation can help optimize the design of intelligent wells. Several well completion dynamic model options can be run and results compared. Costly intelligent control devices can be justified by validating with the dynamic model the expected improvements that can be provided with and without these devices. Optimum liner size and the minimum number of control devices can be optimized by analyzing the multiphase flow along the productive interval, including liner-formation annular effects. This is necessary in extended reach, maximum reservoir contact wells and multi-laterals. The dynamic simulator allows as many inflow points as required (each of them with a different inflow performance relationship or productivity index, permeability, skin, gas/oil ratio, and water cut, if necessary) to describe the flow characteristics along the multi-entry productive intervals, including water and/or gas conning effects.

The application of dynamic simulation is also relevant to optimize production operations and maximum recovery from these complex intelligent wells during the field life cycle. Although normally the ultimate strategic cognitive activity or intelligence has been provided by the field operator based on expert visualization and interpretation of the processed data.

A great deal of the logical workflow associated with the data acquisition, processing, and resultant action normally provided by the operator are the consequence of the automated control responses provided for the controller and actuators following a predefined optimization or functional algorithm. This makes the operator’s work simpler.

This is especially true if the automated responses are coupled to real-time, online dynamic simulation. “What-if” and “look-ahead” dynamic multiphase flow


simulations from the fluids flowing into the well, including the lift gas, can be performed using actual data provided by the SCADA system connected to the dynamic simulator. Dynamic coupling with a near wellbore reservoir simulator to quantify the flow provided from each production interval may be necessary when the well reservoir interaction is significantly high.

The predictive “look-ahead” simulation will provide the operator with the predictions regarding future states of production to make operational decisions and take actions supported by the “what–if” simulations to analyze the consequence of actions or decisions to improve the production performance of the wells.

Intelligent wells/completions require real time production information and control and therefore dynamic simulation is the best type of simulation to optimize these applications

Use dynamic simulation to aid in understanding when cross flow and/or commingling occur.

Recent well completions are more complex as they produce from multiple zones in either vertical, deviated, or horizontal wells. There are possibilities for cross flow between zones during well shut-in and while the well is flowing with very little drawdown or the flowing bottom-hole pressure is significantly higher than the pressure of one of the upper producing zones. Dynamic simulation can be used to understand transient flow conditions and cross flow occurrences. It is important to model the well trajectory. Create enough pipe segments to estimate and optimize commingled production from each zone of interest. Also model each zone as a separate source/well, with its particular inflow reservoir and fluid properties, so fluid production, cross flow, and fluid movement from each zone can be evaluated for different flowing bottom-hole pressure and reservoir depletion scenarios.

Dynamic simulation can be used to justify commingling different production zones or increasing the cost of the well completion to produce them separately for proper reservoir management.

Intelligent well completions enable multiple reservoirs to be accessed with a single well while avoiding the common problem of cross-flow caused by different reservoir pressures. In addition, intelligent completions of injection wells enable greater control of injection and improve the recovery of hydrocarbons from offset production wells.


In multi-lateral wells, there are situations where one lateral may not contribute when the flowing bottom-hole pressure (Pwf) is higher than the layer pressure of that lateral near the wellbore.

Figure IV-9 below shows possible cross flow situations during well flowing.

3860 ft

Lateral - A

Lateral - B

Zone - A Zone - B Zone - C

Pr=2690psia

Pr=2775psia Pr=3140psia Pr=2725psia

Pwf=2550psia

60 ft

Fig. IV-9: Possible Cross-flow Situations during Well Flowing

3860 ft

Lateral - A

Lateral - B

Zone - A Zone - B Zone - C

Pr=2690psia

Pr=2775psia Pr=3140psia Pr=2725psia

Psi=2710psia

60 ft

Fig. IV-10: Possible Cross-flow Situations during Well Shut-in


Generally the cross flow is aggressive soon after the well is shut-in and it will usually cease once the pressures are equalized near the well bore region.

Dynamic simulation may be used to optimized design and production from multi-layer and multi-lateral well completions.

Use dynamic simulation to optimize gas-lift well and system shut-in and start-up operations.

The application of dynamic simulation to design and operate the shut-in and start-up of pipelines and facilities is a standard procedure in flow assurance studies performed by facilities engineers. In these studies, wells are normally included as flow sources, or the well completion model is simplified. Therefore flow assurance in the wellbore upstream of the wellhead is rarely performed and the total system is not integrated. This can lead to significant errors in the flowline-riser-facilities design as well as unsafe operations and production optimization problems. The detailed well description should be included in the final dynamic simulation design and the total system should be integrated to define the interactive behavior of the system. Chapter V-D, provides more details on the appropriate ways of implementing dynamic simulation.

The particular shut-in and start-up conditions associated to the type of artificial lift system also need to be included. Chapter III-J and K provide details for using dynamic simulation to optimize well kick-off and well clean-up.

Gas-lift is a widely used artificial lift methods in oil production. However, gas-lift is an inherently unstable, dynamic process and optimized gas-lift design requires that gas-lift wells be operated on the up-slope of their tubing performance curve – Fig. IV-11a.


Fig-IV-11a: Effect of tubing performance curve on liquid production rate

qL

qinj

Fig-IV-11b: Effect of gas-lift rate (qinj) on liquid production rate

Gravity effects become the dominant factor of gas and liquid two-phase flow in the tubing and this two-phase vertical flow is often unstable. Unstable production under gas-lift is often called well heading. This unstable operation leads to periods of reduced or even no liquid production followed by large slugs of liquid and gas. Operators usually try to overcome this unstable operation by increasing the amount of lift gas beyond the optimum rate (Fig-IV-11b), but this practice may lead to a worsening stability condition.

To better understand gas-lift stability problems, a description of the gas-lift kick-of process is given below.

1. Starting with an annulus pressure down-hole that is lower than the bottom-hole tubing pressure, there is no gas flow through the down-hole gas-lift valve into the tubing. Production rate from the reservoir, if any, is low. As gas is


injected through the surface gas injection choke or control valve, the annulus pressure starts to build.

2. Given some time, the annulus pressure exceeds the bottom-hole pressure and gas is injected into the tubing through the gas-lift valve.

3. The injected gas lightens the fluid in the tubing by effectively reducing its density and back pressure and the liquid production rate from the reservoir begins to increase.

4. Gas flows from the annulus into the tubing at an increasing rate. If gas is supplied at a constant, adequate rate, liquid production can become stable.

Unstable operation

5. If insufficient gas is supplied, the annulus pressure will decrease rapidly and gas-lift valves will start to open and close intermittently. This depends on annular pressure build up cycles due to a gas injection rate that can increase the annular pressure and open the gas-lift valve against the tubing pressure.

6. With decreasing or intermittent gas flow through the gas-lift valve, the liquid density of the fluid in the tubing increases. Then production rate decreases or can even stop.

7. During these cyclic periods, the tubing pressure may exceed the annulus pressure, and gas injection into the tubing stops. Continued gas injection into the annulus eventually will build the pressure again and more gas will be injected into the tubing, generating a surge of production. These unstable production operations are frequently called heading.

To deal with this unstable operating condition generated by the gas-lift process a good approach is to use dynamic simulation with the automatic control system.

This method of setting an automated control system relies on dynamic, transient gas-lifted well models by maximizing the lift gas efficiency and capturing the well and process knowledge developed in the dynamic model48-49.

The concept is to analyze and design stabilizing controllers. If applicable, estimators can be based on a dynamic model of the system. For this purpose a simplified dynamic non-linear model based on physical principles of gas-lifted wells, that is suitable for controller and estimator design, can be developed.

The main purpose with this dynamic model is to describe the interactions between the annular space and tubing which leads to the unstable behavior at low and intermediate gas injection rates. It is necessary that the model becomes stable at high gas injection rates. The idea is to use a simple model basically relying on three differential equations conserving mass in the tubing and casing, and algebraic equations of state for approximating energy and impulse balances. At the cost of a more complicated, yet accurate, model, differential equations


describing energy balances and impulse balances may also be included. To summarize, the nonlinear dynamic gas-lifted well model consists of:

Model of the pipes (casing and tubing):

1. Three ordinary differential equations conserving the mass in casing and tubing.

2. Algebraic equations of state relating pressure, temperature, and liquid and gas holdup to each other in casing and tubing.

3. Algebraic equations for pressure heads.

Model the gas injection choke: An algebraic equation describing the relation between the pressure upstream and downstream of the gas injection choke and the mass flow rate through the choke.

Model the gas injection valve: An algebraic equation describing the relation between the pressure upstream and downstream of the gas injection valve and the mass flow rate through the valve. The equation will vary depending on the type of valve used.

Model the production choke: An algebraic equation describing the relation between the pressure upstream and downstream of the production choke and the mass flow rate of gas and liquid through the choke.

The advantages with this simple dynamic model structure are many. Compactness is one appealing feature since a set of ordinary differential equations and algebraic equations are used. Secondly, it is able to capture the main dynamic behavior of gas-lifted well both at low, medium (unstable operating conditions) and high (stable operating conditions) gas injection rates. Chapter VI-B provides more details on real-time dynamic simulation.

Another option to deal with these unstable operating conditions generated by shut-in, start-up, and the gas-lift process itself is by direct application of a real-time, online dynamic simulator. Chapter IV-D provides details on this type of application.


6. Information Required for Dynamic Simulation

This chapter describes the information required to use dynamic simulation for gas-lift wells and systems. Similar to other transient multiphase flow hydraulic analyses, studying gas-lifted systems requires input in the following categories:

a. Fluid properties (PVT characteristics).

b. Flow path geometry and equipment.

c. Inflow performance relationship (IPR).

d. Boundary Conditions.

The main difference between steady state and transient simulation is the latter also provides changes in the hydraulic status of a well from the specified initial conditions. The input for a transient hydraulic analysis should include the initial pressures, temperatures, and rates in the system. Any operational event that creates a change in the system needs to be specified along with its associated time.

Another difference between steady state analysis and transient simulation is dynamic simulation requires the mathematical input necessary to solve differential equations. This includes: one dimensional grid section length, and integration and time step data. Integration data includes start and end times for the integration, maximum and minimum integration time steps, and CPU limit information. Defaults normally are provided and suggested by the dynamic simulator and can be modified to speed the simulation time and/or make the run more mathematically stable. One dimensional grid section length will define the number of differential sections in the system and therefore the time required for the simulation run. The longer the section length, the shorter the simulation time, but the results are less accurate. For example, liquid hold-up calculation accuracy is reduced when using relatively large section lengths. The shorter the section length the longer the simulation time, but the higher the accuracy. A compromise needs to be reached between section length and accuracy.

The rest of this chapter explains the main inputs.

Fluid propertiesA successful design and operation of a gas-lift well, requires predicting flowing fluid characteristics. Most of the transient multi-phase flow simulators give users an option to choose the amount of detail in defining the fluid properties. The possibilities are:


Black oil correlations

PVT tables

Fully compositional modeling.

Using a black oil correlation is a simplistic approach for describing phase behavior of hydrocarbon mixtures. The word simplistic should not be mistaken as inaccurate. In-situ fluid properties are calculated by using user specified oil density (API gravity), gas specific gravity (density), and GOR at standard conditions. Most of the software packages also provide a module to tune the selected black oil correlation to better match the fluid properties. A correlation should not be adjusted or tuned more than 10% as this will reduce the predicting accuracy of the correlation, and an unsuccessful adjustment is worse than no tuning. Most of the black oil correlations are based on the properties of hydrocarbon mixtures from one specific region, and they are only valid in a certain range of pressures and temperatures. It is important to know the applicability of a black oil correlation in its pressure and temperature range and hydrocarbon types.

Using a PVT table is another way of specifying fluid properties for transient hydraulic analysis of gas-lift systems. The transient multi-phase flow simulator does no fluid property calculations, but it picks the in-situ fluid properties such as phase fractions and densities from a previously constructed PVT table. To create a PVT table, a fluid model is prepared in a PVT package. This model includes the hydrocarbon composition and its measured properties at different pressures and temperatures. The measured properties are used to tune the composition so the selected equation of state will reflect the flowing fluid characteristics.

A PVT report normally contains different laboratory data sets. These are:

The saturation point,

The separator tests,

Constant composition expansion (CCE),

Constant volume depletion (CVD), and

Viscosity measurements.

The first three sets best describe what the fluid goes through in a gas-lift production system. These sets should be used to tune the fluid properties, and then apply viscosity tuning before creating the PVT tables.

The CVD data is related to reservoir engineering applications, and is not applicable for short term performance analysis of a production system. The question of “is it


harmful to involve the CVD data” may rise here. It is impossible to obtain tuning which 100% matches all the different fluid data sets. While trying to get close to one type of measurement, the accuracy of the model in another type of measurement will be sacrificed. The aim of the analysis should determine the data to be used in tuning the fluid model. After these preparations, a PVT table with sufficiently large pressure and temperature ranges should be generated for use in the transient hydraulic analysis of the gas-lift well, riser, and pipeline. The same PVT table can be used for the lift gas, as the produced gas is normally recycled in the gas-lift systems.

Fully compositional modeling is not normally preferred because it is computationally demanding (the hydrocarbon composition is flashed at every in-situ P-T), but it is recommended to achieve accuracy.

There are several occasions that require this capability. One example where fully compositional PVT modeling is required is in a multi-layer well completion with commingled production of significantly different reservoir fluids. In this situation the produced fluid composition will differ from one flowing bottom-hole pressure to another. Hydrocarbon compositions for different reservoirs need to be known and tuned with the appropriate data sets as explained above. Furthermore, the dynamic simulator should be able to track the different fluid compositions in the system, and the resulting fluid mixes along the producing path. Another relevant example is when the gas used in the gas-lift system has different composition than the produced gas. In order to properly evaluate stability in the flow path where there is a mix of the two gases, the different gas compositions needs to be known and the resulting mix calculated.

As a rule of thumb, if phase changes are expected in the system (i.e gas/condensate wells from reservoir to wellhead), a fully compositional model will give more accurate P-T and liquid hold-up calculations than a black-oil correlation.


Well Profile and Well SchematicCalculating pressure drop, whether the well is operating in steady or transient state, requires estimation of pressure losses due to friction, gravity, and acceleration. The distance traveled by the fluid along the wellbore and in the vertical direction determines the friction and the gravity components, respectively. The resulting multiphase flow regime is affected by well deviation. Therefore, an accurate representation of well trajectory is the first step in constructing a transient model for a gas-lift well. It is also important to represent the exact profile of horizontal and deviated wells, because these profiles (ups and downs) can generate terrain induced slugging. Some software packages accept only horizontal and true vertical depth couples for specifying the well trajectory. Others work with depth versus deviation data. Some software packages limit the number of points to describe the well profile which can lead to errors in slugging predictions.

Specifying the geometry where the flow takes place is the next step in constructing a transient flow model. Diameters with associated depth intervals from the completion diagram are needed in the model. This is important because the velocities, Reynolds numbers, and consequently the friction in the system are directly affected by these diameters. In cases where the flow is multiphase, such as in gas-lift, it even affects the hydrostatic pressure drop because the liquid holdup is determined from the velocities of the flowing phases.

Any well equipment, such as valves and chokes, must be entered together with their pressure drop characteristics, openings, and depths. For example, to model unloading, all unloading valves need to be specified together with their valve pressure drop characteristics and opening and closing pressures. Some software packages which were originally designed for gas-lift design and analysis, may already have a valve database to capture this information.

