advanced flow assurance

8/11/2019 Advanced Flow Assurance

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Flow Assurance Master ClassNihl Gler-Quadir, PhD

Principal Consultant, EICE International Inc.


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1

What is Flow Assurance?

Operational Safety

Environmental Footprint

Appraisal

Conceptual

FEED

Detailed

Design

Remediation

Surveillance

Diagnostics

Monitoring

Operations

Planning

Design

Control

Operations

Optimization

Hydrate InhibitionWax Suppression

Emulsification

Corrosion

Drag Reduction

Water Treatment

Asphaltene Inhibition

Radial ConductionFree Convection

Forced Convection

Annulus Radiation

Wellbore Heating

Pipeline Cooldown

Transient Analysis

Black Oil ModelingVapor-Liquid Equilibria

PVT Analysis

Hydrate Prediction

Wax Deposition

Asphaltene

Water Analysis

Reservoir InflowNodal Analysis

Artificial Lift

Pressure Maintenance

Integrated Asset Model

Well Testing

Well Completion

Multiphase FlowPipeline Network

Heavy Oil

Steam Injection

CO2Sequestration

LNG & NGL Lines

Transient Analysis

Economic Justification

Heat TransferFluid Flow Fluid Properties Chemical Treatment Integrated Analysis

Maintain

production

reliably,

economicallyand safely

from sandface

to processing

facilities


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2

0

2000

4000

6000

8000

10000

12000

14000

0 50 100 150 200 250

Temperature(F)

Pressure(psi)

Reservoir

Platform

Hydrate

Asphaltene

Wax

Bubble Point

Chemicals

Heating

Insulation

WELLBORE

PIPELINE

RISER

The Challenge of Flow Assurance

Boosting

Operational Goals

Ensure uninterrupted flow 24x7x365 at target rates

Avoid operating in hydrate region for extended periods

Control wax deposition in pipeline

Limit asphaltene precipitation in well

Manage impact of slugs on processing facilities

Design Objectives

Adequate throughput capacity for life of field production

Ability to monitor entire system from sandface to platform

Infrastructure in place to respond operationally


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3

Day 3 - Integrated Workflows

H. Integrated Flow Assurance Analysis

Combining fluid flow, heat transfer and

thermodynamics

Deepwater/subsea systems

Heavy oil transport

Drag reduction

Monitoring and control

I. Integrated Production Analysis

The economics of flow assuranceReservoir declinehow it impacts production

Introduction to artificial lift methods

Integrated asset modelingreservoir,

production, process plant, economics

J. Flow Assurance Considerations in

Conceptual Design & Operations

A hands-on session where participants will

learn to apply the concepts discussed in the

preceding sessions in a practical example

involving the creation of a field developmentplan for a hypothetical asset with particular

emphasis on the impact of flow assurance

issues on the overall design and operation.

Day 2Applying Flow Assurance

D. Thermodynamics

Single phase propertiesoil, gas and water

Black oil and empirical models

Compositional PVT analysis

Hydrates, wax and asphaltenes prediction

Scales

E. Transport Properties

Viscosity prediction methods

Oil-water viscosityemulsionsOther fluid properties

F. Heat Transfer Analysis

conduction, convection and radiation

Heat transfer through composite layers

Wellbore heat transfer

Pipeline heat transfer

Wellbore and pipeline heating

G. Transient Phenomena

Basic principles of single phase transient

flow

Multiphase flow transients

Pipeline startup, shut-in and blowdown

Terrain induced slugging

Day 1Basics of Flow Assurance

Introduction

Introductions

What is Flow Assurance

The Challenge (Operations and Design)

Course Overview

A. Fundamentals of Fluid Flow

Single phase flow

One-dimensional momentum balance equationThe concept of friction factor

Pipeline transmission applications

B. Multiphase Flow Fundamentals

Basic multiphase flow concepts

Flow patterns, holdup and pressure drop

Horizontal and near-horizontal flow

Vertical, inclined and downward flow

C. Multiphase Phenomena in Flow Assurance

Modeling multiphase flow behaviorThree-phase oil-gas-water flow

Impact of multiphase flow on corrosion / erosion

Hydrodynamic slugging

Course Outline


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4

Single phase flow

One-dimensional momentum balance equation

The concept of roughness and its influence on friction factor

Pipeline transmission applications

A. Fluid Flow Fundamentals


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5

Single Phase Flow

Type of Pipeline Primary Operating Consideration

Gas Gathering System Condensate, Water, Network

Gas Transmission Throughput, Compression

Gas Distribution Low Pressure Network

Refined Products Batch Movement

Heavy Oil Viscosity

Volatile Hydrocarbon PVT behavior

Hydraulics

analyze flow and predict pressure from fluid behavior Heat Transfer

analyze and predict temperature behavior

Thermodynamics

how pressure and temperature impact fluid behavior

Key Flow Assurance Issues


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Momentum Balance

Potential Energy at A

+ Kinetic Energy at A

From the Law of Energy Conservation:

Potential Energy at B

+ Kinetic Energy at B

- Friction Loss in

Pipe =

B

A

Total Pressure Gradient =

Pressure Gradient due to Friction (Frictional Loss)

+ Pressure Gradient due to Elevation (Potential Energy)

+ Pressure Gradient due to Velocity Change (Kinetic Energy)

where (with appropriate units):

frictional gradient = - f v |v| / (2 gc D)elevation gradient = - g/ gc. Sin kinetic energy gradient = - v . dv/dL

is relatively small and generally ignored

(except for high velocity gradients, e.g. flare lines)

L


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Friction Factor

How to determine the friction factor term f in the frictional gradient:

frictional gradient = - f v |v| / (2 gc D)

dimensionless Reynolds number:

Re= v D / (6.72E-4 * )

Note: multiplier is to convert viscosity from cp to lb/sec/ft

Moody Chart: f = f(Re,/D)

. Laminar Flow Region: 0 < Re

< 2300

f = 64 / Re

Turbulent Flow Region: Re > 4000 Colebrook-White Equation:

f = 1 /(1.742 log (2 /D) + 18.7 / Re f0.5)2

relative roughness = /D

Jains eqn:1/(f1/2) = 1.14-2 log(e/d+21.25/Re0.9)

Class Question: How do we handle the transition?

2300< Re < 4000


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Example A2Friction Factor

Find the friction factor in a 12-inch gas transmission pipeline, given the following

data: v = 25 ft/sec, D = 12 inch, = 0.0018 inch, = 5 lb/ft3

, = 0.01 cp

Alternate Numerical Method (Colebrook-White)

1) Set f= 0.015 as initial estimate for friction factor2) Update f for next iteration from Colebrook-White equation:

f = 1 /(1.742 log (2 /D) + 18.7 / Re f0.5)2

= 1 / (1.742 log (2 x 0.00015) + 18.7 / 18601190 x 0.0185)2= 0.01302455

3) Repeat previous step with f= 0.013024554) Converge until error within tolerance (3 iterations, f=0.01302956)

1) Relative roughness /D = 0.0018 / 12 = 0.000152) Reynolds number Re= v (D/12) / (6.72E-4 x )

= 25 x (12/12) x 5 / (6.72E-4 x 0.01) = 18,601,190

3) From Moody chart, friction factor f = 0.015(estimate)

Note: Colebrook-White generally converges within 2-3 iterations


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Example A3Transition Zone Friction Factor

Determinethe friction factor for a 12-inch heavy oil pipeline, given

the following :v = 1 ft/sec, D = 12 inch, = 0.0018 inch, = 60 lb/ft^3, = 30 cp

1) Relative roughness /D = 0.0018 / 12 = 0.00015

1) Reynolds number Re= v D / (6.72E-4 x )= 1 x (12/12) x 60 / (6.72E-4 x 30) = 2976 (transition)

2) From laminar flow model, friction factor f = 64 / Re = 0.021504

1) From Colebrook-White (or Moody chart), turbulent friction factor = 0.0438

2) From interpolation, weighted friction factor at transition = 0.03039

Note: Pipe roughnesshas minimal impact in transition zone


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Symbol Definition

f Friction factor

Density (lb/ft^3)

v Velocity (ft/sec)

gc Conversion factor (32.2 lbf-sec^2/lb-ft)

g Acceleration due to gravity (ft/sec 2)

D Pipe internal diameter (inch)

L Pipe length (ft)

dv/dL Velocity gradient (ft/sec^2)

P Pressure (psi)

dP/dL Pressure gradient (psi/ft)

Absolute viscosity (cp)

Absolute roughness (inch)

Re Reynolds number

Terminology


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Basic multiphase flow concepts

Flow patterns, holdup and pressure drop

Horizontal and near-horizontal flow

Vertical, inclined and downward flow

B. Multiphase Flow Fundamentals


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Basic Concepts of Two-Phase Flow

VGVL

Diamete

r

hLAL

AG

Liquid Phase (with Gas Bubbles)

Gas Phase (with Liquid Entrainment)

Holdup HL= AL/ (AL + AG)Slippage = vG - vL

New concept of holdup HL as the volumetric liquid phase fraction and HL ns as the no-slipholdup

HL ns = qL / (qL + qG) where qL and qG the phase volumetric flow rates at in situ conditions

Significant slippage between phases (gas is faster, except for downhill flow)

HL> HL ns

Frictional pressure gradient much higher (due to interfacial shear i)

Velocity of wave propagation is orders of magnitude slower Distribution of phases based on prevailing flow pattern (dependent on geometry, in si tu rates,

fluid properties)

Concept of superficial phase velocities:

vSL = qL / Area of Pipe = vL x HL

vSG = qG / Area of Pipe = vG x (1 - HL)

and Mixture Velocity, vm = vSL + vSG

ii

Extending Single Phase Flow:

wG

wL


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Example B1: Multiphase Flow Parameters

