optimum switch timing for steam-assisted gravity drainage

University of Calgary

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2018-06-29

Optimum Switch Timing for Steam-Assisted Gravity

Drainage (SAGD) after Cyclic Steam Stimulation

(CSS) in a Viscous Oil Reservoir

Liu, Siyuan

Liu, S. (2018). Optimum Switch Timing for Steam-Assisted Gravity Drainage (SAGD) after Cyclic

Steam Stimulation (CSS) in a Viscous Oil Reservoir (Unpublished master's thesis). University of

Calgary, Calgary, AB. doi:10.11575/PRISM/32260

http://hdl.handle.net/1880/107038

master thesis

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UNIVERSITY OF CALGARY

Optimum Switch Timing for Steam-Assisted Gravity Drainage (SAGD) after Cyclic Steam

Stimulation (CSS) in a Viscous Oil Reservoir

By

Siyuan Liu

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

GRADUATE PROGRAM IN CHEMICAL AND PETROLEUM ENGINEERING

CALGARY, ALBERTA

JUNE, 2018

© Siyuan Liu 2018

ii

Abstract

Steam-Assisted Gravity Drainage (SAGD) is often adopted as a follow-up process of Cyclic

Steam Stimulation (CSS) for heavy oil exploitations. Conventionally, CSS is first applied, and

the operation strategy turns to SAGD after the CSS has reached its economic limit. However,

considering the entire well life production, this timing scheme may not be the best. This study

analyzes the optimum timing for the switch from CSS to SAGD. A numerical simulation method

is employed to optimize the timing for CSS to SAGD and several levels of oil viscosity,

permeability, formation thickness, and well spacing are analyzed respectively. A net present

value (NPV) is set as the objective function to evaluate the overall performance and its

sensitivity to the switch point. The optimized operating conditions (temperature, pressure, and

cycle lengths) corresponding to the highest NPV are also generated. In short, this study helps to

maximize the profit of heavy oil development by determining the optimum switch timing from

CSS to SAGD processes.

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Acknowledgements

First of all, I would thank my supervisor, Dr. Zhangxing (John) Chen with my sincere gratitude

for supporting my thesis study. I appreciate the valuable opportunity he gave me in this research

group during the past four years.

Second, I give my utmost appreciation to Dr. Xinfeng Jia, who gave me a substantial guidance

on the idea of this thesis. I appreciate his precious time and thought of the assistance he provided

throughout my whole thesis study process.

Third, I have to thank my mother and father, who have been giving me a strong love and mental

support all the time during the past four years. Words can’t describe their great love and

contribution to me during my thesis study.

Fourth, I’m thankful to all the people and friends I met in University of Calgary. I will remember

the pleasant time we spent together and the inspirational moments we shared during the hard

times that passed by. This journey will certainly be remembered throughout my remaining

lifetime.

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Table of Contents

Abstract ............................................................................................................................... iiAcknowledgements ............................................................................................................ iiiTable of Contents ............................................................................................................... ivList of Tables ..................................................................................................................... viList of Symbols, Abbreviations and Nomenclature .............................................................x

CHAPTER ONE: INTRODUCTION ..................................................................................11.1 Thermal Methods Introduction ..................................................................................11.2 Problem Statement .....................................................................................................21.3 Thesis Objectives .......................................................................................................21.4 Organization of Thesis ...............................................................................................3

CHAPTER TWO: LITERATURE REVIEW ......................................................................42.1 CSS Literature Review ..............................................................................................4

2.1.1 Overall Introduction ..........................................................................................42.1.2 Production Mechanisms ....................................................................................4

2.2 SAGD Literature Review ...........................................................................................62.2.1 Flow rate control ................................................................................................82.2.2 Influential factors of SAGD performance .........................................................92.2.3 Steam chamber control ....................................................................................10

2.3 Other Techniques .....................................................................................................102.3.1 ES-SAGD process ...........................................................................................102.3.2 VAPEX process ...............................................................................................11

2.4 Reservoir Software Simulators ................................................................................122.5 Information of Liaohe Oilfield’s heavy oil operations ............................................13