To obtain accurate P-T calculations along the well profiles and at the wellhead, the well completion diagram including all casings and annular fluids, cement and formation thickness, and heat transfer coefficients for each constitutive material, must be entered in detail. This data is used to estimate the radial heat losses in the wellbore which is a function of the number of concentric walls. The use of “overall heat transfer coefficients” to estimate these heat losses is a simpler option (standard practice in steady state calculations) which is not recommended in transient simulations because it does not take into account thermal mass and heat storage effects in the different materials. In risers, a detailed temperature profile from sea surface to mud line, including variations in water current velocities, is recommended when there is potential for hydrates or production chemistry problems. This information is used as a boundary condition and may influence riser temperature profiles and flow head temperature calculations at the platform or mobile offshore drilling unit (MODU).


Inflow performance relationshipThe IPR defines how much reservoir fluid can be produced at different flowing bottom-hole pressures and temperatures. It quantifies the flow resistance in the formation and in the well/reservoir interface. The IPR or PI is a steady state definition. However, studying any transient phenomena needs to be coupled with a well’s inflow performance because the production will vary depending on the changes in flowing bottom-hole pressure.

For an existing well, the IPR can be obtained from multi-rate well test data. The curve, which connects measured flowing bottom-hole pressures at different rates, is the IPR. If the well is not on production yet, analytical methods may be used for predicting the IPR by taking the formation permeability and its thickness, expected drainage area, well radius, well/reservoir interface, and the PVT of the reservoir fluids into account.

The IPR has to be entered in the transient simulator in a required format, which can either be a table, the linear PI type, a Forchheimer model, or a Vogel model. Depending on the purpose of the analysis, e.g. for studying the initial startup of a gas-lift well and its clean-up performance, it is better to use the distributed IPR approach. This requires dividing the productive interval into segments and calculating individual IPRs depending on the segment characteristics, as in permeability. These inflow sources can be input to the transient simulator at their corresponding depths to accurately visualize the inflow distribution and completion fluid clean-up performance. The number of the inflow sources depends on the required level of accuracy. A similar approach can be used in commingled gas-lift producers. If the well is producing from several different reservoirs, every inflow zone can be modeled with a separate IPR for a more detailed analysis. Changes in the reservoirs’ pressures and temperatures due to depth differences also need to be reflected, as well as changes in GLR and water cut.

As explained in Chapter II-B, some dynamic simulators offer two IPR options, the standard IPR definition for steady state conditions or the quasi-dynamic IPR definition where the key reservoir properties can change with time. When the dynamic model is used for forecasting purposes, i.e. “what if” scenarios, the use of the standard IPR definition is sufficient since it can give a reliable indication of worst case scenarios. When the dynamic model is used for matching measurements, the use of the quasi-dynamic IPR is required, and the selected variables such as skin, non-Darcy skin, and permeability can be input as time-series so the impact of the transient behavior can be reflected.

Boundary ConditionsFor every inflow source, the reservoir pressure and temperature have to be specified. The wellhead back pressure and temperature, assuming the model stops in the wellhead, are also required for the calculations. If the transient model has a wellhead bean or choke, the wellhead P-T need to be specified downstream of the


wellhead choke. The surface injection P-T together with the amount of injected gas needs to be input, if the injection model starts at the wellhead. Apart from these boundary pressures and temperatures, the transient simulators require the well’s initial fluid content and the associated pressures and temperatures including the soil temperature gradient, surface-subsea temperature gradient, and ambient temperature. These are used as the start up conditions for the calculations at time zero.

Any planned changes in the wellhead and surface injection pressures, or in lift gas injection rate, have to be entered as time series so that their impact on the transient behavior can be determined.


7. Application of Dynamic Simulation

This chapter describes when and how dynamic simulation modelling may be applied.

Integrated modellingWhen is it sufficient to only model the wellbore?Gas-lift is usually a multi-well system and for optimum system design and operation, the total system needs to be modelled.

It is sufficient to model the wellbore of a single well with a short surface pipeline when the well is at early stages in the design of the gas-lift system and/or when the initial troubleshooting efforts are focused on a particular well.

When focusing on one well, the model can be as simple or as complex as required. The annulus can be included in the model as a flow path and the counter-current heat transfer effect of injecting a relatively cold lift gas in the annulus and producing a hot reservoir fluid in the tubing can be evaluated. In the case of wells where the annulus cannot be vented and fluids are trapped in the annular space, the increase in annular pressure and temperature when opening the well to production can be modelled and the maximum annular P-T calculated based on the expected production rates. This allows proper design of the casing, tubing, and wellhead to withhold the generated stresses.

Basically, the study objectives will define the limits of the model. Section D in this Chapter explains in detail the appropriate process to select the parts of the gas-lift system to be incorporated in the model according to the study objectives.

Sooner or later the use of an integrated dynamic simulation model is recommended. This will account for any well-flowline-riser interaction effects.

When must an integrated model of reservoir, near wellbore reservoir area, inflow, outflow, flowline, and surface systems be used?When using an artificial lift system like gas-lift, the production system has a restricting flow condition that may prevent it from producing more fluids to the production facility.

These flow restrictions may be located or generated at any point between the near well bore reservoir area, the well, the pipeline(s), and the process equipment. An integrated dynamic simulation model is necessary to fully understand the system production behavior and to maximize production.

Among those restricting conditions, the mechanisms that will increase the back pressures in the system, such as slugging, increasing water cuts, lower temperatures, increased viscosities in heavy oils, and solids depositions should be considered.

If any of the above flow restrictions are affecting the components in the production system, e.g. flow branches, wells, and process equipment, these will affect the


other components of the system. It is necessary to understand these effects to find or devise a solution that will allow the system to be operated in a safe, stable manner, and to maximize production.

Furthermore, if there is a strong reservoir-wellbore interaction, the dynamic simulator may need to be integrated to a dynamic near-wellbore reservoir simulator model. However, the use of a quasi-dynamic IPR may avoid or postpone this need. When formation damage, multiple and/or commingling reservoir production zones, or other reservoir flow restrictions exist; the following cases may have strong well and near-wellbore interactions:

– Well kick-off and cleanup

– Well testing

– Shut-in/start-up

– Dynamic water and gas coning

– Liquid loading

– Bull heading and injection

– Cross flow

– Formation heading and wellbore slugging

Often, after a few months or years of production, the diminishing driving force of the reservoir to produce the hydrocarbon fluids to the surface demands the use of some sort of artificial lift. Then the original design of the production system may be oversized for the now reduced production rates and increased water cuts. The development of some form of liquid slugging on the surface pipelines may have an amplified effect in the well or wells and in the reservoir. These system interactions between different components in the production system may not be fully understood unless a dynamic integrated simulation model is used.

Section D in this Chapter explains in detail the appropriate process to select the parts of the gas-lift system to be incorporated in the model according to the study objectives.

Real-time modellingReal-time modeling requires simulation of responses at a frequency consistent with the frequency with which the responses occur in the physical system that. Animation of well response requires real-time modeling. Some transient responses may be rapid and require simulation at higher frequencies to capture the effect. Rigorous simulation methods may be slower than real-time, so real-time modeling may be less precise.

For a gas-lift well, one might close the production choke while a SCADA system collects surface measurements such as production rate and pressure, and injection rate and pressure over time. A dynamic simulator could predict these measurements at a given time.


Online dynamic simulation tools offer the possibility of running “what-if” simulation scenarios using current P-T and rate data gathered by the SCADA system and automatically input to the dynamic simulator. The surface P-T and rates, as well as the downhole reservoir P-T conditions, may have changed since the last shut-in dynamic simulation analysis was performed. Online real-time modeling allows the model to be re-run using updated field information to evaluate if, for example, the potential for hydrate conditions have changed when planning a well shut-in. Guideline procedures for well shut-in may be revised for safer operations.

The online dynamic simulator can also be used as an advisor and a data source by creating virtual instruments in the system to validate actual instrumentation, to replace damaged instrumentation, and to locate virtual instruments where there is no physical instrumentation.

The value of using steady state software in real-time to monitor and optimize oil and gas production has been recognized by the industry. Online real-time dynamic simulation software applications offer a wider range of coverage and protection by including the possibility of modelling most unsafe transient operations and flow assurance scenarios. And they offer the option of using the virtual model of the gas-lift system as a training simulator to generate “what-if” scenarios for personnel involved in design, operation, and system optimization.

The main advantages of online, real-time, dynamic simulation are:

• Test any operating procedure with current data before performing required operations

• Expand the operating envelope with flow assurance limits

• Enable better testing / production strategies based on most up-to-date information

– Faster clean-up on start-up / testing

– Stability / slug monitoring and tracking

– Optimize gas injection

– Optimize inhibitor injection including optimum amount of MEG/MeOH

– Minimize risk of hydrates and blockages

• Warn of potential abnormal situations

– Reduce potential for shutdowns and deferred production

• Ensure stable operation and optimized production

• Reduce unplanned shutdowns

• Improve short-term production forecasting

• Reduce uncertainty for better decision making

• Use extensive virtual instrumentation


• Empower a focal-point for multi-discipline knowledge building

Use of dynamic simulation modelling for gas-lift system managementDynamic system models may have several practical uses in gas-lift. These include:

Assisting with designing gas-lift installations

Confirming or validating that a given design will work properly

Helping to identify problems with a gas-lift system operation

Helping to diagnose the causes of gas-lift operating problems

Helping to troubleshoot or find solutions to specific problems

Helping to optimize a gas-lift system operation

- Using dynamic simulation in gas-lift design

Gas-lift design consists of two components: (1) determining the spacing of the gas-lift mandrels, and (2) determining the size and settings of the gas-lift valves and/or orifice. Normally, the mandrels are spaced when the well is first completed or worked over and/or recompleted.

Most conventional gas-lift design programs use steady-state pressure traverses for the injection and production pressure profiles. The mandrels are spaced using these profiles. The mandrels must be spaced so the well can unload to the deepest operating point, and continuously operate at this depth, without multi-pointing or working back up the well. This design process is discussed in API RP 11V6.

But for many gas-lift wells, especially wells with horizontal completion intervals, the actual pressure profiles may not be steady; they may fluctuate dynamically as the well unloads and operates.

By using dynamic simulation, mandrels can be spaced so unloading and continued operation from the deep operating valve/orifice can be assured, even if the well operates in an unstable, dynamic fashion.

When it is time to place a well on gas-lift, the gas-lift valves and orifice must be sized and set. The valves must be designed to permit the correct amount of lift gas injection for unloading, but not so much as to waste gas or prevent working down to lower unloading mandrels/valves. Steady state design of injection pressure operated (IPO) gas-lift valves is covered in API RP 11V6. Design of production pressure operated (PPO) valves is covered in API RP 19G9. Use of dynamic simulation can help assure that the valves are


selected and set properly to permit effective unloading and operation from the desired deepest point.

- Gas-lift design confirmation

Normally, the mandrels are installed when a well is first completed or recompleted. Normally, this was done using a conventional design program with steady-state pressure profiles.

In this case, it isn’t possible to use dynamic simulation to space the mandrels, but the design can be checked with a dynamic simulator to confirm or validate that it will work properly for unloading and operation from bottom. If the simulator indicates that the design will not work as desired, then adjustments can be made in the design pressure, injection rate, or selection of different types of gas-lift valves.

It is preferable to know in advance if a design is going to work properly, rather than install an incorrect design and find out later that it didn’t unload or operate as desired.

It is not normally recommended to do this, due to the potential for leaks and other problems, but if the dynamic simulator indicates that the well can not work down due to improper mandrel spacing, it may be possible to insert and additional unloading valve using a wireline-set pack-off valve.

- Problem identification and diagnosis

Many gas-lift wells operate in an unstable manner at some time(s) in their life cycle. This may be due to a change in the injection pressure or rate, the fluid being produced, the inflow performance from the reservoir to the wellbore, or a leak in the tubing, mandrels, or valves.

Typical problems include unstable operation due to a too large port size in an operating valve or orifice, or multi pointing on two or more valves due to periodical re-opening of an upper unloading valve, leaks in the tubing, mandrels, or valves, or changes in the inflow performance of the well.

When an operating well is unstable, dynamic simulation can confirm or diagnose the cause(s) of the instability. This is done by adjusting the parameters used by the simulator until the predicted well performance, e.g. tubing and casing pressure fluctuations, or production and injection pressure profiles, match the observed or measured pressures and profiles. When a match is achieved, the cause(s) of the instability can be determined.


- Gas-lift troubleshooting

When the causes of ineffective operation have been determined, dynamic simulation can assist in troubleshooting to determine the best solutions to the problem. It may be necessary to reset one or more of the unloading valves; it may be necessary to change the port size in one or more of the valves or the orifice; or it may be necessary to change the gas-lift injection rate or pressure.

Dynamic simulation can be used, much as it is used in design confirmation, to check any proposed change in valve setting, or injection rate or pressure, to verify if the change will accomplish the desired result in gas-lift operation. If not, the proposed change(s) can be adjusted until they produce the desired results.

- Operational optimization

Gas-lift optimization is discussed in API RP 11V5 and 11V8. The objective is to determine the rate of lift gas injection that will optimize the value of oil and gas production with consideration for the cost of gas injection, water treating, and fluid handling.

In an operating gas-lift field, there is rarely the right amount of gas to optimize all of the wells; there is either too much or too little gas available.

Dynamic simulation can determine the range of gas-lift injection over which a well can be operated and still continue to lift from bottom and remain at least relatively stable. Too much gas will be wasteful and my cause upper gas-lift valves to open due to an increase in the injection pressure at depth. Too little gas may not provide enough lifting so the well can continue to operate from the desired depth. This may lead to an unstable, multi-pointing operation.

As gas availability changes in a field, due to changes in compression capacity or demand from wells in the field, the field control system must adjust the injection rates so the total injection from the system is equal to the total supply into the system. Otherwise, the pressure in the distribution system will go too high or too low. Dynamic simulation can provide the range of injection rates that can safely be used in each well. If the overall rate is too high, some gas should be sold or re-cycled to avoid over injection. If the overall rate is too low, it may be necessary to temporarily shut in some of the wells to avoid under-injecting all of them.


- Special considerations

The above discussion focuses on gas-lift wells with mandrels, unloading valves, and an operating valve or orifice. There are at least two other forms of gas-lift which are coming into common use: injection through a single point, and riser gas-lift.

Injection through a single point is possible when the injection pressure is high enough to inject deep in the well without the need for unloading valves. This can be stable if there is good correspondence between the injection rate at the surface and the ability of the downhole injection valve or orifice to transmit gas from the annulus to the tubing. However, if there is not a good match, these wells can be unstable and need dynamic simulation to assist with analysis and correction of the problem. Due to the flexibility that is lost when there is only one injection point, dynamic simulation is required for design and optimum operation of single point gas-lift systems. Chapter II-E provides more information on these systems.

Riser gas-lift is sometimes used when long risers are required to bring production from the sea floor to the surface. In some cases, the height of lift in the riser can be as great as or even greater than the height of lift in the wellbore. Gas-lift is needed to overcome the significant pressure drops between the sea floor and the surface. There are often problems with instability in the riser and dynamic simulation can assist with analysis and correction of the problem. Chapter III-G provides more information on riser gas-lift.

Appropriate dynamic simulation techniques and their implementation- What are the different simulation techniques?

Due to its historical development and the type of operational conditions, the analysis of multiphase flow phenomena can be divided into two techniques:

• Steady state techniques

• Dynamic simulation or transient techniques

A detailed comparison of these techniques, highlighting pros and cons as well as areas of application, is presented in Chapter 2-C.

Optimal design and operation of multiphase injection and production systems rely on understanding multiphase flow behavior. To ensure technical, operational, and HSE integrity during the field life cycle, dynamic simulation is required.


- What techniques are appropriate for any given situation?