Area = D2/ 4 = (3.14) x ( 3/12)2/4= 0.049 ft2

QL = 1000 BPD x 5.615 (ft3/bbl) / 86400 (sec/day) = 0.065 ft3/sec @ Std conditions

Assuming incompressible liquid, qL= QL= 0.065 ft3/sec

QG= 1000 BPD x 1000 (SCF/bbl) / 86400 (sec/day) = 11.574 ft/sec @ Std conditions

qG= QGx Pstd/ (P/z) x (T + 460) / (Tstd+ 460)

= 11.574 x (14.7 / (147/0.9)) x (460+100) / 520 = 1.122 ft3/sec

vSL= qL/ Area = 0.065 / 0.049 = 1.3 ft/sec

vSG

= qG

/ Area = 1.122 / 0.049 = 17.3 ft/sec

HL ns = qL / (qL + qG) = 0.065 / (0.065 + 1.122) = 0.055

vL= vSL/ HL= 1.3 / 0.25 = 5.3 ft/sec

vG= vSG/ (1HL) = 17.3 / 0.75 = 23 ft/sec

Slip = vGvL = 17.7 ft/sec

Given an average holdup of 0.25, predict all relevant multiphase flow parameters

in a horizontal 3-inch ID flowline operating at a pressure of 147 psia and 100 deg

F producing 1000 BPD at a GOR of 1000 SCF/BBL. Use an averagecompressibility factor of 0.9 and assume that none of the gas is in solution.


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Horizontal Flow Stratified (both Smooth and Wavy)

Intermittent (Elongated Bubble and Slug) Dispersed Bubble

Annular

Vertical Flow Bubble (Bubbly and Dispersed Bubble)

Intermittent (Slug & Churn) Annular

Inclined Flow Upward Inclination (see Vertical Flow)

Downward Inclination (see Horizontal Flow)

Multiphase Flow Patterns

Flow pattern boundaries may vary significantly with even slight changes in inclinationangle. As such, empirical horizontal and vertical pattern maps are not suitable for

predicting flow patterns in a pipe or wellbore where the inclination deviates by even a few

degrees from vertical/horizontal. Computer-generated mechanistic models that rigorously

account for inclination (e.g. Barnea et al) are more appropriate for such predictions.


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Horizontal Flow Patterns

Stratified Flow at low flow rates the liquid and gas separated due to gravity

at low gas velocities the liquid surface is smooth, (stratified

smooth)

at higher gas velocities, the liquid surface becomes wavy,(stratified wavy, or wavy flow)

some liquid droplets might form in the gas phase.

Annular Flow at high rates in gas dominated systems

part of the liquid flows as a film around the pipe circumference

the gas and remainder of the liquid (entrained droplets) flow in the

center

of the pipe.

the liquid film thickness asymmetric due to gravity also called asannular-mist or mist flow..

Dispersed Bubble Flow

at high rates in liquid dominated systems the flow is a frothy mixture of liquid and entrained gas bubbles

flow is steady with few oscillations.

also called as froth or bubble flow.

Slug Flow at moderate gas and liquid velocities

alternating slugs of liquid and gas bubbles flow through the

pipeline.

Possible vibration problems, increased corrosion, anddownstream equipment problems due to its unsteady behavior.

Mandhane Map(Empirical)

Bubble,

Elongated

Bubble

Flow

Slug

Flow

Stratified Flow

DispersedFlow

SUPER

FICIALLIQUIDVELOCITYVSL,FT/SEC

SUPERFICIAL GAS VELOCITY VSG, FT/SEC

Wav

e

Flo

w

Annular,

AnnularMist

Flow


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Vertical Flow Patterns

Taitel-Dukler-Barnea Model(Mechanistic)

Superficial Gas Velocity (m/s2)Superficial Liquid Velocity (m/s2)

Supe

rficialLiquidVelocity(m/s2)

Superficial Liquid Velocity (m/s2)

DISPERSED BUBBLE

BARNEA

TRANSITONBUBBLY

SLUG OR CHURN

ANNULAR

Vertical Pipe Flow Patterns

BUBBLE

FLOW

ANNULAR

FLOW

SLUG

FLOW

CHURN

FLOW

Well Flow


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Example B2: Predicting Flow Pattern

Procedure:

From inclination angle, determine appropriate prediction map to use

Estimate in situ rates from standard production rates

Compute superficial phase velocities Predict flow pattern from map

Area = 3.14 x (3 /12) 2/4 = 0.049 ft2

Assuming incompressible liquid

qL = 1000 BPD x 5.615 (ft3/bbl) / 86400 (sec/day) = 0.065 ft3/sec

qG= 1000 BPD x 1000 (SCF/bbl) / 86400 (sec/day) x(14.7 / (147/0.9)) x (460+100) / 520 = 1.122 ft3/sec

vSL= qL/ Area = 0.065 / 0.049 = 1.122 ft/sec

vSG= qG/ Area = 1.122 / 0.049 = 17.261 ft/sec

From Mandhane map (horizontal), flow pattern = SLUG

Find the prevailing multiphase flow pattern in a horizontal 3-inch ID flowline

operating at a pressure of 147 psia and 100 deg F producing 1000 BPD at a GORof 1000 SCF/BBL. Use an average compressibility factor of 0.9 and assume that

none of the gas is in solution.


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Pressure Gradient in Two-Phase Flow

Total Pressure Gradient =Pressure Gradient due to Friction (Frictional Loss)

+ Pressure Gradient due to Elevation (Potential Energy)

+ Pressure Gradient due to Velocity Change (Kinetic Energy)

where:

frictional gradient = - fTP

TP

vTP

|vTP

| / (2 gc

D)

elevation gradient = - sg/ gc. Sin kinetic energy gradient = - TPvTP. dvTP/dL

The new two-phase flow terms introduced are:

slip-weighted mixture density (based on holdup correlation):

s= L . HL+ (1HL) Gtwo-phase density, friction factor and velocity:

TP, fTP, vTPwhich are all dependent on the pressure dropcalculation method (correlation)


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Multiphase Flow Correlations(from Chevron Pipeline Design Manual)

Pressure Drop Near Horizontal

Low GOR - Beggs & Brill

Gas/Condensate

High VelocityEaton-Oliemans

Low VelocityNone

Near Vertical

Gas/CondensateGray, Hagedorn & Brown

Gas/Oil - Hagedorn & Brown

Inclined Up - Beggs & Brill (fair)

Inclined/Vertical DownNone (Beggs & Brill with caution)

Liquid Holdup Near Horizontal

Low GOR - Beggs and Brill

Gas/Condensate none (Eaton better than

others)

Near Vertical

Gas/Condensateno slip

Gas/Oil - Hagedorn and Brown

Inclined Up Low GOR - Beggs and Brill

Gas/Condensate

High Velocitynone (use no slip)

Other none (use Beggs & Brill with

caution)

Inclined/Vertical Downnone (Beggs & Brill with caution)

Flow Patterns Near Horizontal Taitel-Dukler (except Dispersed-Bubble

boundary where a fixed VSL= 10 ft/sec is recommended) Near VerticalTaitel-Dukler-Barnea

Recommendations

General Modeling Guidelines

Liquid holdup accuracy requires detailed pipeline elevation profile

Flow pattern-dependent mechanistic analysis is required for

accurate holdup prediction

Pressure profile is dependent on holdup accuracy (elevationgradient)

Kinetic energy losses generally negligible (except low

pressure/high velocity)

Choice of correlation should be based on a range of factors

including geometry, fluid characteristics and f ield history

Mechanistic correlations (OLGAS, Tulsa) generally scale up better

Rigorous 3-phase analysis may be required for low velocity flowwith significant water cut


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Symbol Definition

VL , VG Phase velocities (ft/sec)

VSL , VSG Superficial phase velocities (ft/sec)

HL Liquid Holdup

HL ns No slip holdup

qL, qG in situ volumetric flow rates (ft3/sec)

i, wL,wG Shear at interface / pipe wall (psi/ft)

hL Height of liquid level

AL , AG Cross-sectional area for phase

Terminology

Subscript Definition

L, G, O, W Liquid, Gas, Oil, Water

i, w Interface, wall

std Standard conditions (60F, 14.7 psia)

TP Two-phase

ns No slip

m mixture


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Modeling multiphase flow behavior

Three-phase oil-gas-water flow

Impact of multiphase flow on corrosion / erosion

Slugging phenomena

C. Multiphase Phenomena in Flow Assurance


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All flow correlation employ a 3-step approach

Establish Flow Pattern

Determine Holdup

Calculate Pressure Drop

Empirical vs. Mechanistic correlations

Empirical correlations are primarily regression-based Mechanistic models are based on physics + data

To model flow behavior in a pipe (or well)

Input Data

pipe geometry (diameter, length, elevation profile)

Fluid characteristics (oil, gas & water gravities)

Phase ratios (water cut, GOR)

Specified boundary conditions may be:

Pressure at inlet and Flow Rate at Outlet Pressure at both ends

Flow Rate at Inlet and Pressure at Outlet

Calculation Procedure is Sequential and Iterative

Pipe divided into Segments

Temperature traverse calculations in parallel

Fluid properties (e.g. density, viscosity at every segment)

Results: pressure, holdup, flow pattern, temperature and phase properties at every

pipe segment Network models (e.g. gathering system) are significantly more complex

Modeling Multiphase Flow Behavior

HLP T FP

Inlet Data:Temperature, Fluid Characterization

Pressure or Flow Rate Boundary

Outlet Data:Pressure or Flow Rate Boundary

HLP T FP HLP T FP HLP T FPHLP T FPHLP T FPHLP T FP HLP T FP

1 2 3 4 5 6 7 8

Distance Along Pipeline, X

Pressure

Temperature

Holdup


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Common Uncertainties:

Flow pattern boundaries are not fully understood (and blurry) Holdup predictions do not scale up well for large diameter pipes

Pressure drop error could be as high as 20 percent

Errors greater for rough terrain, extreme velocities (high or low)

Uncertainties in Multiphase Flow Modeling

What Can be Done:

Define elevation profile in as much detail as possible Define fluid accurately

use measurements (where available), e.g. bubble point, viscosity

Use correlations as appropriate for the situation (pipeline geometry, field

history, applicability)

Validate, validate, validate

leverage available data and past history to adjust model

A

B

Path 1

Path 2

Why will the computed pressure drop for Path 2 ALWAYS be greater?