CHAPTER THREE: CSS TO SAGD PROCESSES .........................................................153.1 Simulation Model ....................................................................................................153.2 Base Case Study .......................................................................................................173.3 Sensitivity Analysis .................................................................................................24

3.3.1 Viscosity studies ..............................................................................................253.3.2 Permeability studies .........................................................................................293.3.3 Formation Pay Zone Thickness .......................................................................343.3.4 Well Spacing Study .........................................................................................40

3.4 Chapter Summary ....................................................................................................43

CHAPTER FOUR: SAGD TO CSS PROCESSES ...........................................................454.1 Introduction and simulation model ..........................................................................454.2 Base Case Study .......................................................................................................454.3 Results and Discussion ............................................................................................50

4.3.1 Effect of Viscosity ...........................................................................................504.3.2 Effect of Permeability ......................................................................................564.3.3 Effect of Well Spacing ....................................................................................644.3.4 Effect of Payzone Thickness ...........................................................................68

4.4 Chapter Summary ....................................................................................................71

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CHAPTER FIVE: CASE STUDY .....................................................................................735.1 Introduction ..............................................................................................................735.2 Field Case Simulation Process .................................................................................755.3 CSS to SAGD results ...............................................................................................775.4 SAGD to CSS results ...............................................................................................795.5 Summary ..................................................................................................................81

CHAPTER SIX: CONCLUSIONS AND RECOMMENDATIONS ................................826.1 Conclusions ..............................................................................................................826.2 Recommendations ....................................................................................................83

REFERENCES ..................................................................................................................84

vi

List of Tables

Table 3-1 Base Model Parameters ..........................................................................................15

Table 3-2 Parameters for sensitivity analysis .........................................................................25

Table 3-3 Best results for medium and heavy viscosity oil scenario ......................................28

Table 3-4 Best time schemes for six cases for 500mD, 1000mD and 2000mD .....................32

Table 3-5 Results best time scheme cases of 45ft, 60ft and 75ft pay zone thickness scenario ............................................................................................................................38

Table 3-6 Results best time scheme cases of 108ft, 198ft and 288ft pay zone thickness scenario ............................................................................................................................42

Table 4-1 Parameters for Sensitivity Analysis ........................................................................50

Table 4-2 Results for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) ............................................53

Table 4-3 Results for six cases for 500mD and 2000mD (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) ...59

Table 4-4 Simulation Results of 60ft and 75ft thickness level (upper 60ft; lower 75ft) ........69

Table 5-1 Data of Liaohe field model .....................................................................................74

Table 5-2 NPV calculation data results for each CSS cycle ...................................................77

Table 5-3 NPV table for different timing schemes from CSS to SAGD ................................78

Table 5-4 NPV table for different timing schemes from SAGD to CSS ................................79

vii

List of Figures and Illustrations

Figure 2-1 Typical CSS cycle production-injection curves (Imperial Oil Resources, 2014) ....5

Figure 2-2 Beattie dilation-recompaction model (Beattie et al. 1991). ....................................5

Figure 2-3 SAGD process illustration (Exxon Mobil) ..............................................................7

Figure 2-4 Gravity Drainage Theory (Butler, 1991) .................................................................7

Figure 2-5 Mechanism of VAPEX process (Butler and Mokrys, 1991) .................................12

Figure 2-6 Workflow of CMOST module simulation (CMG Manuals, 2016) .......................13

Figure 3-1 Reservoir simulation basic model .........................................................................16

Figure 3-2 Model Viscosity-Temperature Curves ..................................................................17

Figure 3-3 Relative permeability curves (Appendix 2) ..........................................................17

Figure 3-4 Pressure control of the 5-year simulation process .................................................19

Figure 3-5 Oil cumulative production and rate (a: CSS; b: SAGD) .......................................20

Figure 3-6 Oil and water production of SAGD (1: CSS; 2: SAGD) ......................................21

Figure 3-7 CMOST Optimization graph (CSS is Upper, SAGD is lower) ..............................22

Figure 3-8 2-year CSS 3-year SAGD cumulative production (left: oil, right: water) ............23