Dynamic simulation techniques can be used to design and/or optimize multiphase production/injection systems for any given situation including steady state and transient conditions. Steady state techniques should be used only for steady state conditions. The application of steady state and/or dynamic techniques is based on the level of complexity of the production/injection system and the fluids to be modelled.

The major advantage of steady state techniques is that the models can be constructed and sensitivities can be run quickly; therefore they are lower cost, and may require less input. They may be reasonably accurate over a well defined range of operating conditions. They are easy to use as design and optimization tools. The common error is the attempt to use these techniques to describe transient conditions.

Dynamic simulation techniques require experienced personnel and more time for building models and analysing results. Therefore, this may be a more costly technique and it may be more difficult to justify.

Both techniques are normally applied and the economic challenge is to optimize the combined use of them without compromising the quality of the design and the operational integrity of the system. Risk reduction and potential catastrophic failures are more difficult to quantify if dynamic simulation is not used.

When evaluating a number of gas-oil field development options using parametric studies to identify the steady state operating scenarios with the most limiting capacity constraints, the use of steady state techniques can be useful to provide a 1st order approximation. But dynamic techniques are required to more accurately calculate capacity requirements, and consider time dependant operating practices, e.g. the effect on system design diameters and slug catcher size, if a well is quickly opened to the desired production rate versus slowly increasing the choke size in steps during a controlled ramp-up. Furthermore, transient analysis is needed to evaluate the effect of hydrate and or wax formation and establish operational guidelines to avoid production chemistry problems during shut-in or start up operations.

Another application that efficiently combines the best of both techniques is to initially build a transient model to analyse the start-up and shut-in operations and more accurately define the steady state or unstable conditions, and maximum wellhead pressures, temperatures. and profiles. Once the steady state conditions have been confirmed and defined by transient simulation, and wellhead P-T and P-T profiles have been validated, these profiles can be used as correlations in steady state software models to make use of the quickness of the steady state technique while obtaining more reliable results.


- What part of the gas-lift well/system needs to be simulated?

Typically, reservoir, well, surface, and process facilities are optimized as individual components. The part of the total gas-lift system to be modelled depends on the objectives of the study. To understand the multiphase flow behavior of the total production/injection system, and evaluate the interaction between the tubing, gas injection annulus, flowline, and riser, the total system needs to be integrated. The advantage of integrated modelling is the ability to dynamically link these components into one interactive, full-field production system. Integrated systems can give more realistic results. There are different levels of model integration and they should be applied following an increasing order of complexity:

1st integration level that typically uses one software package:

Typically, E&P companies divide the design and optimization of the system in different areas of expertise. Production technologists look at well design and optimization, facilities engineers at pipeline-facilities design and optimization, and operation engineers at production optimization and operating costs. Therefore, it is not unusual to find a dynamic model of the well from the reservoir to wellhead that is built by production technologists and a separate flowline-riser model from the wellhead to separator that is built by facilities engineers. These models are built to analyse different design and operational issues and are optimized separately, but when the number of sensitivities have been reduced to a minimum in both models, they need to be connected to analyse the interaction between the system components. To do this, it is necessary to use the same fluid table in both models constructed using with the P-T extremes of the entire system, i.e. reservoir P-T and separator P-T.

In the case of gas-lift wells and systems, it is recommended to start the modelling from the simpler case of the well only and upgrade the model to include the well + flowline + riser based on the results. The order of complexity of the gas-lift injection system is as follows:

1. Model gas-lift injection gas as a source considering its composition, P-T, and rate at the desired injection point. In this type of model, sensitivities can be run for different gas rates and different injection points to obtain the optimum rate and position.

2. Model lift gas injection as a source at the wellhead and include the annulus in the model. This will account for the cross heat transfer


effects of injecting a cold gas downhole in the annulus and producing a hot fluid inside the tubing. This type of model will improve the calculation of the temperature profile and the temperature at each unloading valve location. It will also take into account other annular flow effects such as condensation of liquids from the gas composition since some liquids may be injected with the gas at the desired depth. This type of model will also consider the interaction between the production and the gas injection system components.

3. Model gas-lift injection gas as a source at the compressor output, including the well annulus and the gas injection flowline from the compressors to the annular wellhead. This type of model will take into account the behavior of the lift gas in the injection line. The compressor can also be included in the model.

2nd integration level which typically uses two software packages:

When the interaction between the near wellbore reservoir and the well plays a dominant role in the description of the dynamic behavior of the complete system, to properly model the multiphase flow behaviour, the well + flowline + riser model may need to be integrated to the near-wellbore reservoir model. Some of the cases where the dynamic wellbore/reservoir interactions may be strong are:

– Liquid loading

– Dynamic water and gas coning

– Formation heading and wellbore slugging

– Bull heading and injection cases

– Cross flow cases

– Well kick-off and cleanup cases

– Well testing cases

– Shut-in/start-up cases

As explained in Chapter 2-B, a quasi-dynamic IPR option where the user can specify pressure, temperature, water cut, k-h, skin and non-Darcy skin as time series, can be used when matching interactive dynamic measurements. A near-wellbore reservoir model can more accurately model the reservoir-well interaction than the quasi-dynamic IPR.

Nevertheless, the benefits of the quasi-dynamic reservoir input are:


– No software connectivity requirements since all is performed in one software package

– Faster runs

– Value ranges of key variables will be defined faster

– There will need to be fewer sensitivity runs

– The analyst will be in a better position to:

• define the value of using a near-wellbore model

• define key variables and the value range

Depending on the objectives of the study, some models will be more appropriate than others.

3rd integration level where multiple software packages are used:

Multi-phase flow transient models can be integrated with geo-science software, and risk simulation and decision analysis software packages, to obtain a technical-operative information management system and improve field development decisions. See Fig. VI-1 and VI-2.

Uncertainties across interfaces between surface-subsurface, well location, producing scenarios, fluid-rock dynamic properties, and probabilistic analysis, can be introduced and NPV and recovery estimates can be obtained. Integrated multiphase-flow/geo-science/risk/decision-analysis modelling has the potential to:

– Optimize field productivity through the production life cycle

– Improve reserves recovery

– Enhance surveillance

– Enhance troubleshooting

– Improve decision making

– Improve risk management

– Improve work processes


Fig. VI-1: Integrated Technical Operating Information Management System

PRODUCTION CONTROL

MANAGEMENT CENTER ON-LINE

MONITORING AND

PREDICTION OF

CORROSION

ON-LINE OPERATION

& MAINTENANCE OPTIMIZATION

ADVANCED PROCESS CONTROL

SAFETY STUDY

SIMULATOR

WELL AND ARTIFICIAL

LIFT SYSTEMS DESIGN

PROCESS DESIGN

OFF-LINE OPERATOR TRAINING

SIMULATOR

DECISION MAKING

DIAGNOSIS- PROGNOSIS

PVT-FLUID TRANPORT

AND PROCESS

PROPERTIES

Fig VI-2: Integrated Simulators Under a Unified Software Environment


The major drawback of integrated systems is the convergence problems experienced during simulation runs due to different software packages and explicit connective software.


8. Information Provided by Dynamic Simulation

This chapter describes the information that can be provided by dynamic simulation of gas-lift wells and systems.

Slugging flow:Slug flow can be described as a multi-phase flow pattern in which slugs of liquid are separated from each other by large bubbles of gas. See Fig. VII-1.

Fig. VII-1: Slug Flow

A liquid film with a varying thickness is present around the gas bubbles. Some gas can be entrained in the liquid slug body in the form of much smaller bubbles. The gas and liquid flow rates, with the corresponding pressures and temperatures, and some other factors, can result in slugging in an oil well with or without gas-lift. How flow patterns develop in a nearly vertical oil well with changes in pressures and temperatures is shown in Fig. VII-2.


Figure VII-2: Changes in flow patterns in a vertical well with respect to pressures and temperatures.

Point A in Fig. VII-2 is at the bottom of the hole where the pressures are higher than the bubble point of the fluid at in-situ temperature. There is a reduction in pressure up to point B because of the frictional and hydrostatic losses. This is where the fluid is at the bubble point pressure at the local flowing temperature. Any further reduction in pressure results in gas liberation leading to the bubble flow regime. Reduction in pressures continues as the fluid approaches point C. This increases gas liberation and velocities. The bubble volumes become larger with an increased tendency to coalesce. The flow pattern changes and becomes hydrodynamic slug flow. Large gas bubbles are separated from each other by liquid slugs.

Hydrodynamic slugging is generated by slip between the liquid and gas phases.

To determine if slug flow will occur in a pipe segment, the flow pattern map for a specific deviation needs to be inspected. This approach is not accurate because flow regime transitions cannot be reduced to two defining parameters, but it is a good example for explaining hydrodynamic slugging.

Fig. VII-3 is an example flow pattern map for vertical upward flow. This map is not based on realistic calculations. It is an example to show what a flow pattern map looks like.

A

B

C

PressureTemperature

Dep

th

Pressure

Temperature

D


Fig. VII-3: Flow pattern map for vertical upward flow.

Hydrodynamic slugging does not represent a major instability if the well is producing at sufficiently high rates where the system is dominated by friction. See Fig. VII-4 for cases where the production rates are low, flow is unstable with excessive liquid fall back, and major slugging occurs. This may create operational problems. In an extreme case, the well will cease to flow. Such slugging can also be observed in over-sized risers.

Fig. VII-4: Well production rate indicated by the black dot is in the gravity-dominated area, which is on the left-hand side of the minimum of the intake pressure curve (IPC).

Producing wells in an unstable regime of major slugging are difficult to operate and reduce equipment life. This regime represents a state of instability for the phase fractions at the well outlet and pressures across the system. The retained liquid, which falls back, increases the hydrostatic pressure in the well and results in a

Gross liquid rate

Flow

ing

botto

m h

ole

pres

sure

IPR

IPC, no gas-lift

IPC, with gas-lift

Bubble flow

Slug/churn flow(Intermittent flow)

Gas Froude number

Liqu

id F

roud

e nu

mbe

r

Annu

lar fl

ow

Froth flow


reduction in production. With the increased pressures at the bottom of the hole, at some stage the well is able to push the liquid out. While discharging the slug, pressures in the well start dropping again which leads to an increase in the production from the reservoir. Depending on the size of the slug, and production from the other wells in the field, and even the separation efficiency in the separator train, may be adversely affected due to the temporary excessive liquid rate. Gas-lifting is one of the preferred ways to avoid slugging in wells and risers if further beaning up to increase the choke size is not an option. The aim is to change the flow pattern from intermittent to annular mist, which ensures stable pressures, flow rates, and phase fractions at the discharge point.

The curve of “IPC, with gas-lift” in Fig. VII-4 illustrates the effect of gas-lift on the slugging behavior. The point of instability, which is at the minimum of the intake pressure curve, is shifted towards smaller rates. This offers a longer service life for the well. Fig. VII-4 can be generated by using any steady state well performance or multiphase flow simulator. A Dynamic Simulator is required to predict the system’s behavior and pressure drop after the slugging starts. Transient analysis is required to estimate “what happens next” once the intersection of the IPR and the IPC curves occurs in the instable area. This analysis will provide valuable information about how serious the slugging will be, and whether or not gas-lift will be required to overcome the instability.

Hydrodynamic slugging conditions are more rigorously predicted by dynamic

simulation. These mathematical models are based on physical mechanisms which

determine the transition between the different flow regimes. In the dynamic simulator, P-T and liquid hold-up are interrelated. Phase transfer is a function of P and T. The simulator interface mass transfer model takes into account condensation, evaporation, and retrograde condensation.

Well trajectory can induce another form of slugging behavior in wells. These are called terrain slugs and steady state tools do not predict this behavior. In an undulating trajectory, the heavy liquid phase, e.g. water, may have a tendency accumulate in the sumps (See Fig. VII-5) under steady state flow conditions. Increasing liquid level with time in the pipeline dip creates a backpressure upstream of the accumulation resulting in a reduction in production at these sections. When the pressure at the upstream end of the liquid body is high enough, the liquid can move and enter sections which are highly inclined or vertical. The elevated flowing bottom-hole pressures at this stage will negatively affect the production until the well starts discharging the liquid slug. Terrain slugging results in pressure fluctuations, changes in production rate, and variations in the phase fractions at the well outlet. It is not desirable. Using a transient multi-phase flow simulator provides an opportunity to realize if a well with a sophisticated trajectory will act as a slug generator. Or it may be possible to tune the operational parameters to terminate the slugging behavior.

Main flow directionLiquid falling back


Fig. VII-5: A well trajectory which can trigger terrain slugs.

Horizontal and inclined wells can generate terrain induced slugging; and risers can as well. See Fig. VII-6. Risers are an integral part of offshore and subsea production systems, and well completion and workover operations. Steady state techniques do not predict terrain induced slugging. Stable conditions defined by using steady state analysis may be incorrect in this kind of production systems where the well/system may be unstable. Dynamic simulation is required to properly define slugging conditions and stable flow.

Fig. VII-6: Riser Induced Slugging

A. Slug formation

B.Slug production

C. Gas penetration

D. Gas blow-down


Dynamic simulation can define where slugging originates and what is causing it. Dynamic simulation can also establish the size and frequency of the gas bubble and associated slugging severity. See Fig. VII-1.

Tracking development of the individual slugs along the well and flowline trajectories is necessary to estimate the volume of the liquid surges that flow out of the system.

The main potential problems that may inhibit stable multiphase flow are:

• Terrain

• Inclination/elevation

• Rate changes

• Condensate–liquid content in gas

• Shut-in/start-up

• Risers

Other problems can occur in gas-lift wells:

• Unloading gas-lift valve leaks

• Incorrect mandrel spacing and unloading valve design

• Annular heading

- Downhole operating gas-lift valve and surface lift gas control valve/orifice interaction

- Annular liquid condensation

• Density wave instability26.

• Non-constant fluid composition in tubing above gas injection point, when injecting lift gas of different composition than the produced gas

• Compressor pressure fluctuations

• Interference between gas-lift wells in the system

Water effects on corrosion and hydrates:

- Understand the effects of accumulated water in lines and gas-lift valves.

Hilly terrain, deviation, and changes in flow direction, can induce water hold-up in wells and flowlines. See Fig. VII-7. In deviated and horizontal wells and flowlines, local water cuts can exceed 20% to 50% despite low inflow rates from production zones and/or low production rates measured at surface, even with


water cut measurements of 1% or less. The amount of water going in and out the system does not represent the amount accumulated in low points of the system.

Fig. VII-7: Water accumulation in horizontal wells and flowlines

The water accumulation in the dips can exist for hours or days or can be permanent. Established local water cut values will change at different production scenarios, i.e. wellhead pressures, gas velocities, and gas-lift injection rates. See Fig. VII-8.

Fig. VII-8: Well and flowline liquid content as a function of gas production rate

Dynamic simulation describes the multiphase flow behavior and provides the key flow characteristics to define water accumulation at any point in the system, and the water accumulation effects on both the hydrodynamic and terrain induced slugging conditions, liquid loading conditions, and related internal corrosion susceptibility, as a function of time and for changing operating scenarios.

Gas Production Rate

Liqu

id C

onte

nt

Initial amount

Final amount


The dynamic simulator provides the resulting trends and profiles for the key variables:

Pressure

Temperature

Water, oil, gas, water vapor, water droplets, oil droplets and gas bubble velocities, superficial velocities, and fractions

Water film fraction and velocity where sweet corrosion exists only if a water film is wetting the pipeline

Flow regime and separated/dispersed flow

Water wetting. Normally it is assumed that water is the continuous phase when the water cut is larger than 30%. The inversion point is usually somewhere between 30% and 50%.