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Three-Phase Flow Analysis

Holdup HL= AL/ (AL + AG)Slippage = VG - VL

VG

VL

hLCombined Oil + Water Liquid Phase (with Gas Bubbles)

Gas Phase (with Liquid Entrainment)

ii

wL

Rigorous 3-phase flow analysis is an order of magnitude more complex

Most analysis methods tend to lump oil and water into a common

homogeneous liquid phase with no slippage between oil and water

When segregation does occur, water fraction in the liquid phase

Note: When segregation occurs, the water fraction in the liquid phase may

be several times higher than the water cut of the produced fluid. Why?

Two-Phase Flow

Rigorous Three-Phase Flow

wG

VG

VO Oil Phase (with Gas Bubbles and Entrained Water Droplets)

Gas Phase (with Oil and Water Entrainment)

Holdup HL= AL/ (AL +

AG)Water Fraction HLW= AOW/ AL

Slippage (gas-oil) = VGVO

Slippage (oil-water) = VO - VW

i

i

wG

wLWater Phase (with Gas Bubbles and Entrained Oil Droplets)VW

IWIW


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Example C1: Three-Phase Flow

From Example B1 (two-phase)

HL = 0.25

Pipe Area = 0.049 ftt2qL= 0.065 ft

3/sec

qG= 1.122 ft3/sec

vSG= qG / Area = 1.122 / 0.049 = 17.3 ft/sec

HL ns = qL / (qL + qG) = 0.065 / (0.065 + 1.122) = 0.055

VG= VSG/ (1HL) = 17.3 / 0.75 = 23 ft/sec

With Oil-Water Segregation:

Water Cut, FW= 0.10

Water Fraction HLW= 0.40

vSO= qL * (1 - FW) / Area = 0.065 * 0.9 / 0.049 = 1.19 ft/sec

vSW= qL * FW/ Area = 0.065 * 0.1 / 0.049 = 0.13 ft/sec

VO= VSO/ HL/ (1-HLW) = 1.19 / 0.25 / 0.6 = 7.95 ft/sec

VW= VSW/ HL/ HLW= 0.13 / 0.25 / 0.4 = 1.32 ft/sec

Slip G-O= VGVO = 15.1 ft/sec

Slip O-W= VOVW = 6.62 ft/sec

Example B1: Given an average holdup of 0.25, predict all relevant multiphase

flow parameters in a horizontal 3-inch ID flowline operating at a pressure of 147

psia and 100 deg F producing 1000 BPD at a GOR of 1000 SCF/BBL. Use anaverage compressibility factor of 0.9 and assume that none of the gas is in

solution.

Extend your original analysis (in Example B1) to the three-phase flow scenario where there is segregation

between oil and water, assuming a produced water cut of 10 percent and the volumetric fraction of the water

being 40 percent of the total liquid phase.


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Corrosion risk is higher when:

Produced gas is sour (definition: partial pressure of H2S and CO

2> 0.05)

> 0.5 percent mole fraction for 1000 psi system pressure

Water volume is high

Water velocity is low

Low lying areas of water accumulation are at highest risk

Flow regime dependency

Stratified Flowcorrosion damage can occur at low water velocity Slug Flow high shear increases corrosion rate and reduces inhibitor

performance

Annular Flowhigh velocity combined with sand accelerates erosion/corrosion

Separation of aqueous phase increases corrosion risk

Higher water volume in line (e.g. 10% water cut has 40% volume)

Lower water velocity (from 5.3 ft/sec to 1.3 ft/sec)

Erosional (maximum) mixture velocity:

Vm,max= 100 / ns(0.5)

Where ns= L . HL+ (1HL) G

Factors Impacting Corrosion / Erosion


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Hydrodynamic Slugging

Hydrodynamic slugs are generated at moderate liquid and gas rates (see flow pattern

map) and are a common occurrence in most multiphase flowlines.

Slug Length Prediction

A. Prudhoe Bay Model (Brill et al)

Mean slug length (ft) is given by:

ln(Lm) = - 2.663 + 5.441 (ln(D)0.5+ 0.059 ln(Vm) (16-in 1979)

ln(Lm) = - 3.579 + 7.075 (ln(D)0.5 + 0.059 ln(Vm)0.7712 ln(D) (16+24-in 1981)

log normal distribution predicted

B. Hill & Wood (BP 1990)

1) Calculate Lockhart-Martinelli parameter

X = (VSL / VSG )0.9x (L / G )

0.4x (L / G )0.1

2) Estimate holdup from X using Taitel-Dukler stratified model (see Figure)

3) Determine gas and liquid phase velocities from holdup

4) Determine slug frequency (slug/hr) from:

Fs= 2.74 HLstx (VGVL) / (D/12) / (1HLst)

To calculate Slug Frequency from Slug Length (or vice versa):

1) Estimate liquid holdup in slug HL,slugusing Gregory-Nicholson-Aziz equation n:

HL,slug = 1 / (1 =1/(1+ (Vm/ 28.4)1.39))

2) Assume liquid holdup in bubble HL,bubble to be approx 20 percent

3) From material balance, slug factor (ratio of slug length to total slug + bubble length):

SF = (HL - HL,bubble) / (HL,slug - HL,bubble)

4) Slug Length is given by: Ls= SF x Vm / (Fs / 3600)

Ruleof Thumb: Longest slug (for facilities design) = 6 x Mean Slug

X

(Lockhart-Martinelli parameter)

LiquidHoldup

HLst


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Example C2: Slug Size and Frequency

Mixture Velocity, vm= 3 + 6 = 9 ft/sec

From Prudhoe Bay Model (1980), average slug length

Lm= exp(- 3.579 + 7.075 (ln(D))0.5+ 0.059 ln(Vm)0.7712 ln(D)) = 247 ft

FromHill & Wood (BP) Model:

X = X = (VSL / VSG )0.9 (L / G )

0.4(L / G )0.1= 3.84

From chart in preceding slide, Taitel-Dukler stratified model holdup HLst@ X=3.84 is 0.68

Liquid velocity when stratified = vL / HLst = 3 / 0.68 = 4.41 ft/sec

Gas velocity when stratified = 6 / (10.68) = 18.75 ft/sec

Slug frequency, Fs= 2.74 HLstx (18.754.41) / (D/12) / (1HLst) = 100 slug/hr

Calculate Slug frequency/length:

HL,slug = 1/(1+ (Vm/ 28.4)1.39)) = 1 / (1 + (9/ 28.4)1.39) = 0.83

HL,bubble = 0.2 (assumed liquid hold up in the bubble)

Slug Factor = (HL - HL,bubble) / (HL,slug - HL,bubble) = (0.50.2) / (0.830.2) = 0.47

Mean slug length (for Hill & Wood model) Ls= 0.47 x 9/ (100/ 3600) = 154 ft

Slug Frequency (for Brill et al Prudhoe Bay model) = 3600 * 0.47 * 9 / 247 = 62 slug/hr

The following data are available for a 10 inch horizontal pipeline operating in the slug flow regime:

average holdup = 50 percent, vSL = 3 ft/sec, vSG = 6 ft/sec. Predict the mean slug length and slug

frequency.

Fluid properties: liquid density = 55 lb/ft3, liquid viscosity = 6 cp

gas density = 2 lb/ft3 gas viscosity = .01 cp

X

(Lockhart-Martinelli

parameter)

LiquidHoldup

HLst


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Symbol Definition

HLW Volumetric water fraction in liquid phase

Lm Mean slug length

Vm,max Maximum mixture velocity (erosional velocity)

ns No slip mixture density

X Lockhart Martinelli parameter

HLst Liquid holdup when flow is stratified

HL,slug Liquid holdup in slug

HL,bubble Liquid holdup in bubble (during slug flow)

Fs Slug frequency (slug/hr)

SF Slug Fraction = slug length / (slug length + bubble length)

Terminology


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Single component properties

Black oil and empirical models

Compositional PVT analysis

Hydrates, Wax and Asphaltenes prediction and mitigation

D. Thermodynamics


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To be able to solve the oil or gas problems, pressure-volume-

temperature (PVT) relationships and physical properties of gases, andliquids are essential.

To get these properties, one can define a multi-component fluid system

compositionally, or just as Liquid, Gas, and Water mixture based on the

overall measurable data.

Apparent molecular weight Specific gravity,

Compressibility factor, z

Density,

Specific volume, v

Isothermal gas compressibility coefficient, cg Vapor- Liquid Equilibrium

Gas formation volume factor, Bg Gas expansion factor, Eg Oil Formation Volume Factor, Bo

The Gas Oil Ratio, and Water Cut are easy to measure in the field.