Figure 3-9 Chamber chart CSS+SAGD (a) Day 4 of CSS injection period (b) First day of production period, (c) Last day of CSS period, (d) Day 2 of SAGD, (e) Day 190, (f) last day of SAGD period. .......................................................................................................24

Figure 3-10 Two viscosity profiles (Green: heavy, Red: medium) .........................................25

Figure 3-11 Cumulative oil and water production of case 3-yr CSS + 2-yr SAGD (a,b, c, d) .......27

Figure 3-12 Bar graph of NPVs for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) ......................27

Figure 3-13 Chamber Development at the end of 5 year ........................................................29

Figure 3-14 Cumulative oil and water production for 500mD and 2000mD case ..................30

Figure 3-15 Bar graph and total NPV vs CSS years for 3 permeability scenarios ................32

Figure 3-16 Case comparison for best NPV and CSS years (Permeability) ...........................34

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Figure 3-17 Chamber development at the end of the simulation period of the best NPV case ...................................................................................................................................36

Figure 3-18 Bar graph and total NPV vs. CSS years three thickness scenarios (a to f) .........37

Figure 3-19 Case comparison for best NPV and CSS years (Thickness) ...............................39

Figure 3-20 Chamber development at the end of the simulation period (thickness) ...............39

Figure 3-21 Cumulative oil and water production of 198ft well pair spacing (a, b) ...............41

Figure 3-22 NPVs for three well pair spacing levels (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) ..........41

Figure 3-23 Chamber development at the end of the simulation period of the best NPV case ...................................................................................................................................43

Figure 4-1 Pressure control of the process SAGD to CSS (3yr SAGD 2yr CSS) ...................46

Figure 4-2 Typical Oil production curve .................................................................................47

Figure 4-3 Typical water production curve. ............................................................................47

Figure 4-4 Chamber Chart of SAGD to CSS process (SAGD 3yrs + CSS 2yrs) (a to f) ....49

Figure 4-5 Viscosity Effect on Cum. oil and water production (3-yr SAGD + 2-yr CSS) ......51

Figure 4-6 bar graph of NPVs for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) .........................52

Figure 4-7 Chamber development at the end of 5-year graph .................................................56

Figure 4-8 Cumulative oil and water production of 500mD and 2000mD ..............................57

Figure 4-9 Bar graph of NPVs for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0) .......................59

Figure 4-10 Chamber development at the end of simulation period of 500mD and 2000mD ............................................................................................................................63

Figure 4-11 Cumulative oil and water productions for well spacing of 198ft and 288ft ........65

Figure 4-12 Spacing of 198ft and 288ft spacing NPV simulation results (1 to 4) ..................66

Figure 4-13 Steam chamber phase progression for 198 ft and 288 ft .....................................68

Figure 4-14 Bar graphs and total NPV with CSS years of 60ft and 75ft thickness level. .....70

Figure 4-15 Steam chamber growth of thickness 75ft at the end of 5 years (a to f) ...............71

Figure 5-1 Case Model .............................................................................................................73

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Figure 5-2 Field Model History Match ...................................................................................75

Figure 5-3 Total NPV vs. CSS timing and Bar values of CSS and SAGD process ...............78

Figure 5-4 Total NPV vs. SAGD timing and bar values of SAGD to process ........................80

x

List of Symbols, Abbreviations and Nomenclature

Symbol Definition q Oil flow rate ϕ Porosity So Oil Saturation

k Permeability g Gravity acceleration α Thermal diffusivity of rock and fluid h Oil Drainage height m Exponent parameter νo Oil kinematic viscosity NPV Net present value N Total number of periods t Timing of cash flow i Discount rate Rt Net cash flow at month t

1

Chapter One: Introduction

1.1 Thermal Methods Introduction

The twentieth century marks the latest development of the oil and gas industry. Newest oil plays

as well as the most innovative technologies come out gradually within this era. Heavy oil is one

of the most important resources among the non-conventional resources, which comes mainly

from Canada, Venezuela, and United States. However, its recovery process has been challenging

due to its low mobility properties. As the substances of heavy oil are heavy hydrocarbon

molecules, the molecular interaction between each other is complicated, making its viscosity

higher and causing its flow harder than the conventional light oil.