Water condensation rate

pH

Partial pressure of CO2

Shear stress between water film and pipe wall

Critical velocities for water loading and erosion, since erosional areas are more susceptible to corrosion

Figure VII-9 is an example of a profile plot showing the pressure, temperature, and water condensation rate changes along the system profile at a point in time.


0

20

40

60

80

0 10 20 30 40 50 60

Distance (km)

Pre

ssur

e (b

ar),

tem

pera

ture

(°C

)

0.00

0.02

0.04

Con

dens

atio

n ra

te (g

/m2 s)Pressure

Condensation rate

Temperature

Fig. VII-9: P, T and water condensation rate values along the flowline profile

In gas-lift systems, the amount of injected gas can be simulated as a source defined by its rate, pressure, density, viscosity, corrosive content, and CO2. The location of the source can be selected depending on the objectives of the study, at the:

Downhole injection point (operating GLV)

Wellhead

Compressor output

Multiphase flow resulting trends and profiles (as listed above, including water accumulation and corrosion ambient conditions) can be obtained and analysed for the gas-lift injection system, in any of the three cases listed above. Cases 2 and 3 will improve the temperature calculation in the well due to consideration of the counter current heat transfer effects generated by the cooler gas-lift annular flow. Cases 2 and 3 will also take into account any interaction between annulus and production tubing, i.e. slugging generated in the annulus and being transferred to the tubing. Case 3 will further improve the gas-lift optimization analysis by providing the amount of condensate generated in the annulus-injection flow line of the gas-lift system and the location and amounts accumulated and/or being injected into the well. The virtual model in the dynamic simulator can be as complex as necessary.


- Understand the effects of water-induced corrosion.

Most downhole tubular corrosion is associated with the exposure of downhole steel to low-pH environments, encouraged by the combination of groundwater with a variety of acid-forming elements. CO2 dissolves in water to form a weak acid and therefore the solution has a low pH value. A low solution pH accelerates corrosion. The corrosion will take the form of uniform surface or weight loss and localized pitting corrosion. The primary factors that affect CO2

corrosion are the partial pressure of CO2, temperature, and chloride content. An important aspect of including corrosion models in the dynamic simulator is the possibility of identifying the areas of the well and flowline with the highest risk for corrosion problems and the corrosion rates. The location with the highest corrosion rate can be determined by the temperature and pressure variation along the pipeline or by flow effects like liquid accumulation, flow velocity variations, and changes in flow regimes.

It is important to select a dynamic simulator that can break the multiphase flow at any time and system location into the following components: gas, vapor, oil/condensate droplets, water droplets, oil/condensate film, and water film. It is important to know if water or oil wets the steel surface since corrosion takes place only when water is present at the surface. If water is present as vapor or droplets, the contact with steel surface is not as relevant as when water is present as a film. The duration of water as the film contact is also important because this contact can be transitory and not long enough to be relevant.

The selection of the best corrosion prediction model could generate a debate that is beyond the content of this chapter. Different oil companies and research institutions have developed a large number of prediction models for CO2

corrosion of carbon steel in oil and gas wells and pipelines. Many of these models take flow-related parameters like liquid velocity or water, oil, and gas production rates into account. However, most of the models are point models, i.e. they can only be used to predict the corrosion rate at a given location in a well or pipeline where the temperature, pressure, water chemistry, and flow conditions are specified. The models either take liquid velocity as input or assess the flow effect on corrosion by a simplified fluid flow calculation at a point. To perform a corrosion evaluation for a specific well or flowline, it is necessary to perform a fluid flow simulation with a dynamic simulator and use the results from this simulation as input for running a corrosion model at different points in the well or flowline. It is advantageous to combine fluid flow models and corrosion models into a single package. This has been done using the basic corrosion models:


de Waard Model, 1993 and 1995 versions

NORSOK M-506 model

Top of Line Corrosion Model

The de Waard model is a widely used CO2 corrosion model. The NORSOK model is a more recent model. The Top of Line corrosion model is based on laboratory studies performed in 1990 with emphasis on the effects of variation of water condensation rate, temperature, and CO2 partial pressure on corrosion at the top of wet gas pipelines, whereas other models describe corrosion at the bottom of the line. Fig. VII-10 shows a case comparing de Waard and NORSOK corrosion rate estimates. The NORSOK model estimated smaller corrosion rates than the de Waard model for formation water at high temperature with bicarbonate present. The NORSOK model takes account for protective corrosion films. With no bicarbonate present, the two models predicted similar corrosion rates. Fig. VII-11 shows Top of Line corrosion rate analysis results.

0

5

10

0 5000 10000Position / m

Cor

rosi

on ra

te /

(mm

/y)

de Waard model

Norsok model

Fig. VII-10: de Waard and NORSOK Corrosion Rates, showing peaks in corrosion rate in downhill slopes with higher flow velocities


0.00

0.02

0.04

0.06

0.08

0 10 20 30 40 50 60

Distance (km)

Cor

rosi

on ra

te (m

m/y

)

0

50

100

150

200

Fe2+

sat

urat

ion

(ppm

)Fe2+ sat.

TOL corrosion rate supersaturation

Fig. VII-11: Top of Line Corrosion Rate (TOL)

The usual dynamic simulator outputs are:

– Pressure and temperature profile

– Liquid velocity or wall shear stress

– Flow regime and separated/dispersed flow

– Water wetting

– Water condensation rate

The usual corrosion specific inputs are:

– CO2 mole fraction in the gas

– CO2 partial pressure which is the total gas pressure times CO2 mole fraction

– Water chemistry: bicarbonate content and ionic strength

– Glycol concentration and inhibitor efficiency

Calculation of the pH value in the water is based on:

– CO2 partial pressure, temperature and water chemistry


The dynamic simulator offers three options for pH calculation:

– Condensed water without corrosion products for low pH of +/- 4

– Condensed water saturated with iron carbonate for higher pH

– Formation water with specified bicarbonate content

Water chemistry in condensing water may be very different from the bulk water phase:

– Salts from formation water are not present in the Top of Line model

– Condensing water will have low pH and high corrosivity

– Corrosion products accumulate rapidly in the condensing water

– pH increases until the water is saturated with iron carbonate

– Corrosion is reduced by formation of protective iron carbonate films

Typical formation water values as a reference are:

– 60 - 600 ppm bicarbonate (1 - 10 mM)

– 0.5 - 2 M ionic strength

– pH often in the range of 5 - 5.5

Studies in the literature show that for small amounts of H2S, CO2 is the dominant corrosive species. However, for a ratio of pCO2/pH2S > 200-500, which represents small amounts of H2S in a CO2 dominant system, H2S can affect the corrosion rate mainly by formation of more or less protective films (FeS). For pCO2/pH2S < 200-500, H2S usually dominates the corrosion rate and there is sour or cracking corrosion. Sour or cracking corrosion is a very different phenomenon where H+ penetrates the steel and makes it more brittle so it finally cracks. The corrosion models are not made for H2S corrosion:

– Not valid for CO2 to H2S ratios below 20

– Should not be used when the H2S partial pressure is above 0.1 bar (1.45 psi)


In summary:

The modelling and understanding of multiphase fluid flow and CO2 corrosion is important for economic and safe design and operation of wells and flowline systems, and corrosion mitigation plans. Depending on operating conditions, the corrosion mitigation plan may need to change.

Operating and related multiphase flow conditions may affect corrosion of well and flowline steel in different ways. It is important to know if water or oil wets the steel surface since corrosion takes place only when water is present at the surface. Water wetting depend on the fluids, the flow conditions, and the water cut.

The multiphase flow characteristics may also affect corrosion if corrosive species are involved. Higher flow velocities give more turbulence, better mixing, and thus larger transport. The flow also affects the structure and strength of protective corrosion product layers, which reduce the transport of corrosive species towards the steel surface.

Within each flow regime, water and oil may be separated or dispersed. If they are separated, both water and oil wet the wall, but at different parts of the wall. Water is heavier and wets the bottom of the pipe but this is not valid in vertical flow.

Dynamic simulators are unique tools which can provide most of the information required to develop risk-based corrosion susceptibility profiles.

The whole production system can be modelled including the well annulus and gas-lift injection lines. Trend and profile results of the key variables are obtained at any location and time.

An important aspect of including corrosion models in a dynamic simulator is the possibility of identifying the areas of the well and flowline with the highest risk for corrosion problems. The location with the highest corrosion rate can be determined by the temperature and pressure variation along the pipeline or by flow effects such as liquid accumulation, flow velocity variations, and changes in flow regime.

The dynamic simulator provides pressure, temperature, shear stress, and water wetting predictions to calculate CO2 partial pressure, pH, and corrosion rate profiles along the pipeline. The basic corrosion models are included in the simulators, but the implemented models can be extended with other CO2 corrosion models.


The dynamic simulator can be used to estimate the amount of inhibitor required to eliminate or minimize corrosive conditions, and to predict inhibitor distribution and estimate the right type and amount to be used during transient, steady state, and changing operating conditions.

- Understand the effects of hydrates in lines and gas-lift valves

Gas hydrates are crystalline compounds formed by water and natural gas molecules at high pressures and low temperatures below approximately 35°C (95 oF). They are solid ice-like crystals consisting of geometric lattices of water molecules containing cavities occupied by light hydrocarbons (methane, ethane, propane) or other light gaseous compounds (nitrogen, carbon dioxide, hydrogen sulfide). Unlike ice, they can form at temperatures higher than 0°C

(32 oF). They can take many forms from slushy, sticky lumps to a fine powder.

Hydrates can form in gas, gas-condensate, and black-oil systems and can block any flowline. Hydrate blockages can form very rapidly when suitable P-T conditions and compositions are present. Severe P-T changes across chokes and/or gas-lift injection valves can create hydrates. Transient operations such as start-up and shut down are very susceptible to hydrate blockages because the production system is likely to fall into the hydrate region. It is important to model transient operations for deep wet and dry subsea wellheads and subsea tiebacks in deep waters, shut-in and restarting from shut-in conditions can create significant flow assurance problems. Hot fluids from the wellbore will come in contact with a cold flowline and can form hydrates during restart operations. Subsea wellhead conditions at the mudline are often within the hydrate formation region. As the water depth increases, boundary temperatures decrease and the potential for higher shut-in pressures increases due to additional liquid head, as well as the probability of hydrate formation.

Clearing hydrate blockages in subsea equipment or flowlines poses safety concerns and can be time consuming and costly.

Hydrates are the most prevalent flow assurance problem in offshore oil and gas operations, an order of magnitude worse than waxes.

There are different hydrate control design and remediation options such as controlling P-T, removing water, and shifting thermodynamic equilibrium with inhibitors:

• Insulation for passive thermal control

– Used for tie-ins and short to medium length pipelines

– Not normally used for long gas-condensate lines.


• Bundles for active thermal control

– Complex bundles used for deep offshore

– Generally used for risers, tie-ins, and short to medium length pipelines.

• Active Heating

– Electrical

– Hot fluid circulation.

• Depressurization: provide capacity for depressurization and displacement

• Inhibition

– Typical for gas-condensate systems

– Used for oil systems at critical points, e.g. well-heads and wellbore, and during critical operational phases shut-in, cool-down, start-up.

The most common inhibitors are:

• Thermodynamic inhibitors, i.e. inhibitors that move the melting curve of the hydrates towards lower temperatures:

– Alcohols (MeOH)

– Glycols (Mono Ethylene Glycol – MEG)

• Low Dosage Hydrate Inhibitors (LDHI) modify crystal growth or crystal structure to avoid blockage.

Water salinity tends to reduce hydrate temperature. To be conservative, the hydrate inhibitor requirement estimates do not account for the inhibitor effect of produced water salinity.

A significant effort is required in the design phase to develop a production system with an acceptable level of risk. At the beginning of the flow assurance design process, basic design and operating philosophies which cover hydraulics, deliverability, hydrates and waxes should be clearly set.

To determine the P-T conditions under which hydrates can form, use thermodynamic models to predict hydrate behaviour by calculating the hydrate equilibrium curve or hydrate dissociation curve. This is a prediction of temperature at a given pressure above which hydrates will not form.

The PR78 SRK-P EOS model was used to obtain the hydrates curve for the fluid shown in Fig. VII-12.


0

100

200

300

400

500

600

-50 -40 -30 -20 -10 0 10 20 30 40

Temperature - deg C

Pres

sure

- ba

ra

Fig VII-12: Hydrates P-T curve – EOS: PR78 Peneloux

The hydrate curve represents the thermodynamic boundary between hydrate stability and dissociation. A hydrate formation curve represents the pressure temperature relationship at which hydrates may form, whereas a hydrate dissociation curve represents the points where a hydrate crystal, once formed, will dissociate. The dissociation curve is typically 2 to 3 ºC (3.6 to 5.4 oF) above the formation curve. The region between these two curves is the zone where the hydrates are unstable. The hydrate dissociation curve, also termed the “hydrate curve,” therefore presents a conservative scenario and is used in studies for hydrate assessment calculations.

- Understand when, where, and under which conditions hydrates may be formed.

The cost of thermodynamically inhibiting production systems under steady state and/or transient operations can be prohibitive. It may not be possible to avoid the hydrate formation region in all probable operating scenarios. It is therefore important to estimate the risk of forming a hydrate plug during a restart operation or in a new field design.

Modelling is an effective way to reduce uncertainty by screening various options. Dynamic simulation offers a methodology to estimate when, where, and under which conditions hydrates may be formed in a production system, during transient and steady state conditions, based on the difference between a


hydrate temperature (Thyd) and fluid temperature (Tf) at section pressure. The model calculates the output variable:

DTHYD = Thyd – Tf

if DTHYD>0 then the section is within the hydrate region.

Plots of the difference between the hydrate formation temperature and the fluid temperature (DTHYD) at any time are termed subcooling profiles. Positive temperature numbers in these profile curves indicate the potential for hydrates formation in these locations. Fig. VII-13 shows an example of hydrate margins in a riser during well kick-off.

Profile Data (deg. C) – Riser Length (metres) – Time (Minutes)

Black - Time 0 (Static Conditions)

Red: Time 1; Green: Time 2; Blue: Time 3; Purple: Time 5; Yellow: Time 10Profile data

GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 0GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 1GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 2GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 3GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 5GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HYDRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 10

C

0

-10

-20

-30

-40

-50

-60

-70

-80

-90

-100

Length [m]300250200150100500

Fig VII-13: - Hydrate Margin in Riser vs Time during well kick-off – 60 MMscfd, 15 WGR

Dynamic simulation offers application of different hydrate control methodologies in the virtual model such as insulation, active heating, and inhibition, and selecting the most effective one for steady state and transient operating conditions.


Fig. VII-14 shows the influence on the amount of MeOH used in the hydrate dissociation curves and Fig. VII-15 shows the overlap of the worst P-T trends in the riser profile, during well clean-up (blue), shut-in (purple), end of shut-in (doted purple), and kick-off (green), indicating the amount of MeOH required to avoid falling in the hydrates region.

Hydrate Curves with MeOH Inhibition(kg MeOH / kg Aqueous)

0

500

1000

1500

2000

2500

3000

3500

-5 0 5 10 15 20 25 30 35

Temperature (C°)

Pres

sure

(psi

a)

0%wt 1%wt 5%wt 10%wt 15%wt 20%wt 25%wt 30%wt 35%wt 40%wt 45%wt 50%wt 60%wt

Hydrate FormationRegion

Fig. VII-14: Hydrate Dissociation Curves with MeOH inhibition (0% to 60%)


Hydrate Curves with MeOH Inhibition - (kg MeOH / kg Aqueous)

0

500

1000

1500

2000

2500

3000

3500

-5 0 5 10 15 20 25 30 35 40 45

Temperature (C°)

Pres

sure

(psi

a)

0%wt 10%wt 20%wt 30%wt40%wt 45%wt 50%wt 930min-RISER-Shut-in2370min-RISER-kick-off 5min-RISER-Clean-up 2314-RISER-SI-end

Hydrate FormationRegion

Fig. VII-15: Hydrate Inhibition Curves with the overlaps of the worst case P-T trends from Riser Profile Plots

In addition to the flowline, the well should be included in any hydrate formation study. Inhibitor injection only protects components in the production system downstream of the injection point; therefore the location of the injection point is an important decision. The most common locations are downhole in the well immediately above the SCSSV, at the tree between master and wing valves, and on the manifold.