Single Component (Average) Properties for

Oil, Gas, and Water


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P V = n R Twhere

p = absolute pressure, psiaV = volume, ft3

T = absolute temperature, R

n = number of moles of gas, lb-mole

R = the universal gas constant which, for the above units, has the

value 10.730 psia ft3/lb-mole R

n = m/ MW

PV = ( m / MW ) R Twhere

m = weight of Gas, lb

MW = Molecular Weight of the Gas

g= m / V = (P MW) / (R T)where

g= Density of gas, lb/ft3

Volume of 1 mol Ideal Gas at Standard Conditions, ( Vsc )

at Psc= 14.7 psia, Tsc = 60 F = 520 R

Vsc= n R Tsc/ Psc = (1) (10.73)(520)/ (14.7)

Vsc

= 379.4 scf/lb-mol

Ideal Gas Law


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At a very low pressure, the ideal gas relationship gives reasonable

results2-3 % At higher pressures, the use of the ideal gas Lawte may lead to errors

as great as 500%

Therefore to express the relationship between the variables P, V, and T,more accurately, the z-factor, is introduced.

P V = z n R T

z = V/ Videal= V / ( (n R Tact) / Pact )

Real Gas


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Black Oil and Empirical Models

Black Oil Model is where the phase behavior of the mixture is based onexperimentally derived prediction methods of gas and liquid phases for

bubble point pressure, solution GOR, FVF, and viscosity.

The relative gravity of the oil, gas, and water phase are required.

All three phase gravities has to be known even if they are not expected to be

present in the mixture.

Empirical Modelspredict the fluid properties that will define the behavior of

the fluid mixture with changes in Pressure and Temperature.

Gas Compressibility

Solution Gas Oil Ratio Oil, Water Formation Volume Factor

Gas, Oil densities

Gas, Oil Viscosities


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Example D1Gas Thermodynamic Properties

1) Calculate the Specific Gravity of the gas.

SGgas=0.687461379

2) Using the Standing-Katz Gas Compressibility Chart, find the

z-factor for the gas at 90 F and 1200 psia. ( ignore

contaminants)

z-factor = 0.75

3) Update the z-factor for the contaminants

z-factor = 0.82

4) Calculate gas density at 90 F and 1200 psia. Use the

Engineering EOS

g=5 lb/cuft

M Tc Pc

16.04 343.34 667.00

30.07 550.07 707.80

44.10 665.93 615.00

28.01 227.52 492.80

44.01 547.73 1070.00

34.08 672.40 1300.00

Component y

C1 0.790

C2 0.007

C3 0.004

N2 0.012

CO2 0.017

H2s 0.170

Total 1.000

Determine the following properties for the natural gas with the given composition.

Mol Weight and critical Temperature and Pressure data is also supplied from Pure

Component Data tables.


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Procedure for Predicting Gas CompressibilityProcedure Calculate the Apparent Molecular Weight of the gas Mg=(yi*Mi) 19.93 lb/lb-mol

Calculate the Specific Gravity of the gas SGg Mg / Mair 0.688

Calculate the Pseudo Critical temperature Tpc

= (yi

*Tci

) 404F

Calculate the Pseudo Critical Pressure Ppc = (yi*Pci) 779 psia

Calculate the Pseudo Reduced Temperature Tpr= T/Tpc1.36 F

Calculate the Pseudo Reduced Temperature Ppr= P/Ppc 1.54 psia

Read the corresponding Compressibility Factor from

the Standing and Katz Chart z-factor 0.75

Check if the sour gas contains more than % 5 contaminants sum the mol fraction of H2Sand CO2

If more than % 5, calculate the Adjustment Factor, ,

for the contaminants = 120*(A0.9-A1.6)+15*(B0.5-B4.0 ) 40.9F

where

A=(yH2S+yco2) 0.187

B

= yH2S 0.17 Calculate the Adjusted Pseudo Critical Temperature Tpc= Tpc- 363F

Calculate the Adjusted Pseudo Critical Pressure Ppc= (Ppc* Tpc)/(Tpc+B(1-B)* 690.6psia

Recalculate the Pseudo Reduced Temperature and

the Pseudo Reduced Pressure using the adjusted Pseudo Critical T and P

Tpr 1.51F

Ppr 1.75 psia

Read the Gas Compressibility Factor from

the Standing and Katz chart z-factor 0.82


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Solution Gas Oil Ratio

Solution Gas Oil Ratio (Rs)

The bubble point pressure equation is reversed to solve for the solution gas oil ratio.

When oil is reaches to surface conditions some natural gas to come out of solution due to the Pand T change. The gas/oil ratio (GOR) is defined as the ratio of the volume of gas that comes out of

solution, to the volume of oil at standard conditions.

A point to check is whether the volume of oil is measured before or after the gas comes out of

solution, since the oil volume will shrink when the gas comes out.

In fact gas coming out of solution and oil volume shrinkage will happen at many stages of the flow

while the hydrocarbon stream from reservoir through the wellbore and processing plant to export.

Pb = f(Rs, g, T, o)

Lasater

for RsRp Rs = [ (379.3*35*o,,sc)/Mo]/[g/(1-g ] ( suggested for API>15)

Standing

for P1000 Rs= ( g*(P*X)1.20482/ (18)1.20482 ( suggested for API


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Oil and Water Formation Volume Factor

Oil Formation Volume Factor ( Bo) Standing

for P < Pb

Bo

= 0.972 + 0.000147 * F1.175+ C

where F= Rs*(g0.5/ o sc) + 1.25* T

Glaso

Vazquez-Beggs

for P < Pb and API 30 Bo= 1+4.67x10-4* 0.175 D*10-4 -1.8106RsD*10-8

for P > Pb and API >30 Bo= 1+4.67x10-4* 0.175 D*10-4 -1.8106RsD*10

-8

where D=(T-60)API / SG

Water Formation Volume Factor ( Bw) Computed from water densities


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Example D2Liquid Phase Density

Determine the liquid phase density for a 3 phase mixture given the

following data.

2200 psia and 190 F.(Use Standing correlations)

Oil gravity= 30 API

Gas Gravity= .85 Water Cut = 10%

Assume oil formation volume factor is 1.2 and Rs is 100 scf/stb at insitu

conditions.

SGoil= 0.876

LIQ = 48.11lb/cuft


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Not only the properties of oil, gas, and water, but also the phase behaviorchanges with the changes in Pressure and Temperature. The phase behavior

will determine the condensation or the evaporation of the phases, hence

determine the vapor-liquid split and the thermodynamic properties of the

phases.

Compositional PVT analysis predicts the properties of the Hydrocarbon

Water mixture based on the equilibrium, enthalpy, and property correlations.Flash calculations are based on the Equation of State to decide for the phase

separation., i.e.:

Peng-Robinson

Suave-Redlich-Kwong

Composional PVT Analysis

Multiple Component Phase Diagram


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Example D3Liquid Fraction

Determine the Liquid Fraction of the HC mixture from the given Phase

Diagram at the following conditions:

1) at 625 F and 4000

psia

2) At 425 F and 2250

psia

3) At 175 F and 1000

psia

4) At 100

F and 500

psia

0 mol %

10 mol %

20 mol %

20 mol %


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Gas Hydrates are formed by the C1, C2, CO2, H2S at P>166 psi

Formation of Hydrates require three conditions: the right combination of P and T; favored by low T, above 32 F and high P

Hydrate forming components have to be present in the system

Some water must be in the system, not too much, not too little

Other phenomena that increases Hydrate formation: Turbulence

High velocity- through chokes, narrowing valves due to Joule Thompson effect

Agitation, i.e. heat exchangers, separators

Nucleation sites are the points where phase change is favored, such as: Imperfections in the pipeline

A weld spot

Fittings Scale

Dirt

Sand

Presence of Free Water not necessary but the gas-water interfacecreates a nucleation site for hydrate to form

Hydrates

Courtesy of Petrobras


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Hydrate Prediction

The point at which hydrates form is dependent on the composition of the

gas.

This particular curve is only based on a correlation that

is valid for gases with similar compositions to those

shown in the table below. It is invalid in the presence

of H2S or CO2.

EXAMPLE: For a gas with a specific gravity of 0.7, and a pressure of 1000 psia, the temperature

below which hydrates would be expected to start forming would be 64F.

If the pressure is reduced to 200 psia, the temperature below which hydrates would

be expected to start forming reduces to 44F

Hydrate Formation Prediction for Sweet Natural Gases


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Hydrate formation prevention can be accomplished through

Water removal Separation

Separation will remove most of the free water from gas stream

Higher System TemperaturesPipe insulation and bundling, or steam or electrical heatingprocess

Lower System PressuresHigh temperature system pressure drops design through linechoking.

Alcohol Inhibitors injectionActing as antifreezes, alcohols will decrease hydrate formationtemperature below operating temperature

Kinetic (Polymer dissolved in solvent) InhibitorsWill bond on the hydrate surface to prevent crystal growth. shift thehydrate equilibrium conditions towards lower temperatures andhigher pressures , or increase hydrate formation time.

Antiagglomerants

These dispersants will cause water phase be suspended as

small droplets in oil or condensate

Hydrate Formation Prevention

Comparison of Hydrate Formation Prevention


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Comparison of Hydrate Formation PreventionMethods

Drying the natural gas

MeOH EG, DEG, MEG, TEG, and TREG

TEG, TREG are too viscous , too soluble in HCs

Drying is Preferred until not economical

Used :

upstream of chokes

Short gathering lines

Heating the flow line

Initial investment

Attention needed - minimum

Fuel - readly available

Cost - low

Adding Ckemicals:

Long flow lines


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Methanol versus Glycol

Methanol Used at any Temperature

Prevents hydrate formation better thenDEG and EG on per lb basis

Injection technique not critical

Good fraction of Methanol

evaporates into gas.