At present, thermal production techniques that are widely used are Steamflooding, Cyclic

Steam Stimulation (CSS), Steam Assisted Gravity Drainage (SAGD), In-situ Combustion (ISC),

Mining and some other minor subsidiaries. Mostly the ultimate goal of these methods is to heat

heavy oil by using different kinds of approaches in order to lower the oil viscosity and make it

flowable and recoverable. For these thermal methods, steamflooding and ISC are long time used

approaches with some high restrictions. CSS is used as an efficient thermal recovery method

which is frequently applied in heavy oil reservoir countries with its high adaptability and is often

set as a precursor to steamflooding and other thermal recovery methods. However, its oil

producing rate is not consistent and the residual oil saturation is high as well. SAGD is well

adopted in Canada and other countries for its adaptation in highly viscous heavy oil reservoirs

based on a production mechanism of two horizontal wells using the gravity drainage theory,

which can deliver a much higher recovery factor.

2

1.2 Problem Statement

In field operations for a specific heavy oil reservoir, these processes are frequently used

separately for a long time until their economic limit is reached. But a mixed thermal process

which potentially consists of a combination of several single processes is not fully optimized in

the perspective of the total period to reach a maximum economic performance. By doing

optimizations over the whole recovery period of the entire well life, the ending time point of a

first thermal process such as CSS or SAGD is altered to reach a better economic performance.

1.3 Thesis Objectives

In this thesis, a 2D homogeneous heavy oil reservoir model is generated and the ultimate goal is

to explore the maximum level of a recovery method that consists of thermal methods by CSS and

SAGD using reservoir simulation tools. Throughout the study, the best timing of the transition

year from CSS to SAGD or SAGD to CSS is the key strategy that is explored within a 5 years’

simulation period within this model. An experimental analysis method is used and commercial

reservoir simulation software CMG sets are adopted for generating experiment groups and

running production results. For each process, among the parameters of reservoir viscosity,

permeability, payzone thickness and well spacing, one parameter is changed to two to three

levels and the other three kept the same to see the impact it exerts to the whole recovery result.

During the process, an NPV factor is introduced into the analysis to appraise the process to find

the best strategy with the highest NPV value. Meanwhile, the best operating parameters for each

of the thermal processes is optimized as well. Finally, a field reservoir model from is used for a

validation process of this simulation flow.

3

1.4 Organization of Thesis

After the introduction, the thesis starts with Chapter 2: a literature review. It provides an

evaluative report of studies found in the literature related to thermal recovery processes,

including SAGD, CSS, optimization methods, and information of field operation. Chapter 3

elaborates the optimization of a complex thermal recovery process, i.e., CSS to SAGD, including

its numerical model, optimization scheme, results and sensitivity analyses. Chapter 4 investigates

an inverse process, SAGD to CSS, and the optimized NPV and operating schemes are provided.

Chapter 5 applies the optimization case study of a field model from Liaohe Oilfield with

practical reservoir physical properties, including permeability, porosity, and initial oil saturation.

Finally, conclusions are drawn and recommendations are given in Chapter 6, which finalizes this

thesis.

4

Chapter Two: Literature Review

2.1 CSS Literature Review

2.1.1 Overall Introduction

CSS, also called huff and puff, was first explored and used as a method in 1959 in Mene Grande

field in Venezuela. Compared with other thermal recovery methods, it is a single well process. It

is used for both light and heavy oil reservoirs. At present, it is still widely used in heavy oil

resources in Canada, Venezuela, and China. The main difference between steam stimulation and

flooding processes is that for a stimulation process, oil is heated and remains to flow around a

production well, while in flooding the oil has to flow through a cooler reservoir area until the

flooding becomes mature enough.

2.1.2 Production Mechanisms

A classical CSS process is normally carried out in 3 stages: injection, soak, and production. For

the injection stage, steam is injected into a production well normally for a period of 2 to 4 weeks

(Green and Whillite, 1998). During the soaking period, the oil receives the enthalpy energy from

the steam and becomes mobile. For the production period, natural energy is the most important

role. Formation recompaction is the main mechanism that drives oil to the production well. CSS

is also considered using a depletion drive mechanism for the usage of natural energy.