Inhibitors can provide protection against hydrate formation if sufficient quantities are injected, but under injecting may accelerate the kinetics of hydrate formation. Therefore, it is typical to overdose to be safe. Significant savings can be obtained using dynamic simulation to estimate the right amount of inhibitor and the times when inhibitor injection is no longer required. The water production rate needs to be known. The main uncertainty is the amount of the dissolved salts in the produced water and their effect on hydrate formation. Salinity in produced water tends to reduce hydrate temperature, but to be conservative normally the calculated hydrate inhibitor requirements do not account for the inhibitor effect of produced water salinity. However, dynamic simulation can include the affects of salinity. Dynamic simulation allows the tracking of the amount of inhibitor in the well/pipeline to ensure enough inhibitor is available. Inhibitor can be tracked in both the water and gas phases. Dynamic simulation gives: – Inhibitor (MeOH or MEG) concentration along the well / flowline profile– Time to reach a desired inhibitor concentration


Dynamic simulation allows development of operating guidelines that ensure proper injection rates and distribution of inhibitors for all operating modes.

An example of MeOH injection tracking is given in the Fig. VII-16. Upon restart, cold gas enters the flowline due to Joule Thompson cooling on gas expansion. This cooling is inhibited by injecting MeOH upstream of the wellhead prior to start up and continuously for the first 3 hours. Additionally, as the cold liquid residing in the flowline is pressured, it heads towards the hydrate region. This takes some time as restart is slow, and is worse at high water cuts

Fig. VII-16: Tracking MeOH injection and Hydrates Potential

Dynamic simulation can answer the following questions:• What is the predicted hydrate dissociation temperature profile? How far are the

conditions from hydrate formation? Where? When?• When will the temperature fall into the hydrates region?• How deep below the wellhead will the well experience hydrates problems?

When?• What’s the best solution for the well flow assurance problems?

– Pressure control– Temperature control


– Remove supply of water – Perform a hot or cold re-start– Preheating the flowline– Flowline depressurization– Insulation– Inhibitor injection? Where? When?

Hydrate remediation schemes can be divided in two:

Reducing pressure in the system to the point where ambient temperatures allow melting

Active heating

These schemes should be dynamically modelled prior to execution. Dynamic simulation is a tool to evaluate and design successful hydrate remediation operations. For instance, the wellbore thermal-hydraulic transient simulation can be useful to assess the feasibility of injecting hot oil in the tubing-casing annulus for melting hydrate plugs formed inside the tubing in dry-tree gas-lift wells38,39,47. Dynamic simulation can provide the required: Bleed-off tuning pressure Amount of inhibitor Time for inhibitor distribution Heating temperature and oil injection rate Operational guidelines to restart well production

Due to the potentially severe economic impact of forming hydrates plugs, to better estimate the time required for hydrate plug formation, and to better understand hydrate kinetics, new hydrate growth, deposition, sloughing, and jamming models are being developed. E&P companies, universities, and research centers have been developing models with extensive testing using flow loop data and field data. This is still considered experimental but some field application results that demonstrate hydrate rate formation and hydrate mass in pipe are encouraging51.

Production chemistry:- Understand the effects of wax and/or paraffin formation and the impact of

each of these on well performance and stability.

Production chemistry issues associated with wells and production/injection systems are relevant to cost-effective field developments and operating integrity. Plugging due to wax, paraffin, asphaltene, scale, and hydrates reduces the ability of the well-flowline production/injection system to deliver the fluids. In addition, deep water operations amplify the environmental and safety concerns. The increased risk associated with long sub-sea tiebacks, dry-tree risers, and extended export pipelines in cold ambient water should be considered by operators when planning their development scenarios. Under


these severe conditions, it is important to understand multiphase fluid properties and the design options to prevent or mitigate flow assurance challenges. Dynamic simulation is a tool to provide understanding of flow behavior and the resulting internal ambient conditions at any point of the production system.

Waxes, wax deposition, and wax gelation are three potentially important issues in crude oil and gas condensate systems.

Waxes are high molecular weight, straight, long-chain hydrocarbons (C17 to C75) that precipitate from the produced fluid. They are crystalline and are usually characterized by the wax appearance temperature (WAT) and pour point where the first wax crystals start to precipitate out of solution.

The deposition of n-paraffin waxes will commonly occur along the well/flowline walls when the temperature of produced fluids falls below the WAT or cloud point. Deposition rates can be attributed to many factors including paraffin content, fluid viscosity, flow rates, gas/oil ratio, and the heat transfer coefficient or U-value.

The problems caused by waxes are twofold:

Wax produces choking or total blockage through increased apparent inner wall roughness and decreased diameter effects.

Increased apparent fluid viscosity; viscosity can reach the point where the wax forms a gel and excessive pressure may be required to generate flow.

Wax gelation is less common in steady-state than wax deposition, but it can have greater impact if, during transient operations like shutdowns and start ups, fluid temperatures cool below WAT and pour point, allowing the formation of a solid wax column. This condition can completely block the flowline. During restart operations there may not be sufficient pressure available to "break" the gel and allow the well to flow.

When dealing with high wax content crudes, strategies for wax prevention must be developed.

For waxy crude production systems, the criterion used for thermo-hydraulic studies is the prediction of the fluid temperature along the system from the perforations to the facilities needs to be above the WAT. Dynamic simulation can accurately calculate, if input data and fluid characterization from lab studies have been properly done, where and when fluid temperatures fall below WAT and the wax deposition rate as a function of time and space. See Fig. VII-17.


Fig. VII-17: Wax Deposition Rate Along the Pipe vs. Time

Dynamic simulation can also model realistic pig runs and the results of the run. The pig-plug model tracks the masses on each side of the pig, calculates the leakage through the pig, and modifies the forces acting on the control volumes surrounding it. The pig velocity is set based on the local volumetric flux, taking into account any pig leakage rate. The influence of the pig on the flow conditions are through pig and related friction forces, the gravity forces due to the mass of the pig, and any leakage of the pig.

Dynamic simulation predicts the need of:

Pigging

– Efficiency of wax removal after pigging

– Pressure requirements for wax scraping

– Frequency required for wax removal operations

Thermal insulation required to minimize or eliminate wax formation

Non-Newtonian behavior of viscosity due to wax precipitation into oil phase

Self-regulation of wax deposition due to release of latent heat

Active heating required to minimize or eliminate wax formation

Chemical injection. Diluents can reduce viscosity and cause a depression in the WAT resulting in a reduction of frictional losses and a decrease in thermal insulation requirements.

Gas-lift injection as diluent to reduce cloud point and cause WAT suppression

Investigation of increase in 1st separation pressure results


Dynamic simulation can:

Perform a material balance of wax components

– Wax in dissolved oil

– Precipitated wax suspended in oil

– Precipitated wax deposited on walls.

Describe the dynamics of wax formation/dissipation

– Wax precipitation

– Molecular diffusion and shear stripping

– Wax melting.

Wax deposition rate analysis is done using one model, or running sensitivities to the following multiphase flow wax deposition models:

1. Rygg, Rydahl & Rønningsen (RRR)

The RRR model considers a laminar velocity sub-layer in turbulent flow. Wax deposition is estimated from the diffusion of wax from the bulk flow towards the wall as a result of temperature gradients and shear dispersion effects. Varying inner pipe wall friction due to wax deposition is also included. It may under-predict wax deposition rate for single phase oil cases.

2. HEAT ANOLOGY, University of Tulsa

The heat analogy model was introduced to extend the wax deposition model to handle laminar flow. Deposition rate reduction due to shear stripping and rate enhancement due to entrapment of oil and other mechanisms not accounted for by the classical Fick's mass diffusion theory, were incorporated through the use of dimensionless variables and empirical constants derived from the wax deposition data. The kinetic model, although semi-empirical, predicts wax thickness with an acceptable accuracy, especially at high oil superficial velocity, and provides an insight for future model development.

3. MATZAIN

The Matzain model considers a concentration boundary layer as for laminar flow. It has a diffusion enhancement effect which is not directly related to the shear stripping part of the Matzain/Tulsa model where shear stripping effect itself may be tuned.


A typical wax analysis should include:

• Fluids and wax characterisation measured in the laboratory

– Compositional analyses (HTGC)

– WAT

– Pour point

– Wax content

– Viscosity

– Deposition rate or diffusion coefficient

– Deposit analysis including yield strength, trapped oil

– Gel strength

– Impact of inhibitors

– Impact of diluents

• Thermal hydraulics analysis, e.g. insulation, cooldown

• Wax deposition rate analysis

• Pig-ability analysis

• Gel restart-ability analysis

A wax thermo-hydraulic study strategy should include the following steps:

• Define/understand the characteristics of fluids, wax, and gel

• Keep the fluid hot by insulating or direct heating of the well-pipeline

• Alter wax characteristics by blending with less waxy fluids or use wax or gel inhibitors

• Quantify the extent of wax buildup to establish frequency of wax removal operation

• Remove wax frequently by pigging, melting, or removal by chemicals

• Quantify cool down to gel formation by displacing the fluids to avoid plugging.

Dynamic modelling can also provide indicators for profiling well-pipeline temperatures and wax buildup. This tool can assist the operator in making economic decisions and exploring multiple design options. Current modelling technology includes real-time, online well-pipeline monitoring and advisory systems that help manage a series of flow assurance issues including pigging operations and any “what-if” scenarios.


Gas-lift valve performance:- Understand information and models for dynamic gas-lift valve and

orifice performance; how and when to use them.

Gas-lift valve performance relates to the valve’s flow performance. Many other criteria, such as reliability, robustness, corrosion resistance, and ease of maintenance are also performance factors but in this section, the subject will be focused on flow performance.

The purpose of a gas-lift valve is to open at a predefined pressure and allow gas to flow from the annulus to the production string. The valve should then close at a predefined pressure, shutting off flow from the annulus into the tubing. The pressures at which the valve opens and closes are determined by performing a gas-lift design. Each well is different and therefore each valve will have a different opening and closing pressure.

The flow performance of a gas-lift valve is a function of the valve design and application conditions. There are two major categories of gas-lift valve designs: Injection Pressure Operated (IPO) and Production Pressure Operated (PPO). An IPO valve is designed to have opening and closing pressures that are most sensitive to annulus pressure. PPO valves are designed to have opening and closing pressures that are most sensitive to production pressure. The flow performance of IPO and PPO valves are markedly different.

The single most important factor effecting flow performance of a gas-lift valve is the port size. In most cases, the larger the port, the greater the flow rate. This is true for both IPO and PPO valves. The next most important factor is the ratio of injection pressure (Piod) to opening pressure (Pvot); the higher this ratio, the greater the flow rate. Finally, load rate and stem travel of the valve have a significant effect on performance. The port size and ratio of Piod to Pvot are application dependent. They are not a function of the valve design. The load rate and stem travel are a function of valve design.

For many years the flow performance of a gas-lift valve was determined using the Thornhill-Craver equation53. This equation was developed to predict the flow performance of wellhead beans or chokes. These chokes were used to control the flow of gas from the gas injection line into the annulus. The beans were cylindrical, about 6-7 inches long, and had a hole drilled through the center. The size of the hole determined the choke size. Many tests were performed to determine the flow rate at different pressures and the equation is quite accurate for this type of choke.


The Thornhill-Craver equation existed long before the industry had the ability to test gas-lift valves and, as a result, was used as the best approximation of the flow performance of gas-lift valves. Most gas-lift design programs continue to use Thornhill-Craver to compute flow through gas-lift valves, even though it was never intended for use with gas-lift valves. Recent testing of IPO and PPO gas-lift valves has shown that the Thornhill-Craver equation will over estimate gas-lift valve flow rate by a factor of two to three. When used to estimate the flow through orifice valves, Thornhill-Craver will over estimate by about 20-30%.

Fig. VII-18 shows the difference in performance of a 1-inch IPO valve using both the Thornhill-Craver equation and a tested performance model. The model is tested by the Valve Performance Clearinghouse (VPC); an industry consortium for testing gas-lift valves.

1 Inch IPO with 12/64thsVPCPvoT= 917 Pcf= 900Temp=125

1 Inch IPO with 12/64thsThornhillPvoT= 917 Pcf= 900Temp=125

Flowrate -(Mscf/d)

Downstream Pressure - (psig)

0

200

400

600

800

0 200 400 600 800 1000

Fig. VII-18: Thornhill-Craver equation and VPC model Valve Performance Comparison

As noted, the flow performance using the Thornhill-Craver equation shows typical orifice flow characteristics. The tested performance model shows the valve flow rate increasing as differential pressure increases and then decreasing and finally closing. The Thornhill-Craver equation predicts flow rates much higher than is actually possible.

Fig. VII-19 shows the same valve when the ratio of Piod to Pvot has been increased sufficiently to ensure the IPO valve will operate as an orifice.




1 Inch IPO with 12/64thsThornhillPvoT= 917 Pcf= 950Temp=125

Flowrate -(Mscf/d)


0

200

400

600

800

0 200 400 600 800 1000

Fig. VII-19: Thornhill-Craver equation and VPC model Orifice Performance Comparison

In this case, the 1-inch IPO valve has flow performance similar to Thornhill-Craver. These two examples show the importance of the ratio of Piod/Pvot to valve performance. With a Pvot of 917 psi, when Piod is 900 psi (Piod/Pvot = 900/917 = 0.981), the valve has a peak flow rate of 6,732 m3/d (225 Mscfd) and throttles closed as production pressure decreases. When the ratio is 1.036, the valve performs as an orifice with a peak flow rate of 6,732 m3/d (500 Mscfd).

This difference in flow behavior is caused by a valve property referred to as load rate. Load rate is a measure of the gas-lift valve’s ability to expose a full open port. Historical models of valve behavior and those employed in most gas-lift design programs postulate that when the injection pressure (Piod) reaches the opening pressure (Pvot), the valve will be fully open and function as an orifice. Load rate prevents this from happening.

The nitrogen charge in the dome and the bellows act as a spring that attempts to hold the valve in a closed position. As with all springs, increased force is required to compress the spring. For gas-lift valves, increased pressure is required to compress the bellows and allow the valve to expose a fully open port. The higher the load rate, the higher the ratio of Piod/Pvot required to cause the valve to fully open.

Fig. VII-20 shows the difference in performance for a 1-inch IPO valve with different load rates. The performance curve with the lower flow rate corresponds with the valve with a higher load rate.




Flowrate -(Mscf/d)


0

100

200

300

400

500

0 200 400 600 800 1000

Fig. VII-20: VPC model Performance Comparison with Different Load Rates

The amount the bellows can be compressed is referred to as stem travel. The bellows compresses in a nearly linear manner until the bellows convolutions begin stacking. At this time the load rate increases dramatically. The distance the bellows compresses in the linear portion is referred to as the stem travel. Stem travel must be sufficient to fully expose the port. This amount differs depending on the port size.

Fig. VII-21 shows a valve with a 16/64ths port and varying amounts of stem travel.