Not as economical

Low recovery cost High vaporization loss

Unless feeds into TEG unit, where

easily recovered in the regen

Good for

Low gas volumes

Temporary cases

Rarely needed Long flow lines

Dissolves the hydrates already formed

Glycol Not under 15 oF high viscosity

Difficult to separate from liquid HCs DEG has higher vaporization when


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Methanol Injection Problems in Facilities

If gas feeds into a glycol plant for dehydration after methanol injection:

Higher Glycol Regen heat (methanol co-absorbed with H2O vapor)

Any methanol released atmosphere with H2O vapor - hazardous

Cause corrosion in glycol still and reboiler ( If high enough in the

concentration in H2O)

Reduce the capacity of solid desiccant pellets competing with water

to be absorbed


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Cloud pointof a fluid is the temperature at which dissolved solids are nolonger completely soluble, precipitating as a second phase giving the fluid acloudy appearance.

In the petroleum industry, cloud point refers to the temperature below which wax

in liquid hydrocarbon form a cloudy appearance. The presence of solidified

waxes thickens the oil and clogs.

In crude or heavy oils, cloud point is synonymous with Wax Appearance

Temperature, (WAT) and Wax Precipitation Temperature (WPT).

Pour pointof a liquid is the lowest temperature at which it will pour or flowunder prescribed conditions. It is a rough indication of the lowest temperature at

which oil is readily pumpable. In crude oil a high pour point is generally

associated with a high paraffin content.

Cloud Point and Pour Point Definitions


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Waxes

Waxes are : The organic compounds of the crude

Insoluble in the crude at the producing conditions

High molecular weight C18-C60 alkanes

C18 to C36 (paraffin waxes, macrocystalline waxes)

C30 to C60 (microcrystalline waxes),

They are:

aliphatic hydrocarbons (both straight and branched chain),

aromatic hydrocarbons,

naphthenes

resins and asphaltenes.

Melting point, Boiling point, and Solubility of the HC mix is profoundly

effected by the presence of alicyclic, aromatic, and condensed rings. Deposits as solid when the temperature falls below the cloud point

The cloud point determines the rheology of waxy crudes

Above the cloud point, flow is Newtonian

Below the cloud point flow is non-Newtonian due to wax/solid

precipitation


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Problems with Waxes

When wax forms: Reduced permeability around the well bore/formation damage

Pumping cost increase because of:

Increase in viscosity can be 10 folds

Increased horse power requirement to transport the fluid through

Area for flow decreases due to wax deposition on the inner pipe wall

Increases pressure drop, can eventually plug the production string

Loss of production: Can eventually plug the production string and/or pipeline

Can deposit in the surface facilities

Decreased equipment volume, hence reduced volume/flow


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Wax deposits usually happen in oil

flowlines with components C7+.

Wax deposits have potential to

accumulate onto cooled surface

when it gets down to the CloudPoint, or Wax Appearing

Temperature.

Wax formation Temperature can be

determined within 5 C.

GOR, and Pressure effects can be

measured, but it is usually calculated

via thermodynamic prediction based

on Dead Oil values.

Formation of Wax

Temperature/Pressure Relationship in Formation of Wax

Wax Formation

No Wax

Bubble Point

Reservoir Fluid

Pressure

Temperature


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Wax Mitigation and Prevention:

Wax Deposition Removal Techniques: Mechanical

Pigging - Scraping wax from the pipe wall and mixing it with the crude

in front of the pig

ThermalMaintaining or increasing the temperature of the crude above the WAT

can prevent wax from settling on the pipe wall, or help to remove softened

wax.

ChemicalChemical Solvents and Dissolvers

substituted aromatics blended with gas oil.

Chlorinated solventsenvironmental concerns.

Wax PreventionWax Inhibitors

Crystal Modifiers

Pour Point Depressants

Dispersants

Surfactants


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Wax Deposition Rate Measurement Techniques

Wax Deposition Rate Measurements

Test Description Advantages Disadvantages

Static cold finger A cold surface is immersed in a reservoir of oil for set

duration then removed and inspected. The surface can

simple cooled block or finger, cooled tube or

sophisticated probe.

Useful inhibitor screening tool.

Quick Simple

Small volumes of sample.

Deposit formed.

Deposit directly inspected.

Accurate control of temperatures.

Adaptable for live oil.

No flow effects.

Risk of depletion of wax in small

sample volume.

Dynamic cold finger As above but shear can be applied to flow the oil over

the surface. This can be achieved with stirring or

immersing the surface in a flowing stream.For better control concentric cylinders are used.

Useful inhibitor screening and deposition

characterization tool.

As above

Addition of shear

Accurate control of shear/stress or flowvelocity.

Risk of depletion of wax in small

sample volume.

Difficult to simulate pipeflow andturbulence.

Difficult to monitor in-situ deposition

until end of test.

Capillary/tube blocking Warm oil is displaced through a narrow bore tube until

pressure increase indicated restriction or blockage.

Often used in uncontrolled cooling but better results

achievable with set temperature regimes.

Quick Simple

Small vols of sample

Qualitative measure of in-situ

deposition rates.

Live oils.

No direct measure of deposit.

Laminar flow regimes only.

Uncertain temperature profiles and heat

transfer rates.

Recirculating flowloops Oil is pumped through a section of pipe in whichconditions of temperature and flow can be defined.

Deposition can be detected by increasing pressure and

recovering of deposit.

Useful qualitative tool for assessing deposition

characteristic.

Simulates pipeflow regimes.Limited sample volumes

Control of temperature and flow rate.

Qualitative measure of in=situ

deposition rates/

Complex equipment.No direct measure of deposit at specific

points.

Need to recondition recirculating oil.

DP insensitive in Laminar flow.

Potential waxing outside deposition

section.

Cloud Point Methods


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These methods detect an effect caused by wax crystallization

- Recommended Indirect Methods


DSC When wax crystallizes from crude oil, small

quantities of heat are generated(Much like heat

given off when water freezes). The temperature at

which this heat of fusion first occurs can be

detected by a Differential Scanning Calorimeter,

DSC.

Small sample size.

Automated.

Quick.

Can estimate wax content.

High cooling rates potential for

subcooling.

Sensitivity: low wax contents difficult.

Subject to interpretation.

Infrared Detection/ Light

Scattering

Infrared Detection/ Light Scattering Wax crystals

will deflect and scatter light passing through the

oil. Infrared can be absorbed by waxes and willpenetrate black oils. Changes in light reflected or

absorbed as the oil cools will indicate wax

forming.

Sensitive.

Small sample size.

Suitable for live fluids.

Unrepresentative sample size.

Subject to interpretation

Little published validation.

NMR Sensitive.

Small sample size.

Estimate solid wax content.


Unrepresentative sample size.

Little published validation.



Thermodynamic

prediction

Model uses compositional analysis of oil and

published properties of components to predict

solubility of wax components.

Predicts cloud point and solid wax

phase for range of pressures and oil

compositions.

Very detailed input data.

Needs tuning to measured value.


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These methods are not recommended to evaluate cloud points

Cloud Point Methods- Not Recommended Methods


Visual and turbidity test

(ASTM D2500)

The term cloud point is taken from turbidity test

used to determine wax precipitation from fuels.

The wax crystals are detected by a change in

turbidity as the wax crystallizes. Often this test is

performed by eye but turbidity meters increase

sensitivity.

Simple.

Representative sample size.

Adaptable for live fluids.

Wide range of cooling rates.

Sensitivity( needs finite amount of

crystals)

Operator dependent (Visual only)

Other solids may be detected

Not suitable for Black Oils.

Viscosity As solid wax crystallizes it will effect the oils

rheology causing non-Newtonian behavior. The

Newtonian viscosity / temperature relationship ofthe oil is altered as the solid phase increases.

Representative sample size. Sensitivity. May require presence of

significant solid wax phase.

Underestimating initial crystallization.May detect other solids formation.


Pyknometry Crystallization will change the temperature /

density relationship of the fluid as it cools.

Representative sample size.


(New techniques are improving

sensitivity)

May detect other solids formation.

Sensitivity. May require presence of

significant solid wax phase.

Underestimating initial crystallization.


No published validation.


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Asphaltenes

The C:H ratio is approximately 1:1.2

Soluble in toluene but insoluble in lower n- alkanes such as pentane and hexane.

Asphaltenes are the heaviest and largest molecules in a typical hydrocarbon mixture

Oils from which asphaltenes are likely to precipitate

have low API gravity (are more dense), and have higher viscosities.

Deposits can be in the form of shiny and black graphite like appearance, or brown

sticky soft deposits.

Asphaltenes often co-precipitate with wax and even scale.

Asphaltenes

59


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It is better to prevent formation of asphaltenes deposits, through design and

operating conditions

If it cannot be prevented via design and the operating conditions, then treatment

is necessary to prevent flocculation of the asphaltenes particles.

Chemical treatments for removing asphaltenes:

solvents dispersant/ solvents

oil/dispersants/solvents

The dispersant/solvent approach is used for removing asphaltenes from

formation minerals.

Continuous treating may be required to inhibit asphaltenes deposition in the tubing.Batch treatments are common for dehydration equipment and tank bottoms. There

are also asphaltenes precipitation inhibitors that can be used by continuous

treatment or squeeze treatments

Treatment and Prevention of Asphaltenes:

60


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Asphaltenes

A h lt T t M th d S


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Asphaltenes Test Methods Summary


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Scale and Mitigation Strategies:

There are different types of scales.

Calcium Carbonate naturally exists in the resevoir (carbonate reservoirs)

Scale forms:

with co-mingling of produced fluids from different producing zones or

reservoirs

normally with decrease in pressure, carbon dioxide is released, and pH

changes to form scale.

Mitigation: dissolution by acidification or application of calcium carbonate scale

inhibitor.

Barium Sulphate In general barium sulphate scale results from water incompatibility,

primarily from either seawater injection and / or seawater breakthrough,

co-mingling with produced water rich in barium.

highly insoluble and will deposit at temperature drops across the production

processing plant.

Mitigation strategies::

removal of sulphate ions from seawater for re-injection,

application of barium sulphate scale inhibitors

treatment with dissolvers.


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Scale and Mitigation Strategies:

Iron Sulphide Iron Sulphide scale is deposited where microbial enhanced corrosion has

become a serious problem.

The scale is derived from the reaction of iron oxide from corrosion and

hydrogen sulphide,

a by-product of sulphate reducing bacteria metabolism.

Treatment for iron sulphide is application of a specialist chelating and

dissolution agent followed by microbial control with biocide application.

Calcium Sulphate Calcium Sulphate scale is relatively soluble and only poses a real problem when

conditions are close to the solubility limit and super-saturation occurs.

Sodium Chloride Sodium Chloride scale is caused by a saturation and evaporation process and is

readily removed by warm water in most cases.


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Viscosity prediction methods

Oil-water viscosityemulsions

Gas viscosity

Compositional viscosity (LBC)

Oil-water surface Tension

E. Transport Properties

Vi it D fi iti


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Oil viscosity o= F( P,T, SGo,SGg, Rs) usually reported in PVT Analysis. If notavailable, then the correlations are used.

Dead Oil Viscosity Viscosity of the oil at atmospheric conditions withno gas in solution and the system temperature.

Saturated Oil Viscosity Viscosity of the oil at P= PBand Tres

Unsaturated Oil Viscosity Viscosity of the oil at P>PBand Tres

Viscosity Definitions

Estimating Oil viscosity at PPB and at Tres1. Calculate the Dead Oil Viscosity obat Tres2. Adjust the dead oil viscosity for Gas Solubility effects at the desired

temperature

Estimating Oil viscosity at P> PB and at Tres

1. Calculate the Dead Oil Viscosity obat Tres2. Adjust the dead oil viscosity for Gas Solubility effects at the desiredtemperature

3. Include the effects of compression and under saturation of the

reservoir

Vi it P di ti M th d


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Viscosity Prediction Methods

L = 10X-1

WhereX = 103.0324-0.02023 API/ T1.163

Dead Oil Viscosity Correlations

Beal

Beggs-Robinson

Glaso

Saturated Oil Viscosity Correlations

Chew- Connaly

Beggs-Robinson

Dead oil Viscosity at Reservoir Temperature

and Atmospheric pressure (after Beal)


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Other Fluid Properties


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Surface Tension = f (SGoil, SGwater, P, T)

Plays an important role in calculating the flow pattern prediction in

multiphase flow.

Plays role in GasOil interface, as well as gaswater interface, and oil-water interface.

Surface Tension Calculation Methods:

Baker and Swerdloff

Katz et. al.

Specific Heat Capacity of the fluid - Very important parameter in heat transfer

Other Fluid Properties


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Heat Transfer Phenomena


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Heat Transfer Phenomena

The heat transfer coefficient U is determined by analyzing the combined effect of the

three modes of heat transfer:

Conduction- within a solid or between solid bodies (e.g. pipe wall and soil)

Convection- achieved through the movement of fluid (e.g. submerged pipe)

Radiation- energy emitted as electromagnetic waves from a hot body

Notethat radiation heat transfer is generally not significant in flow assurance (with the

exception of steam injection)

The rate of heat transfer per unit length (Btu/hr/ft) is given by:

dH/dL = U A (T fluidT ambient)where U overall heat transfer coefficient, Btu/hr-ft2-degF

A cross-sectional area of pipe, ft2

Tambient temperature of surrounding, deg F

T fluid average temperature of fluid in pipe, deg F

T fluid

TambientBuried Pipeline Area of Cross-Section

From basic calorimetric calculations, the change in pipeline fluid temperature due to heat transfer

to the surroundings is given by:

(ToutletTinlet) = - dH/dL x pipe length / Cp/ mass flow ratewhere Cp specific heat capacity of fluid mixture, Btu/lb/deg F

Tinlet

Example F1 Pipeline Heat Transfer


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Procedure1. Area of pipe cross-section = 3.14 / 4 * (12/12)2= 0.785 ft2

2. Mass flow rate = 5000 BPD /24 hr/day * 5.615 ft33/bbl * (0.8 * 62.4) lb/ft3= 58,396 lb/hr

3. Estimate outlet temperature = 60 deg F

4. Heat transfer gradient, dH/dL = U A (T fluidT ambient) = 1.0 x 0.785 x (80-40) = 31.4 Btu/hr/ft

5. Change in temperature = dH / Cp/ mass flow rate = 31.4 * 10,000 / 0.5 / 58396 = - 10.8 deg F

6. Revised outlet temp (iteration 1) = 10010.8 = 89.2 deg F (error = - 29.2)

7. Repeat Steps 4-6 with new outlet temp8. Revised outlet temp (iteration 2) = 85.3 deg F (error = 3.9)

9. Repeat iteration steps until convergence

10.Converged outlet temperature (after 4 iterations) = 85.8 deg F(error = 0.1)

Questionwill segmentation of the pipe provide greater accuracy?

Oil Gravity = 0.8, Specific Heat Capacity = 0.5 Btu/lb/degF

Tambient= 40 deg FBuried Pipeline, U = 1.0 Btu/hr-ft^2-degF, Pipe Length = 10,000 ft Pipe Outer Diameter = 12 inch

Tinlet=100 deg F

Q = 5000 BPD

Example F1Pipeline Heat Transfer

Determine the outlet temperature for 12-inch x 10,000 ft buried crude oil (sp gravity =

0.8) pipeline flowing at 5000 BPD, given an overall heat transfer coefficient of 1.0 Btu/hr-

ft2-degF.

Temperature at the inlet of the pipeline is 100 deg F and the ambient temperature is 40 deg F.

Assume that the specific heat capacity of the oil is 0.5 Btu/lb/de gF.

Overall Heat Transfer Coefficient


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Overall Heat Transfer Coefficient

Outer surface: submerged (convection), buried

(conduction) or exposed (free convection)

Conduction at outer wall, coating, Insulation

Conduction at inner wall, coating, Insulation

Convection due to boundary layer - film

Convection (or conduction) in annulus

Classical Shell Balance

Overall Heat Transfer Coefficient U = 1 / Total Resistance

Total Resistance = sum of resistances from convection /

conduction layers

Conduction layer resistance = diameter * loge(diaouter/diainner) / 2k

where: - thermal conductivity, Btu/day-ft-degF

Resistance due to film (convection) = diainner

/ (0.0225 * k * Re

0.8)

where Re - Reynolds number

Outer Surface (buried / submerged / exposed)

Resistance due to conduction (buried pipe) = diameter * loge((2Z+ (4Z2dout2220.5)/dout) / 2ksoil

where Z is the distance from the surface to the centerline of the pipe

Resistance due to convection (submerged in water/exposed to wind)

= diameter / (10 k *(0.26694 * log10(Re,surrounding)1.3681))

Where

Re,surrounding= 1.47 x Reynolds number calculated from pipe outer diameter and surrounding fluid properties

Overall Heat Transfer Coefficient OHTC


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Overall Heat Transfer Coefficient, OHTC

OHTC based on the flowline internal surface Area Ai is:

OHTC based on the flowline external surface Area Ao is:


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Thermal Conductivities of Soil


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Thermal Conductivities of Soil

Kersten(1949) soil= [ 0.9 log() -0.2]*100.01*

where

soil soil thermal conductivity, [BTU-in/(ft2-hr-F)]

moisture content in percent of dry soil weight dry density , lb/ft3

Thermal Conductivities of Typical Soil Surrounding Pipeline (Gregory,1991)

Flowline Burial Depth


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Flowline Burial Depth

When the ratio between the burialdepth and the Outside Diameter is

greater than 4, the decrease in the

U value is insignificant.

Available burial techniques may set

the limit on Minimum and MaximumBurial Depths.

Potential seafloor scouring and

flowline disturbance buckling need

to be considered .

Loch (2000)

Example F2 Overall Heat Transfer Coefficient


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Procedure

1. Area of cross-section = 3.14 / 4 * (12/12)2= 0.785 ft2

2. Fluid velocity = 5000 BPD x 5.615 ft3/bbl / 86400 sec/day / 0.785 = 0.41 ft/sec

3. Reynolds number = 1488 * 0.41 * (12/12) * (0.8 * 62.4) / 3.5 = 8785

4. Film resistance (convection) = (12/12) / (0.0225 * 1.6 * 87850.8) = 1.944 E-2

5. Pipe wall resistance (conduction) = (12/12) x 1/(2*600) loge (12.5/12) = 3.4 E-5

6. Insulation resistance (conduction) = (12.5/12) x 1/(2*0.96) loge (13.5/12.5) = 4.175 E-2

7. Soil resistance (conduction) = log( (4*24213.52)0.5/13.5)/(2 x 24) = 2.877E-2

8. Total resistance = 1.044E-2 + 3.4E-5 + 4.175E-2 + 2.877E-2 = 9.00 E-02

9. Overall heat transfer coefficient U = 1/(9E-2 x 24) = 0.46 Btu/fr/ft2/degF

Overall contribution of insulation = 4.175 / 9 = 46.4 %

Overall contribution of burial = 2.877 / 9 = 32.0 %

Updating Ex F1 with U=0.46 changes the calculated outlet temperature from 85.8 deg F to 93 deg F

Calculate the overall heat transfer coefficient for the pipeline in Example F1

given the following data:

Example F2 Overall Heat Transfer Coefficient

pipe diameter (inner) 12 inch

pipe wall thickness 0.25 inch

insulation 0.5 inch

Burial depth (center line to surface) 24 inch

Pipe Thermal Conductivity 600 Btu/day/ft/F

Insulation Thermal Conductivity 0.96 Btu/day/ft/F

Soil Thermal Conductivity 24 Btu/day/ft/F

Oil Flow Rate 5000 BPD

Oil Specific Gravity 0.8 water = 1Oil Specific Heat Capacity 0.5 Btu/lb/degF

Oil Thermal Conductivity 1.6 Btu/day/ft/F

Oil Viscosity 3.5 cp

Determine the relative contribution

of insulation and burial on the

overall resistance to heat transfer.