1 Inch IPO with 16/64ths VPC Pcf= 875psig PvoT= 917psig Temp 125F

Trvl .04

Trvl .034

Trvl .028

Trvl .022

Trvl .016

Flowrate -(Mscf/d)


0

100

200

300

400

0 200 400 600 800 1000

Fig. VII-21: Stem Travel Valve Performance Comparison

One last variable affecting flow performance is the size of the valve. 1-1/2-inch valves have much higher flow rates than 1-inch valves with the same port size. Fig. VII-22 compares a 1-inch and 1-1/2-inch IPO valve with the same port size and configured to have the same opening and closing pressures.



Camco R-20 with 12/64thsVPCPvoT= 920 Pcf= 913Temp=125

Flowrate -(Mscf/d)


0

200

400

600

800

0 200 400 600 800 1000

Fig. VII-22: Valve Size Performance Comparison

The flow performance of a gas-lift valve is markedly different from the Thornhill-Craver equation. The amount of gas flowing through a valve has a significant effect on how a gas-lift well performs. A simulator must have good gas-lift valve performance models to give accurate result. Several valve performance models are available.

TUALP Model

The Tulsa University Artificial Lift Project (TUALP) performed many tests on gas-lift valves in the 1980’s and ‘90’s. The results of these tests and the models were published as graduate student theses and are available from the Tulsa University Library. These models are statistical and attempt to predict performance by adjusting the coefficients in the parabola equation. The models do not account for valve properties such as load rate and stem travel. The models have an accuracy of about 30-40% within the range of pressures used for the tests. Beyond this range the accuracy drops off significantly.


Winkler-Eads Model

This model uses the Thornhill-Craver equation with a modification. Normally the Thornhill-Craver equation uses the full area of the port but this model uses only that amount of the port open to flow. This is calculated using the force balance equation for the valve, and the load rate. It assumes the area open to flow is equal to the surface area of the frustum of a right cone. This model is entirely theoretical and does not require testing of the gas-lift valve. As such, it will not account for specific valve design characteristics. The model is accurate to within 15-25% for valves with port sizes less than 12/64ths inch. The description of the model with equations is available54.

API Simplified Model

This model is a combination of theoretical and tested valve performance factors. The model uses the ISA method of testing valves to determine the flow coefficient (Cv) and combines this with the force balance equation for the valve. The model has an accuracy of 15-25% for all port sizes and pressure ranges. This model was first published in API Recommended Practice 11V2. It is also available in ISO 17078.2.

Valve Performance Clearinghouse (VPC™)

This model is a combination of theoretical and tested valve performance factors. The model uses the ISA method of testing valves to determine the flow coefficient (Cv) and actual flow performance tests of the valve. This is combined with the force balance equation using a tested load rate of the valve to determine the amount of stem travel. A correlation is then developed using actual test data to predict flow performance. The model has an accuracy of 10-15% for all valves, all port sizes, and all pressure ranges.

Most of the current gas-lift design programs now have the ability to enable the VPC™ models.

Shell Valve/Choke Model

Shell Oil Company places chokes downstream of the port in IPO valves and finds that the flow performance of the valve is superior to a valve without chokes. This seems counter-intuitive but anecdotal evidence has proven it to be true. The VPC™ conducted tests and verified that in some cases, a


downstream choke in an IPO valve actually increases the flow rate. See Fig. VII-23. This model has an accuracy of about 10-15%.

Fig. VII-23: Comparison of Valve Performance with a choke (Green Line) and without a choke (Blue Line).

Summary

The unloading sequence of a gas-lift well is important. If the gas-lift design is unable to unload to the orifice valve at the desired depth, the well will under perform with injection through one or more upper valves and possibly with multipointing.

Unloading gas-lift valves do not perform as well as Thornhill-Craver predicts. This is particularly true for 1-inch valves. The ability to design a gas-lift well that performs as expected is directly connected to the ability to predict flow performance of the unloading gas-lift valves. With respect to gas-lift simulators, the accuracy of the results depends on use of a good valve performance model.

How to use the models

All of the models use equations or correlations to compute flow rate. The degree of complexity of the equations or correlations is a function of the model used. In all cases, it is best to use a computer to solve the equations.


The models will predict a single flow rate for a specific set of conditions. To develop a full performance curve as shown in the graphs above, the annulus pressure (Piod) is held constant while the production pressure (Ptf) is iterated from a value equal to Piod and decreased to atmospheric or until the valve closes. This type of curve shows typical performance but is not realistic for an actual unloading scenario. During unloading, and sometimes during lifting, the annulus pressure and production pressure are constantly changing.

To give accurate results, a simulator must invoke the model at each point in time for the specific conditions existing at that time. Use of a pre-calculated performance curve as shown in the graphs above to predict valve flow rate during the entire unloading sequence will lead to simulator errors and could give false results.

When to use the models

Valve performance models are used during two distinct phases. Once during the design phase, and during the simulation phase. The design phase is a static condition and the simulation phase is dynamic. In the design phase, valve performance models are used to determine a port size for the valve. In the simulation phase, the valve characteristics are given and the model is used to predict or analyze performance.

Well equipment:- The effects of down-hole pressure restrictions such as safety valves,

corrosion, scale, and wax deposits, and the effects of tight spots or holes in the tubing.

Ensure that dynamic simulation flow assurance studies are performed in the well. Normally, facilities engineers only perform flow assurance studies downstream of the sub-sea well and do not include the wellbore.

In well completions, there will be a slight reduction in internal diameter and less roughness in the down-hole safety valve, SSD, ICV, ICD, PBR, and nipple profiles that affect the fluid flow pattern and frictional pressure drop. Include all such down-hole equipment while using dynamic modelling tools to predict the effect of this equipment on the fluid flow.

In the upper part of the well closest to sub-sea temperature conditions, the temperature can fall below hydrate and/or wax deposition conditions. The


SSSV should be located in a zone were no hydrate formation or wax deposition is expected as this could compromise its closure. Use hydrate and wax modelling as appropriate to see the impact of hydrate and wax deposition, and to plan remedial hydrate and wax prevention and wax cleaning schedules.

Figures VII-24, VII-25a and VII-25b show an SSSV and the effect of scale deposition in a gas-lift mandrel.

Fig. VII-24: Subsurface Safety Valve

Fig. VII-25 a: Scale deposits b: GL Mandrel cut-a-way


Typically, the major pressure drop will be in the choke used to control flow at surface and downhole (ICV, ICD, GLV, etc.). P-T conditions downstream may fall in the hydrate formation or wax deposition zones.

- The effects of risers and the effects of surface equipment such as flow lines, manifolds, separators, and separator back-pressure.

The gases and liquids may exist as a homogeneous mixture or the liquid may be in slugs with gas pushing behind it. The liquid and gas may also flow parallel to each other or other combinations of flow patterns may be present.

Fig. VII-26 illustrates some common vertical and horizontal multiphase flow patterns. Each of these flow patterns will produce a different pressure drop over a given distance. Well/Flowline geometry will affect multiphase flow patterns. See Fig. VII-27. In addition to flow pattern, factors affecting the pressure loss in multiphase flow include:

Inside diameter of flowing conduit

Wall roughness

Inclination

Liquid density

Gas density

Liquid viscosity

Gas viscosity

Superficial liquid velocity

Superficial gas velocity (See Fig. VII-28)

Liquid surface tension

Wall contact angle

Gravity acceleration

Pressure gradient


Fig. VII-26: Common vertical and horizontal multiphase flow patterns

Fig. VII-27: Well/Flowline Common Geometries


Fig. VII-28: Effect of critical velocity in horizontal/inclined flow.

Since the pressure drop is caused by a complex interaction of many factors, one of the major problems in analyzing flowing wells and designing gas-lift installations has been the prediction of flowing pressure at depth. It is important to understand the pressure drop in the horizontal flow line to determine the back pressure at the well head. This problem has been the subject of numerous studies. A dynamic simulator is required to understand multiphase flow behavior.

Extra pressure is required to lift fluids through a riser. Furthermore, risers are terrain induced slugging generators. Dynamic simulation is required to properly model terrain slugging.

Well design:- The effects of well design and the associated dynamic effects on well

operations includes:

The type of well completion, well profile, and well location play a major role in designing gas-lift components and systems. Figures VII-29 a, b and c show common vertical, horizontal, and multi-lateral well completions.

Dynamic modeling with the current well fluid properties, well/flowline geometry, well completion and flowline data, and flow restrictions should be


used to simulate the effect of gas-lift at different locations. Chapter VII-D, provide more detail information on dynamic modelling implementation.

o Vertical wells o Horizontal wells o Multi-lateral wells

Fig. VII-29: a- Vertical well profile b - Horizontal Well profile c - Multilateral well profiles

Slug flow and water accumulation are typical problems associated to horizontal wells:

• Horizontal wells allow a reduced drawdown to obtain a desired rate, thereby maintaining the reservoir pressure above the bubble point for longer periods of time, thus reducing GORs and improving recovery. But gas velocity may be too slow and lead to slug flow. The addition of gas-lift gas increases the superficial gas velocity and changes the multiphase flow to a more stable flow regime.


• Horizontal wells producing below bubble point pressure can act as downhole separators generating slug flow. The terrain can also be originating slug flow.

Dynamic simulation is the optimum method for predicting slugging flow and estimating water accumulation, as explained in detail in Sections VII-A and B. To properly model the production from horizontal wells, several inflow points should be included in the dynamic model. Each inflow point can have different reservoir properties and IPRs. Free gas and/or water sources can also be included to model gas and water coning respectively.

In the case of intelligent wells with multiple production zones such as multilayer and/or multilateral legs that allow remote selective production, dynamic simulation brings the additional benefit of virtually testing each zone individually or in combination to establish maximum total production potential prior to any actual operation. Well clean-up operations can be improved by simulating how layers and legs can be produced separately to generate the maximum drawdown. During production, gas and/or water coning can be avoided and slugging minimized by optimizing the opening of each ICV.

Dynamic simulation can help justify the use of intelligent completions by demonstrating the added value during the well completion design stages. The well may not be producing from half of the reservoir section without intelligent completions.

In multi-lateral or multi-layer wells producing from different reservoirs with different fluid compositions, dynamic simulation offers the possibility of tracking the different fluids and estimating the resulting mixture composition along the production/injection path. Dynamic simulation can also predict cross-flow between formations during static or producing conditions. Chapter VI-E describes the application of dynamic simulation in complex and intelligent wells in detail.

- When and where to inject gas in a well: in the vertical, in the knee, in a rat hole, in the horizontal section.

Gas-lift is by nature a transient artificial lift system. Dynamic simulation can define the amount of gas-lift gas and the optimum gas injection point.

Fig. VII-30 shows where to inject lift gas for more effective fluid flow and how to avoid liquid hold up and loading in a riser section.


Fig. VII-30: Vertical well profile

More in-depth analysis is required to determine when to start gas-lift, where to inject gas, and how much lift gas is required for optimum well performance. Dynamic modelling may be used and various scenarios run to simulate injecting at different locations in the well tubular or riser sections with the expected fluid rate, to understand the impact of gas-lift and optimize total well production and lift gas utilization.

In offshore wells producing to a platform, gas-lift optimization may be obtained initially by injecting gas in the base of the riser rather that going all the way through a sub-sea flowline to the wellhead with the pressurized lift gas. The cost savings can be significant. Later in the field life, when reservoir depletion occurs and water cut increases, gas-lift injection through the tubing-casing annulus may be the optimal scenario. Dynamic simulation can compare the different scenarios and define the optimum approach. It can also forecast the optimum time to switch producing scenarios and methods.


9. Case Histories

This is a summary of pertinent case histories where dynamic simulation has been used to address and solve real world gas-lift well and system situations. Chapter IX provides a list of papers with actual case applications and evaluations.

Case History 1: Penguins Gas-Lift The Penguins field in the North Sea was discovered in 1974. Several exploration wells were drilled until 1991 to understand the field and acreage. Numerous field development options were considered; it was concluded that a 65 km (40.4 miles) sub sea tie-back to the Brent Charlie platform was the most economic option. The key technical justifications for this choice were that processing capacity was available, product evacuation routes were established, and gas-lift compression was already in use for the platform wells.

The field comprises a cluster of reservoirs and is located north of the Brent Charlie platform, UKCS and has 9 production wells. See Fig. VIII-1. These wells produce via a single 35.6 cm (14 inch) commingled flowline. Initially the field produced naturally from 2003 to 2007, at which time some wells started to require artificial lift.

Fig. VIII-1: Penguins Field Schematic Layout in Relation to the Brent Charlie Platform

Based on the reservoir fluid type, it was foreseen that artificial lift would be required in a number of wells to ensure ultimate recovery; therefore these wells were


completed with a single gas-lift mandrel (GLM) with a shear orifice valve pre-installed.

As the wells depleted, the black oil wells began to struggle to flow, to the point were the gassier condensate wells had to be choked back severely to avoid killing the black oil wells. Eventually, one well ceased production when other wells were flowing. The other wells were also having kick-off problems and required the pipeline to be bled down to below normal operating pressure of 35 – 40 barg (507.6 – 580.2 psig) to allow them to restart. Hence optimization of the field production became more and more complex over time.

In 2005 the gas-lift project was approved, using a 10.2 cm (4 inch) supply line from the Brent Charlie platform, and modifying an existing injection compressor to provide the required rate of 500 Km3/d (18 MMscf/d) of lift gas at pressures up to 280 barg (4061 psig).

As the project on-stream date drew closer, it was realized that the commissioning phase posed some challenges and required detailed planning. Commissioning challenges that were evaluated included:

Avoiding hydrates or other temperature related integrity limits due to Joule Thomson effects through various valves/restrictions in the system.

Staying within velocity limits of orifice valves in the side pocket mandrels.

Minimizing risk of slugging of wells and/or pipeline during commissioning and steady state flow which could result in a platform trip at Brent Charlie.

Minimizing time taken for commissioning process and hence production deferment.

Determining measurable indicators as to when the gas-lift line, jumpers, and annuli were cleared/unloaded.

Following the commissioning phase, challenges that existed in field operations were:

Managing liquid slugs during future start-up of the system.

Maintaining stability of the wells under conditions of continuous gas-lift.

Engineering assessments and achieving the desired targets were primarily carried out by utilizing both a commercial dynamic transient simulator and steady-state modelling software.

The main objective of the studies carried out using transient simulations for the Penguins field is to provide high-level guidance and procedures for the various operational aspects of interest for the gas-lift system. To obtain an all-purpose model, the complete Penguins system including the wells, the 35.6 cm (14 inch) production pipeline and the 10.2 cm (4 inch) gas-lift pipeline, was built. For each of the wells, the inflow and outflow were modelled using parameters including


reservoir pressure, PI, and fluid PVT. This model was validated against field data and was determined to be representative of the Penguins system.

In the interest of computational expense and time, subsequent simulation work was done using simplified models reduced from the full system model. The full system model includes the production and gas-lift lines and all the wells, gas-lift annuli, and jumpers. Typical model run times were reduced from the order of days to hours.

The phases of clearing MEG from the gas-lift line and crossovers, and the unloading of the base oil from the annuli were modelled in an iterative fashion to determine the required procedures to remain within the system limitations.

The main step requiring iteration was the shearing of the gas-lift orifice in each well. Initial runs of the model resulted in velocities across the orifice that far exceeded the 1 bbl/min limitation and also showed temperatures at the gas-lift choke that reached –30 oC (-22 oF). The process control for this step was to reduce the pressure in the gas-lift line. Iterations were run on each well to find a balance that allowed the process to stay comfortably within the system limits of temperature and velocity, while minimizing overall time for commissioning.

Further to the initial commissioning, subsequent field start-up guidelines were derived from transient simulation. Scenarios developed for analysis were based on attempts to generate the largest perceivable slug sizes arriving at the Brent Charlie facilities. These were established with the most aggressive start up scenarios foreseeable under the limits of operation. The sequences generate liquid arrival rates within the handling capacity of the platform facilities.

Well stability was a concern as this may cause undesired interruptions in production. Transient simulation has been used to investigate stability for each of the gas-lifted wells under conditions of continuous gas-lift. The results of the dynamic simulations have been used to create stability maps whereby regions of unstable well production have been identified.

Commissioning of the gas-lift line and the 5 wells was efficiently and successfully executed as a result of the good planning and guidance provided by transient modelling.

Dynamic simulations using transient modelling were helpful in providing guidance and procedures for the commissioning process, predicting pressure, temperature, velocity transients, and the associated integrity risks.


Case History 2: Transient Gas-Lift Analysis in ERD and non-ERD Wells Introduction

A transient multiphase flow simulator was used to investigate gas-lift stability in several extended reach (ERD) and non-ERD well types. Models have been built for 8 different cases:

17.8 cm (7 inch) ERD well model

- Injection pressure 110 bar (1595 psia)


17.8 cm (7 inch) non-ERD well



14.0 cm (5.5 inch) ERD well



14.0 cm (5.5 inch) non-ERD well



Gas-lift stability was evaluated using a commercial transient simulator for each of these cases at water cuts of 0, 40, 60, 80, and 95%. A tubing head pressure of 16 bar (232 psia) and a reservoir pressure of 175 bar (2538 psia) were assumed.

Conclusions

For nearly all cases, flow is predicted to be stable with the exception of water cuts greater than 80-90%.

The injection pressure did not have a significant impact on the stability of the flow. However, since the injection depths were slightly deeper for the higher injection pressure cases, the flow was slightly more stable in the 110 bar (1595 psia) injection pressure cases.

For the ERD wells (deep injection), there is not a significant difference between the 17.8 and 14.0 cm (7 and 5.5 inch) tubing in terms of flow stability at low water cuts. As expected, the 14.0 cm (5.5 inch) tubing wells are more stable at higher water cuts.

For the non-ERD wells (shallow injection), the 17.8 cm (7 inch) tubing provides the greatest stability with gas-lift (case 3 is stable at all water cuts and gas injection rates).


Recommendations

ERD Wells

- If 113,280 m3/d (4 MMscf/d) injection rate is available, 14.0 cm (5.5 inch) tubing in the ERD wells will allow for stable production at water cuts up to 80% for both 110 bar (1,595 psia) and 140 bar (2031 psia) injection pressures. While the 17.8 cm (7 inch) tubing will allow for higher production rates, the flow will be unstable at 80 % watercut with 140 bar (2031 psia) injection pressure.

- If 226,560 m3/d (8 MMscf/d) injection rate is available, 14.0 cm (5.5 inch) tubing in the ERD wells will allow for stable production at all water cuts. While the 17.8 cm (7 inch) tubing will allow for higher production rates, the flow will be unstable at 95 % water cut.

17.8 cm (7 inch) tubing in the non-ERD wells will allow for higher production flow rates without gas injection. Also, at gas injection rates of 4 and 8 MMscf/d, production will be stable at all water cuts. This is not the case with 14.0 cm (5.5 inch) tubing.

Models Used

A commercial transient simulator was used for all transient gas-lift simulations. Fig. VIII-2 shows a schematic of the model.

Well

PPPP

Annulus Tubing

Fig. VIII-2: Dynamic Model of Well Including Annulus

A well module was used for inflow from the reservoir. The IPR was matched to a commercial steady-state simulator model provided by the project team. Constant


pressure boundaries at the tubing head and casing head were used. The choke on the annulus branch was controlled to provide a constant gas flow rate. The gas-lift valve was modelled as a valve with ID of 20.6375 mm (0.8125”).

Using the constant pressure boundary for the gas injection provided for a proper stability analysis. The model also incorporated the effect of the gas-lift gas flowing down the annulus of the well.

A PVT package was used to simulate the production and gas-lift fluids. As no PVT data was given, the data used to characterize the PVT in the commercial steady-state simulator model was used. The PVT package was able to replicate the measured PVT to within a few percent. The gas-lift gas was modelled as a 0.7 gravity gas comprised of methane, ethane, and propane.

The profiles used for each well are given in Fig, VIII-3. These profiles were taken from the simulator models.

0

500

1000

1500

2000

2500

30000 1000 2000 3000 4000 5000 6000 7000

Horizontal Distance (m)

TVD

(m)

5.5" ERD and 7.0" ERD5.5" NONERD7.0" NONERD

Fig. VIII-3: Profile of each well

Note that the 14.0 cm and 17.8 cm (5.5 and 7 inch) ERD wells are highly deviated and step out nearly twice as far as the non-ERD wells. Table VIII-1 gives more detail for each of the cases.

Table VIII-1. Details of each case


Case WellsTubing OD

(in)Injection MD (m)

Injection Pressure (bara)

1 7” ERD 7 4941 110

2 7” ERD 7 6350 140

3 7” non-ERD 7 3508 110

4 7” non-ERD 7 4100 140

5 5.5” ERD 5.5 4878 110

6 5.5” ERD 5.5 6350 140

7 5.5” non-ERD 5.5 2698 110

8 5.5” non-ERD 5.5 3200 140

Comparison of the transient simulator and the steady-state simulators

Before the full array of simulations was performed, a comparison of three different programs was made to ensure that the transient simulator was suitable for gas-lift simulations. Predictions for the dynamic simulator were compared with steady-state predictions from steady-state simulators. Fig. VIII-4 shows the comparison for Case 5. The dynamic simulator predictions are within 5% of the steady-state simulator, which is reasonable.


9500

9700

9900

10100

10300

10500

10700

10900

11100

0 1 2 3 4 5 6 7 8

Gas Injection Rate (mmscf/d)

Oil

Rat

e (s

tb/d

)Simulator XSimulator YSimulator Z

5.5" ERD Well0% Watercut1595 psia Injection 232 psia THP2538 psia Pres

Fig. VIII-4: Comparison of Dynamic Simulator X and Steady-State Simulators Y and Z

Predictions from two steady-state simulators for Cases 1, 3, 5, and 7 at 0% water cut. Table VIII-2 shows the comparisons.

Table VIII-2. Comparison of Simulators X and Y for Cases 1, 3, 5, and 7 at 0% WC

Oil Rate (stb/d)

Gas Rate Case #1 Case #3 Case #5 Case #7

(mmscf/d) X Y X Y X Y X Y

0 16432 17125 18388 18487 10276 10850 13236 14298

1 16574 17351 18580 18604 10333 10916 13342 14370

2 - 17529 18725 18687 10314 10959 13401 14399

4 16713 17779 18898 18806 10190 10971 13422 14417

8 16586 17967 18916 18809 9793 10732 13252 14203


Differences between the two programs are expected due to: (1) slight differences in the PVT properties of the fluids and (2) different flow correlations used in the tubing and casing annulus. However, the two programs are fairly consistent with one another.

Results

Figures VIII-5 through VIII-12 show the predicted oil rate versus gas injection rate for each of the eight cases. Note that the shaded region in the plots represents regions of unstable or transient flow.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)

CASE #17" ERD Well110 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut

Simulator X - Solid LinesSimulator Y - Dashed Lines

Transient Flow

95% Watercut

80% Watercut

60% Watercut

Fig. VIII-5: Simulation results for Case 1


0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)CASE #27" ERD Well140 bar Injection16 bar THP175 bar Pres

0% Watercut

40% WatercutSimulator X Predictions

Transient Flow

95% Watercut

80% Watercut

60% Watercut


0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)

CASE #37" NONERD Well110 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut


95% Watercut

60% Watercut

80% Watercut



0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)CASE #47" NONERD Well140 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut

Simulator X Predictions

95% Watercut

60% Watercut

80% Watercut

Transient Flow


0

2000

4000

6000

8000

10000

12000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)

CASE #55.5" ERD Well110 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut

95% Watercut


60% Watercut

80% Watercut

Transient Flow



0

2000

4000

6000

8000

10000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)CASE #65.5" ERD Well140 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut

95% Watercut


60% Watercut

80% Watercut

Transient Flow


0

2000

4000

6000

8000

10000

12000

14000

16000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)

CASE #75.5" NONERD Well110 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut


95% Watercut

80% Watercut

60% Watercut

Transient Flow



0

2000

4000

6000

8000

10000

12000

14000

0 1 2 3 4 5 6 7 8 9


Oil

Rat

e (s

tb/d

)CASE #85.5" NONERD Well140 bar Injection16 bar THP175 bar Pres

0% Watercut

40% Watercut


95% Watercut

80% Watercut

60% Watercut

Transient Flow


For nearly all cases, the flow is predicted to be stable with the exception of water cuts greater than 80-90%. The injection pressure did not have a significant impact on the stability of the flow. However, since the injection depths were slightly deeper for the higher injection pressure cases, the flow was slightly more stable in the 110 bar (1,595 psia) injection pressure cases.

Flow Stability

Effect of Gas Injection Rate: For the majority of the cases, the results of the dynamic simulations show steady-state behavior quite similar to that of the steady-state simulator. However, at higher water cuts and lower gas injection rates, the dynamic simulator predicts the flow to be either unstable or transient whereas the steady-state simulator predicts the flow to be stable. Although this happens in many of the cases run, Case 5 at 95% water cut gives a more illustrative example of unstable flow. Table VIII-3 shows the dynamic and steady-state results for Case 5 at 95% watercut.


Table VIII-3. Comparison of Simulator X and Y for Case 5 at 95% WC (shaded cells are for transient flow)

X Y

Gas Rate Oil Rate Oil Rate

(mmscf/d) (stb/d) (stb/d)

0 0 0

1 0 132

2 85 219

4 271 319

8 358 383

Figures VIII-13 through VIII-15 show total liquid flow rates vs. time for 2, 4, and 8 mmscf/d.

0

5000

10000

15000

20000

25000

0 5000 10000 15000 20000 25000 30000 35000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

) Simulator XSimulator Y

CASE #55.5" ERD Well95% Watercut2 mmscf/d Gas Rate110 bar Injection16 bar THP175 bar Pres

Fig. VIII-13: Comparison of Simulator X and Y at 2 MMscf/d gas rate


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 5000 10000 15000 20000 25000 30000 35000 40000 45000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)

Simulator XSimulator Y



0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 5000 10000 15000 20000 25000 30000 35000 40000 45000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)

Simulator XSimulator Y




As can be seen, the steady-state simulator model predicts a steady liquid flow rate due to the nature of the program, whereas the dynamic simulator predicts the true transient behavior. In this case, severe slugging is expected at 2 MMscf/d with the slugging being partially mitigated by increasing the injection rate to 4 MMscf/d. Similar behavior is shown for several of the other cases which are highlighted as transient flow in Figures VIII-5-12 and Tables VIII-1-3.

Figures VIII-13 and VIII-14 give ample reason for using a transient multi-phase flow simulator as a final check on the stability of a gas-lift design.

Effect of Tubing Head Pressure: What follows is a description of the transient behavior via dynamic simulations due to changes in the tubing head pressure (4 MMscf/d injection rate and 95% water cut case). Fig. VIII-16 gives an overview of how the slug frequency and size changes with wellhead pressure (THP).

Intermittent SluggingRegion

Surging Region Severe SluggingRegion

OscillatingRegion

S-SRegion

0

0.2

0.4

0.6

0.8

1

0 5 10 15 20 25

Tubing Head Pressure (bar)

Slu

g F

requ

ency

(1/

hour

)

0

20

40

60

80

100

120

140

160

180

200

Slu

g S

ize

(stb

)Slug FrequencySlug Size

4 mmscf/d gas rate95% Watercut

Fig. VIII-16: Overview of Slug Frequency and Size versus THP

Transitioning from low to high tubing head pressure, the behavior of the flow starts as steady-state behavior and transitions to a surging flow (Fig. VIII-17a). At ~10 bar (150 psia) THP, the flow turns to an intermittent slugging, which then transitions to an oscillating flow (Fig. VIII-17b). The oscillating flow transitions to a severe slugging region beyond ~21 bar (310 psia) (Fig. VIII-17c).


0

2000

4000

6000

8000

10000

12000

14000

0 5000 10000 15000 20000 25000 30000 35000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)THP - 1 barTHP - 5.2 bar

Fig. VIII-17a: Rate versus time for THP of 1 and 5.2 bar


0

2000

4000

6000

8000

10000

12000

14000

0 5000 10000 15000 20000 25000 30000 35000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)

THP - 13.8 bar

THP - 18.6 bar

Fig. VIII-17b: Rate versus time for THP of 13.8 and 18.6 bar

0

2000

4000

6000

8000

10000

12000

14000

0 5000 10000 15000 20000 25000 30000 35000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)

THP - 20.7 bar

THP - 370 25.5

Fig. VIII-17c. Rate versus time for THP of 20.7 and 25.5 bar


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 5 10 15 20 25

Tubing Head Pressure (bar)

Liqu

id R

ate

(stb

/d)

Fig. VIII-18: Average Daily Liquid Rate versus Tubing Head Pressure

As expected, the average daily liquid rate reduces as tubing head pressure increases, as shown in Fig. VIII-18. However, only using by transient simulation tools can the actual dynamics of the system be investigated.


Effect of Orifice Port Size: Here is a plot showing the effect of orifice port size for the 95% water cut and 4 MMscf/d injection rate case (Fig, VIII-19). Note that, if not properly accounted for, the orifice port size could either restrict gas flow or cause unwanted transients in the well.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 5000 10000 15000 20000 25000 30000 35000 40000 45000

Time (s)

Tota

l Liq

uid

Rat

e (s

tb/d

)

0.25" Valve0.5" Valve1" Valve1.5" Valve


Fig. 19: Effect of Orifice Port Size on Flow Stability

The results given in Fig, VIII-19 show the importance of reviewing all production scenarios when designing a gas-lift system; including orifice port size.


10. References

This is a comprehensive bibliography or set of references for text books, papers, and magazine articles that describe use of dynamic simulation technology for gas-lift wells and systems, and for other related general production system applications such as wax, hydrates, and flow assurance. Some references are provided to help understand dynamic simulation.

A list of informative references is included after the bibliography.

Bibliography

1. Mantecon, J.C.: ”The Virtual Well: Guidelines for the Application of Dynamic Simulation to Optimize Well Operations, Life Cycle design and Production", SPE paper 109829, presented at the 2007 SPE Annual Technology Conference and Exhibition held in Anaheim, California, USA, 30-3 November 2007.

2. Lancy, M.F.: ”Dynamic Simulation of the Europa and Mars Expansion Projects: A New Approach to Coupled Subsea and Topsides Modelling”, SPE paper 56704, presented at the 1999 SPE Annual Technology Conference and Exhibition held in Houston, Texas, 3-6 October 1999.

3. Gayton, P.W., Miller, S.D., and Napalowski, R.: “Innovative Development Engineering Techniques”, SPE paper 65202, presented at the SPE European Petroleum Conference held in Paris, France, 24-25 October 2000.

4. Schoppa, W., Jayawardena, S., Agbaje, T., Ebere, D., and Iyer, S. “Bonga Flow Assurance Benchmarking via Field Surveillance”, OTC paper 18949, presented at the 2007 Offshore Technology Conference held in Houston, Texas, U.S.A., 30 April - 3 May 2007.

5. Zakarian, E, Larrey, D.: “A systematic Investigation of Girassol Deep Water Field Operational Data to Increase Confidence in Multiphase Simulation”, IPTC paper 11379, presented at the Internationl Petroleum Technology Conference held in Dubai, 4-6 Dec 2007.