Change the heat transfer coefficient

in Ex F1 to the calculated value andevaluate the impact.

Heat Transfer In Wellbores


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Heat Transfer In Wellbores

Outer surface: submerged (convection), buried

(conduction) or exposed (free convection)

Conduction at outer wall, coating, Insulation

Conduction at inner wall, coating, Insulation

Convection due to boundary layer - film

Convection (or conduction) in annulus

Aditional Heat Transfer in Wellbores: Infinite Conduction

For a vertical well, the surrounding formation extendsoutwards infinitelythe finite depth burial model forconduction described earlier needs to be modified.

Transient ConsiderationsIn steam injection wells, there may a significant time-

dependent effect as the surrounding formation heats

up and heat transfer rates change as a consequence(heat transfer rate during the early time period will be

higher). The Ramey function is used to analyze this

time dependent effect.

Heating the surrounding formation may also cause the

thermal conductivity to change around the wellbore

due to the evaporation of water.

Annulus Heat TransferHeat transfer in the annulus due to convection of the

static annulus fluid (water/oil/gas/vacuum) needs to be

taken into account. Additionally, radiation effects are

sometimes important (e.g. in some steam injection

systems, a reflecting coating is painted on the inside

wall of the casing to reduce radiation effects).

Classic Shell Balance

Terminology


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Symbol Definition

dH Heat transfer rate, Btu/hr

dH/dL Heat transfer gradient, Btu/hr/ft

U Overall heat transfer coefficient, Btu/hr-ft2-degF

A Area of pipe cross-section, ft2

Tambient Temperature of surroundings, deg F

Tfluid Temperature of fluid, deg F

Cp Specific heat capacity, Btu/lb/deg F

k Thermal conductivity, Btu/day/ft/deg F

Terminology

G Transient Phenomena


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Basic principles of single phase transient flow

Multiphase flow transients

Pipeline startup, shut-in and blowdown

Terrain induced slugging

G. Transient Phenomena

Common Transient Operations


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Common Transient Operations

Transient Condition Operation Impact

Ramp Up / Down Rate change Rate surge

Startup Rate change from zero Pressure surge

Rate surge

Shutdown Compressor / Pump

shutdown

Pressure surge

Blowdown Pressure reductionTerrain Slugging Caused by topography Slug formation, growth and

dissipation

Sphering Periodic operation Rate surge

Pipeline leak / rupture Unplanned Product loss

Environmental damagePressure surge

Flow Rate Ramp Up


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0

200

400

600

800

1000

1200

0 20 40 600

2000

4000

6000

8000

10000

0.0 100.0 200.0 300.0

Flow Rate Ramp Up

BEFORE AFTER

LIQUID INVENTORY REDUCTION

How Big is the Surge?

Inventory,bbl

Marlin Pipeline 67 mile x 20 inch (Cunliffes approximation procedure)

Rate, MMscfd

69 bbl/MMscf liquid loading

Rate ramped up from155 MMscfd to 258 MMscfdPredicted Liquid Inventory

Time, hr

OutletLiquidRate,bp

h

Determine equilibrium inventory (holdup) at initial and final rates

Difference give the amount of liquid to be swept out

Estimate transition time as residence time for final inventory

Transition Time = Final Inventory / Final Rate

Estimate Transition Rate

Transition Rate = Final Rate + Inventory Change / Transition Time

Example G1 - Marlin Pipeline Transient


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Example G1 Marlin Pipeline Transient

Invent

ory,

bbl

Rate, MMscfd

69 bbl/MMscf liquid loading

Time, hr

OutletLiquidRate,bph

Initial inventory at 155 MMscfd = 19200 bbl (estimated from plot)

Final inventory at 258 MMscfd = 17600 bbl

Liquid to be swept out = 1920017600 = 1600 bblLiquid Rate (Final) = Liq Loading x Gas Rate = 69 x 258/ 24 = 742 bphTransition Time = Final Inventory / Final Rate = 17600 / 742 = 23.7 hr

Transition Rate = Final Rate + Inventory Change / Transition Time = 742 + 1600 / 23.7 = 809 bph

From data:

Actual surge rate > 1000 bphthe discrepancy is caused by the high transition timeLowering the effective transition time estimate would improve prediction(see spreadsheet)

From the pipeline inventory prediction provided for Marlin, use Cunliffes method toapproximate the surge rate at the downstream slug catcher when the gas rate at the inlet

is ramped up from 155 MMscfd to 258 MMscfd over a period of one hour. Compare thepredicted surge rate to the actual data and recommend additional steps to improve the

estimation.

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600

800

1000

1200

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5000

10000

15000

20000

25000

30000

35000

0.0 100.0 200.0 300.0

Pipeline Blowdown (depressurization)


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Pipeline Blowdown (depressurization)

Blowdown is the controlled depressurization of a gas (or gas-dominated) pipeline

generally achieved over a period of time. Blowdown is generally a safety procedure

used to reduce the risk of pipeline rupture and fire in an emergency.The key concerns during blowdown are:

1) How long will it take to depressurize the pipeline (to near atmospheric conditions)

2) What is the cooldown temperature profile given that the temperature will drop

below ambient due to Joule-Thompson cooling (potential for hydrate formation)

The discharge rate is generally controlled through an orifice (or valve) to ensure that

these operational issued are addressed.

Assuming critical flow,

the mass flow rate (lb/sec) through an orifice is given by the relationship:

W = CdK A P (MW / zT)0.5

where Cdis the coefficient of discharge

K is the specific heat capacity ratio for the gas

A is the area of cross-section

MW is the molecular weight

P is the upstream (pipeline) pressure

Example G2 - Pipeline Blowdown


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p p

Determine the pressure profile for the blowdown of a 5 mile x 6 inch (ID) gas pipeline

operating at 800 psi when the gas (gravity=0.8) is released through a 3-inch orifice (Cd

= 1.0). Average compressibility is 0.9, k = 1.4, and assume that the pipeline

temperature does not change from its initial value of 39 deg F.

0

200

400

600

800

1000

0 1000 2000 3000 40000.00

5.00

10.00

15.00

20.00

0 1000 2000 3000 4000

Procedure1. From geometry, orifice area = 3.14/4 * (3/12)2= 0.049 ft2

2. Pipeline volume = 3.14/4 * (6/12)2 * (5 x 5280) = 5181 ft3

3. Gas Molecular Weight = 28.97 x 0.8 = 23.18

4. Initial density of gas = 800 * 23.18 / (0.9 * 10.73 * (460+39) = 3.85 lb/ft3

5. Initial mass of fluid (gas) in pipeline = 3.85 * 5181 = 19934 lb

6. Initial rate of gas flowing through the orifice = 1 x 1.4 x 0.049 x 800 * (23.18/0.9/(460+39))0.5= 12.48 lb/sec

7. Starting from time =0, calculate the following at 100 second intervals1. Mass rate of gas through the orifice (from the orifice equation)

2. Remaining mass of gas in the pipeline (previous massmass rate * time increment)

3. Gas density = remaining mass / pipeline volume

4. Average pipeline pressure = density * z * 10.73 * (460+39) / 23.18

5. Determine the gas discharge rate at standard conditions from the mass rate

6. Plot the pressure and gas flow rate profiles as a function of time

Pressure Profile (psi vs. time)Flow Rate Profile (MMcfd vs. time)

Pipeline Cooldown


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p

When pipeline is shut-in, the fluid temperature drops over an extended

period of time until ambient conditions are achieved. A significant

parameter for cooldown analysis is the no-touch period which is the timeavailable before the pipeline must be started up again.

For a pipeline transporting waxy crude, the no-touch period is the time

before pour point (plus safety margin) is reached

From the Lumped Capacitance Cooldown Model, the temperature T is given

by :

T(t)To= (Ti - To) x exp (- C x t)

where t = period after shut-inC = U * Area of Contact / (mass of fluid * specific heat capacity)

Example G3 - Pipeline Cooldown


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Solution:

From the Lumped Capacitance Cooldown Model, the temperature

T is given by :

T(t)To= (Ti - To) x exp (- C x t)

where Tiis the inside fluid TemperatureT(t) is the inside fluid Temperature at time t

Tois the ambient temperature

t = period after shut-in

C = U * Area of Contact / (mass of fluid * specific heat capacity)

Procedure:

Fluid mass = 3.14/4 * (12/12) 2 * 10,000 * (62.4 * 0.8) = 391,872 lb

C = 1 x (3.14 x (12/12) x 10000) / (391872 * 0.5) = 0.16

p p

Given a 10,000 ft x 12 inch subsea pipe with a heat transfer coefficient of 1

Btu/hr/ft2/F and an average fluid temperature of 100 deg F, estimate the no-touch time

when the surrounding temperature is 40 deg F.