6. Gudimetla, R., Carrol, A., Havre, K. and Canon, J.: ”Gulf of Mexico Field of The Future Subsea Flow Assurance”, OTC paper 18388, presented at Offshore Technology Conference held in Houston, Texas, U.S.A., 1-4 May 2006.

7. Costa, D., Vu, V-K, Barnay, G.C., Larrey, D., McClimans, O.T. and Sand, E.B.: “Investigation of a Subsea Separation Station Operating Envelope using Sub-surface to Topsides Integrated Dynamic Simulations”, OTC paper 18709, presented at Offshore Technology Conference held in Houston, Texas, 30 April-3 May 2007.

8. Bell, G.M., Chin, Y.D., and Hanrahan, S.: “State of Art of Ultra Deepwater Production Technologies”, OTC paper 17615, presented at Offshore Technology Conference held in Houston, Texas, USA, 2-5 May 2005.

9. Tagore, A., Utgard, M., Ramachandran, K., Alwazzan, A. and McDermott, J.R..: “Fluid Characterization: Impact on Deepwater Field Development”, SPE paper 115777, presented at the 2008 SPE Annual Technology Conference and Exhibition held in Denver, Colorado, USA, 21-24 September 2008.

10. Shi, H., Holmes, J., Aziz, K., Durlofsky, L., K., Diaz, L., Alkeya, B., and Oddie, G.: “Drift-Flux Modelling of Two Phase Flow in Wellbores”, SPE paper 84228, SPE Journal Vol 10 #1, March 2005.

11. Bendiksen, K. H. et al., “The Dynamic Two-Fluid Model OLGA: Theory and Application, SPE Production Engineering, May 1991.

12. Falcone, G., Teodoriu, C., Reinicke, K.M., Bello, O.O., and Clausthal, T.U.: “Multiphase Flow Modelling Based on Experimental testing: A comprehensive Overview of Research Facilities Worlwide and the need for Future Developments”, SPE paper 110116, presented at the 2007 SPE Annual Technology Conference and Exhibition held in Anaheim, California, USA, 30-3 November 2007.

13. Sturm, W.L., Belfroid, S.P.C., van Wolfswinkel, D., Peters, M., Verhelst, F.: “Dynamic Reservoir Well Interaction”, SPE paper 90108, presented at SPE Annual Technical Conference and Exhibition held in Houston, Texas, U.S.A., 26-29 September 2004.

14. Sagen, J., Sira, T., Ek, A., Selberg, S., Chaib, M. and Eidsmoen, H.: “A Coupled Dynamic Reservoir and Pipeline Model – Development and Initial Experience”, 13 th

International Multiphase Conference on Multiphase Production Technology 07’, Edinburg, UK, 13-15 June, 2007.

15. Hu, B., Sagen. G., Chupin, G., Haugset, T., Arild, E., Sommersel, T., Xu, Z., and Mantecon, J.: “Integrated Wellbore-Reservoir Dynamic Simulation: SPE paper 109162, presented at the 2007 SPE Asia Pacific Oil & Gas Conference and Exhibition held in Jakarta, Indonesia, 30 Oct -1 Nov 2007.

16. Ballard, A.L., Adeyeye, D., Litvak, M., Wang, C.H., and Stein, M.H., Cecil, D. and Dotson, B.D.: “Predicting Highly Unstable Tight Gas Well Performance”, SPE paper


96256, presented at the 2005 SPE annual Technology Conference and Exhibition held in Dallas, Texas, U.S.A., 9-12 October 2005.

17. Kerem, M., Proot, M. and Oudeman, P.: “Analyzing Underperformance of Tortuous Horizontal Wells: Validation with Field Data”, SPE paper 102678, presented at the 2006 SPE Annual Technical Conference and Exhibition held in San Antonio, Texas, 24-27 September 2006.

18. Meng, W., Zhang, J.J., and Brown, R.J.: “Modelling and Mitigation of Severe Riser Slugging: A Case Study”, SPE paper 71564, presented at the 2001 SPE Annual Technology Conference and Exhibition held in Louisiana, New Orleans, 30 Sep – 3 October 2001.

19. Ascencio-Cendejas, F., Reyes-Venegas, O. and Nass, M.A.: “Thermal Design of Wells Producing Highly Viscous Oils in Offshore Fields in the Gulf of Mexico”, SPE paper 103903, presented at the First International Oil Conference and Exhibition in Mexico held in Cancun, 31 August – 2 September 2006.

20. Tang Y., and Huang, W.: “A Combined Well Completion and Flow Dynamic Modeling for a Dual-Lateral Well Load-up Investigation”, paper IPTC 11332, at the International Petroleum Technology Conference held in Dubai, U.A.E., 4–6 December 2007.

21. Leemhuis, A., Nennie, E., Belfroid, S., Alberts, G., Peters E., and Joosten, G.: “Gas Conning Control for Smart Wells Using a Dymanic Coupled Well-Resevoir Simulator”, SPE paper 112234, presented at the 2008 Intelligent Energy Conference and Exhibition held in Amsterdam, 25-27 Feb 2008.

22. Duncan, G.J. and Beldring, B.: “A Novel Approach to Gas-Lift Design for 40,000 BPD Subsea Producers”, SPE paper 77727, presented at the SPE Annual Technology Conference and Exhibition held in San Antonio, Texas, 29 September – 2 October 2002.

23. Eikrem, G.O., Foss, B., Imsland, L., Hu, B. And Golan, M.: “Stabilization of Gas-Lifted Wells”, Proceedings of the 15th IFAC World Congress on Automatic Control, Barcelona, Spain, 2002

24. Gaspari, E.F., Oliveira, G.P., Monteiro, M.R., and Dourado, R.J.: “Evaluating Transient Multiphase Model Performance for the Brazilian Offshore Environment”, OTC paper 17956, presented 2006 Offshore Technology Conference held in Houston, Texas, U.S.A., 1-4 May 2006.

25. Hu, B. and Golan, M.: “Gas-lift Instability Resulted Production Loss and Its Remedy by Feedback Control: Dynamic Simulation Results”, SPE paper 84917, presented at the SPE International Improved Oil Recovery Conference in Asia Pacific held in Kuala Lumpur, Malaysia, 20-21 October 2003.


26. Hu, B. and Golan, M.: “Occurrence of Density Wave Instability in Gas-Lifted Wells”, 4th North American Conference on Multiphase Technology, Banff, Canada, 3-4 June 2004.

27. Mantecon, J.C., Andersen, I., Freeman, D. and Adams, M.: “Impact of Dynamic Simulation on Establishing Watercut Limits for Well Kick-off”, SPE paper 88543, presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition held in Perth, Australia, 18-20 October 2004.

28. Øverland, A.M. and Ramstad, H.J.: “Yme Marginal Field, 12 Km Subsea Gas-Lift Experience”, SPE paper 71539, presented at the SPE Annual Technology Conference and Exhibition held in New Orleans, U.S.A., 30 September – 3 October 2001.

29. Song, S., and Peoples, K.: “Impacts Of Transient Analysis on Kuito Production Operations”, OTC paper 15186, presented 2003 Offshore Technology Conference held in Houston, Texas, U.S.A., 5-8 May 2003.

30. Tang, Y., Schmidt, Z., Blais, R.N., Doty, D.R.: “Transient Dynamic Characteristics of the Gas-Lift Unloading Process”, SPE Journal, (Sep. 1999), 268-278.

31. Tang, Y.: “A New Method of Plunger Lift Dynamic Analysis and Optimal Design for Gas Well Deliquification”, paper SPE 116764, presented at the 2008 SPE Annual Technical Conference and Exhibition held in Denver, Colorado, U.S.A., 21-24 September 2008

32. Veeken, K., Hu, B., and Schiferli, W.: “Multiphase Flow Modelling of Liquid Loading”, presented at the Gas Well Deliquification Workshop, Denver, Colorado, 23-26 February 2009.

33. Veeken, K., Hu, B., and Schiferli, W.: “Transient Multiphase Flow Modeling of Gas Well Liquid Loading”, paper SPE 123357, presented at the 2009 SPE Annual Offshore Europe Oil & Gas Conference and Exhibition held in Aberdeen, U.K., 8–11 September 2009.

34. Tang Y., Wolff, M., Condon, P., and Ogden, K.: “A Dynamic Wellbore Modeling for Sinusoidal Horizontal Well Performance With High Water Cut”, paper SPE 109262, presented at the 2007 SPE Annual Technical Conference and Exhibition held in Anaheim, California, U.S.A., 11–14 November 2007.

35. Noonan, S.G., Kendrick, M.A., Matthews, P.N., Sebastiao, N., Ayling, I. and Wilson, B.L.: “Impact of Transient Flow Conditions on Electric Submersible Pumps in Sinusoidal Well Profiles: A Case Study”, SPE paper 84234, presented at the SPE Annual Technical Conference and Exhibition held in Denver, Colorado, U.S.A., 5-8 October 2003.

http://www.spe.org/elibrary/servlet/spepreview?id=SPE-109262-MS&soc=SPE&speAppNameCookie=ELIBRARY






http://www.spe.org/elibrary/servlet/spepreview?id=00057659&speCommonAppContext=ELIBRARY

http://www.spe.org/elibrary/servlet/spepreview?id=00057659&speCommonAppContext=ELIBRARY


36. Barrett, N. and King, D.: “Oil/Water Slugging of Horizontal Wells – Symptom, Cause and Design”, SPE paper 49160, presented at the 1998 SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, 27-30 September 1998.

37. Sisco, R., Kirby, M.: “Chemical Distribution During Normal and Transient Conditions”, IPTC paper 10706, presented at the International Petroleum Technology Conference held in Doha, Qatar, 21-23 Nov 2005.

38. Harun, A.F., Krawietz, T.E. and Erdogmus, M.: “Hydrate Remediation in Deepwater Gulf of Mexico Dry-Tree Wells: Lessons Learned”, OTC paper 17814, presented at the 2006 Offshore Technology Conference held in Houston, Texas, U.S.A., 1-4 May 2006.

39. Harun, A.F., Krawietz, T.E. and Erdogmus, M.: “Transient Simulation Assist Hydrate Remediation Efforts in Deepwater Gulf of Mexico Dry-Tree Wells”, SPE paper 100750, presented at the 2006 SPE Asia Pacific Oil & Gas Conference and Exhibition held in Adelaide, Australia, 11-13 September 2006.

40. Lunde, G.G., Vannes, K., McClimans, O.T., Burns, C., and Wittmeyer, K.: “Advanced Flow Assurance System for The Ormen Lange Subsea Gas Development”, OTC paper 20084, presented at the 2009 Offshore Technology Conference held in Houston, Texas, U.S.A., 4-7 May 2009.

41. Teng, D., Maloney, B. and Mantecon, J.C.: “Well Testing by Design: Transient Modelling for Predicting Behaviour in Extreme Wells”, SPE paper 101872, presented at the 2006 SPE Asia Pacific Oil & Gas Conference and Exhibition held in Adelaide, Australia, 11-13 September 2006.

42. Harun, A.F.:”Planning and Executing Lost Distance Subsea Tie-back Oil Well Testing”, IPTC paper 1193, presented at 2007 International Petroleum Technology Conference, Dubai, 4-6 December, 2007.

43. Mantecon, J.C., and Hollams, R.R.F.:”Use of Dynamic Simulation to Refine Well Testing Procedures and Optimize The Data Required for Deconvolution Techniques”. OTC paper 19767, presented at the 2009 Offshore Technology Conference held in Houston, Texas, U.S.A., 4-7 May 2009.

44. Hu, B., Uv, E.H., and Xu, Z.G.:”Modelling and Simulation of Co-flow of Reservoir Fluids and Drilling/Completion Mud in The Ultra-Long Multilateral Horizontal Wellbores”, presented at the 14th International Conference Multiphase Production Technology, Cannes, France, 17-19 June 2009.

45. Rygg, O.R., Friedemann, J.D. and Nossen, Jan: “Advanced Well Flow Model Used for Production, Drilling and Well Control Applications”, 1996 IADC Well Control Conference for Europe, Aberdeen, 22-24 May, 1996.


46. Rygg, O.R.: “The Necessity of Modelling in Contingency Planning and Emergency Well Control Response”, 2005 IADC International Well Control Conference & Exhibition, Singapore, 8-9 November, 2005.

47. Harun, A.F., Fung, G. and Erdogmus, M.: “Experience in AA-LDHI Usage for a Deepwater Gulf of Mexico Dry-Tree Oil Well: Pushing the Technology Limit”, SPE paper 100796, presented at the 2006 SPE Asia Pacific Oil & Gas Conference and Exhibition held in Adelaide, Australia, 11-13 September 2006.

48. Dalsom, M., Halvorsen, E. and Slupphaug, O.: ”Active Feedback Control of Unstable Wells at the Brage Field”, SPE paper 77650, presented at the SPE Annual Technology Conference and Exhibition held in San Antonio, Texas, 29 September – 2 October 2002.

49. Jansen, B., Dalsmo, M., Nøkleberg, L., Havre, K., Kristiansen, V. and Lemetayer, P.: ”Automatic Control of Unstable Gas-Lifted Wells”, SPE paper 56832, presented at the 1999 SPE Annual Technology Conference and Exhibition held in Houston, Texas, 3-6 October 1999.

50. Krogh, E., Mjaaland, S., Sletfjerding, E.: “Dynamic Flow Simulation of Well Clean-up Operation at the Asgard Field”, SPE paper 124653, presented at the 2009 SPE Annual Technology Conference and Exhibition held in New Orleans, USA, 4-7 October 2009.

51. Davis, S., Boxall, J., Koh, C., Sloan, E., Hemmingsen, P., Kinnari, K., and Xu, G.: ”Predicting Hydrate Plug Formation in a Subsea Tieback”, SPE paper 115763, presented at the 2008 SPE Annual Technology Conference and Exhibition held in Denver, USA, 21-24 September 2008.

52. Salman, Y., Wittfeld, C., Lee, A., Yick, C., and Derkinderen, W.: “Use of Dynamic Simulation To Assist Commissioning and Operating a 65-Km Subsea-Tieback Gas-lift System”, SPE paper 121187, published in the SPE Production & Operations magazine, November 2009.

53. Acuna, H.G., Schmidt, Z.X., Doty, D.R. “Modelling of Gas Rates Through 1”, Nitrogen-Charged Gas-Lift Valves”, SPE Annual Technology Conference and Exhibition held in Washington D.C., USA, 4-7 October 1992.

54. Decker, K. “Gas-Lift Valve Performance Testing,” SPE 21636, SPE Production Operations Symposium, 21-23 March 1993, Oklahoma City, Oklahoma.


Informative References

API RP 11V5 Operation, Maintenance and Troubleshooting of Gas Lift Installations

API RP 11V6 Design of Continuous Flow Gas Lift Installations Using Injection Pressure Operated Valves

API RP 11V8 Gas Lift Systems Design and Performance Predictions

API RP 19G9 Operation, Maintenance and Troubleshooting and Design/Re-Design of Dual Gas Lift Systems

API RP 11V10Design of Intermittent and Chamber Gas Lift Wells and Systems

ISO 17078-1 Petroleum and natural gas industries -- Drilling and production equipment -- Part 1: Side-pocket mandrels

ISO 17078-2 Petroleum and natural gas industries -- Drilling and production equipment -- Part 2: Flow-control devices for side-pocket mandrels

ISO 17078-3 Petroleum and natural gas industries -- Drilling and production equipment -- Part 3: Running tools, pulling tools and kick-over tools and latches for side-pocket mandrels

ISO 17078-4 Petroleum and natural gas industries -- Drilling and production equipment -- Part 4: Practices for side pocket mandrels and related equipment

master copy of the document

Documents