Crude oil characteristics: specific gravity = 0.8, heat capacity = 0.5 Btu/lb/F, pour point = 50 deg F

0.0

20.0

40.0

60.0

80.0

100.0

120.0

0.00 10.00 20.00 30.00

Time, hr

FluidTemp,F

For a range of time periods (e.g. 0-24 hrs in 1 hr increment) calculate and plot T(t)

From the plot (see right), no-touch time = 11 hr (actual time will be lower)

H. Integrated Flow Assurance


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Combining fluid flow, heat transfer and thermodynamics

Deepwater/subsea systems

Heavy oil transport

Monitoring and control

H. Integrated Flow Assurance

Fluid Flow, Heat Transfer & Thermodynamics


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, y

Fluid Flow Analysis

Predicts Flow & Pressure Behavior

Heat Transfer Analysis

Predicts Temperature Behavior

Thermodynamic AnalysisPredicts Fluid PVT Properties Flow Assurance

Integrated Analysisof Flow Behavior,

Pressure and

Temperature

Performance, and

Fluid Properties

Hydrate Management

Thermodynamics establishes hydrate limits

Temperature and pressure determine hydrate performanceHeat transfer controls temperature profile

Fluid Flow influences Heat Transfer

Heavy Oil Transport

Heat Transfer determines temperature profile

Temperature controls viscosity behaviorFluid viscosity establishes fluid flow

Fluid Flow influences Heat Transfer

Production Performance

Flow rates establish production

performance

Pressure determines flow rates

PVT properties impact pressure and

temperature profileTemperature and pressure influence

PVT properties

Flow Assurance in Deepwater / Subsea


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Commingling of

incompatible fluids

Deeper, colder

plugging & deposition

High back-pressure

Need for boosting 0

2000

4000

6000

8000

10000

12000

14000

16000

0 50 100 150 200 250

Temperature

Pressure

Reservoir

Facilities

Hydrate

Asphaltene

Wax

Bubble Point

Fewer wells, minimal intervention

Premium on reliability

Limited monitoring of

wells, pipeline & riser

Flow assurance in deepwater is about designing and operating systems that handle

the many unique challenges of subsea production while mitigating unnecessary risk to

ensure the continuous flow of oil and gas from capital-intensive projects


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Drag Reduction


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Drag Reduction Additives (DRA) are long-chain,

ultra-high molecular weight (1-10 million)

polymers that are injected into liquid pipelines

(both crude and refined products) to increasethroughput capacity.

DRA does not alter the fluid properties or coat

the pipe wall, but rather drag reduction occurs

due to the suppression of energy dissipation by

eddy currents in the transition zone between

the laminar sub-layer near the pipe wall and theturbulent core at the center of the pipe.

Turbulent flow in the pipe is therefore a

prerequisite for DRA to be effective.

In crude oil pipelines, DRA injection rates vary in the range of 10-50 ppm, with the

corresponding drag reduction effectiveness, the fractional reduction in frictional

pressure drop in the treated line, typically about 30-70 percent, and generally moreeffective in lighter crudes.

Modeling the effect of DRA injection in a pipeline is relatively straightforward.

Vendor supplied Performance Curves the effective drag reduction as a function

of flow rate for a range of concentrations.

These curves are pipeline specific and are generated from flowline

tests conducted by the vendor.

I. Integrated Production Analysis


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g y

The economics of flow assurance

Reservoir performance

how it impacts production

Introduction to artificial lift methods

Integrated asset modeling (IAM)

reservoir, production, process plant, economics

Economics of Flow Assurance


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At a high level, the economics of flow assurance involves a balance between

Cap Ex and annual Op Ex Costs based on the projected revenue stream.

Higher investments in Cap Ex are justified when the field is expected to produce

economically for a longer period (the projected life of a typical offshore field

varies from 10-30+ years).

Several factors effect the Revenue projections, including:

pricing forecasts for oil and gas

the availability of future markets through nearby pipeline connections

(especially for gas)

fiscal regimes (taxation, royalty, production sharing)

the time value of money (relating to deferred production)

Economics of Flow Assurance


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Capital Expenditure

Drilling and completion of wells

Pipelines and gathering system installation

Installation of prime movers (compressors / pumps / multiphase pumps)

Facilities (platform, slug catcher, separator, heaters, recovery and reinjection,

other topsides)

Artificial lift installations including related facilities such as compression, power

lines etc.

Operating Costs

Facilities maintenance

Inhibitors/chemicals for hydrates (methanol/glycol), wax, asphaltenes, corrosion,surfactants, etc.

Power costs for compressors, pumps, heaters, topsides, etc.

Personnel (platform, onshore, central support)

QHSE

Some of the key components of Cap Ex and Op Costs that need to be

included in any economic analysis for evaluating flow assurance alternatives:

Reservoir performancehow it impactsproduction


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p

Reservoir Decline

Reservoir Pressure (current) = Reservoir Pressure (previous) * Decline Rate * Cum Production

Note: for gas fields p/z is sometimes used instead of pressure (p) in the above equation

Maximum Drawdown

Drawdown is generally limited to avoid problems such as sand production

Bottom Hole Pressure > Reservoir PressureMax Drawdown Limit

Introduction to Artificial Lift Methods


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Most oil production reservoirs have sufficient

potential to naturally produce- during the early

phases of production. As reservoir pressure decrease, water

encroachment will naturally cause all wells to slow

down in production.

At some point, an artificial lift will be used to

continue or increase production.

On the other hand most water producing wells willneed some kind of artificial lift due to the high

hydrostatic pressure it creates on the oil, gas, or

both.

A well with high water rate will be usually put on

an artificial lift from the beginning.

Available technologies add energy to the systemto lift the fluids to the surface. There are times an

oil well may need:

Pressure(Psi)

Hydraulic Pumps

PCP

Plungers

ESP

Gas Lift

Rod Pump

Integrated Asset Modeling, IAMReservoir, Production, Process Plant, Economics


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IAM help to determine :

impacts of new drilling

best locations to set compression

to influence the order and location of the new drilling

evaluating the impact of third party activity

investigating gathering system improvement opportunities

for tubing sizes and evaluation of options versus performance

identifying wellwork candidates and other production enhancementopportunities

and to analyze:

upsets and production losses

requests from Infill Team on lateral capacity

uplift for future

pressure changes for future pipeline projects,

pressure changes for future compressor projects for debottlenecking

In summary, the reservoir decline, added wellhead compressor, the new wellsfeeding into the same line, the increased compressor suction pressures, andthe availability of processing facilities, along with the economics can becoordinated to give the optimized production scenerios.

Flow Assurance Monitoring & Control


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DTS

ESP

wellbore data seabed data

FPSO

manifold

multiphasepump

Subsea monitoring& control data

multiphase

meter

flowline

measurements

IAM Visualization


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Business value of these new operating tools achieved

through improved operations efficiency, integritymanagement, and organizational performance, byintegrating activities around reservoir, wells,pipelines, facilities, and commercial decision-making

Near Real-Time Field Data and Model Results Monitoring

Map-based Visualization


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Near Real-Time Field Data and Model Results Monitoring

IAM Online Model Calculations


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Differential Line Pressure (actual versus model

calculated)

Pipeline resistance (DP/Q)

Mixture Velocity

Erosion Rate (Salama)

Corrosion Rate (de Waard)

Liquid Hold-up

Model Error Tracking

Reservoir Inflow


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Inflow Performance Relationship (IPR):Production rate as a function of flowing wellbore pressure, (Pwf).

Productivity Index under-saturated oil reservoir

PI = Qo/ (PR- Pwf) Linear

Vogels equation below the bubble point pressure

Qo= Q

omax(10.2 P

wf/P

R0.8 (P

wf/P

R)2)

where Qomaxis a hypothetical maximum rate at Pwf = 0

The following equation can be used when Pwf < PB< PR

Qo= PI (PR- PB) + 0.5 PI / PB(PB2Pwf2)

For Gas Wells (back pressure equation):

QG= Cp [ (PR)2(Pwf) 2]n for 0.5 < n < 1.0

Qomax

Pwf

Qo

Oil Production Rate

FlowingBot

tomHolePressure

Slope = 1 / PI

Pr

Productivity Index

in Under-Saturated Reservoirs

Example I1 - Oil Well IPR


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Since test pressure (1234 psi) < BPP (2222 psi)

PI = Qo/ [(PR- PB) + 0.5 / PB(PB2Pwf

2)]

= 1.07 bpd/psi

Qomax= Qo/ (10.2 Pwf /PR 0.8 (Pwf /PR)2)

= 2792 bpd

Calculate Qofor a range of Pwfusing the equation:

Qo= PI (PR- PB) + 0.5 PI / PB(PB2

- Pwf2

)

Where: PR = 3636 psi

PB = 2222 psi

PI = 1,07 bpd/psi

The maximum rate is 2713 bpd (at Pwf= 0)

From a well test, the bottom-hole pressure was measured as 1234 psi at a rate of 2345

bpd. The static pressure in the reservoir after the well was shut-in for 48 hours was

measured as 3636 psi. Lab tests show that the bubble point pressure at the reservoir

temperature of 200 deg F was 2222 psi. Determine the productivity index and

absolute open flow potential and use these values to plot the IPR curve for the well.

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0.0 1000.0 2000.0 3000.0

Pressure vs. Rate

Rate (bpd)

Pressure(psi)

Example I2 - Integrated Production System


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An integrated gas production system extends from the reservoir through the wellbore,

pipeline and compressor flowing into the separation facilities. Estimate the delivery

capacity to a downstream trunk line operating at a fixed pressure of 1000 psia.

advanced flow assurance

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