For the most typical case, a production rate curve is periodical during the entire period. A

water rate will remain the same during the production time, but the oil production rate will

decline quickly after about 8 cycles.

5

Figure 2-1 Typical CSS cycle production-injection curves (Imperial Oil Resources, 2014)

The Beattie dilation-recompaction model is a well acknowledged model which describes

the CSS process. It is shown in the figure below.

Figure 2-2 Beattie dilation-recompaction model (Beattie et al. 1991).

6

It indicates that a change in the reservoir rock porosity and permeability is not reversible, and it

is increased through the pressure back to the original value. During the elastic and dilation stage,

the steam is injected into a formation with high pressure to fail the formation mechanically.

In some regions, steam is injected above the fracture pressure into the formation to break the

formation and create a crack within the reservoir.

Compared to typical vertical wells, horizontal wells improve sweep efficiency, increase

producible reserves as well as steam injectivity, and decrease the number of wells required for

field development (Joshi, 1991). However, few pilot test in early 2000s had success in horizontal

well application as operating costs for generating steam still remained high due to a greater heat

loss when steam injection is schemed to a horizontal well application. Creating fractures using

hydraulic fracturing allows a more efficient placement of injected steam, heating up a larger

volume of reservoir and reducing residual oil saturation. This combination is usually considered

for low-permeability heavy oil reservoirs like California diatomite or Athabasca oil sands.

2.2 SAGD Literature Review

SAGD (steam-assisted gravity drainage) is a thermal recovery process which is applied in a large

scale in recent years, invented by Dr. Roger Butler around 1969. It consists of two horizontal

wells which locate in one vertical plane theoretically. Normally the horizontal producer locates

several meters below the injector, and two wells form a heavy oil recovery unit in a specific

reservoir region. A steam chamber is formed after steam is injected to the upper injector. The

recovery of SAGD is as high as 70%.

7

Figure 2-3 SAGD process illustration (Exxon Mobil)

Preheating is an essential part of the SAGD process. Before steam injection, the total area

should be preheated for several months by circulating the steam to the well pattern areas.

The gravity force is the main driving force of the SAGD method. After oil’s viscosity is reduced

and becomes movable, it will flow along the surface of the chamber interface to the producer

well with the steam condensate in the bottom of the chamber (Figure 2-4)

Figure 2-4 Gravity Drainage Theory (Butler, 1991)

Both the horizontal wells locate at the bottom of an oil pay zone. The steam is injected

from the horizontal injector, and starts to rise. The oil phase will receive the conduction heat

8

from the steam and become movable, and the steam becomes condense water as well. Therefore,

the heavy oil and water condensate flow down towards the bottom driven by the gravity force.

The interface between the steam and the cold immobile oil forms and the shape of the steam

zone is like a chamber. After the oil is produced, the steam will occupy the pore space which is

originally taken by oil, and, therefore, the chamber grows gradually, upwards and sideways.

During the process, the chamber pressure almost remains the same (Butler, 1991).

2.2.1 Flow rate control

An oil drainage rate is often described in the following equation (Butler, 1991):

𝑞 = #$Δ%&'()*+,-

(2.1)

which is parallel to the vapor-liquid interface, where q is the oil flow rate to the production well,

φ is the porosity, ΔSo is the average oil saturation change, k is the permeability, g is the gravity

acceleration, α is the thermal diffusivity of rock and fluids, h is the oil drainage height, m is the

parameter, and νo is the kinematic viscosity of oil.

Compared to the typical steamflooding, the SAGD process has a potential of reducing the

steam override (Butler, 1991) as wells are placed in the vertical plane and the gravity force

caused by the density difference of steam and the oil and water condensate phases is totally

beneficial to make the condensate flow to the producers. The viscous fingering effect is reduced

to a minimum level as well.

9

2.2.2 Influential factors of SAGD performance

As the SAGD process is an enthalpy conduction process from a steam chamber to its adjacent

outer cold oil reservoir, the conduction efficiency is the most essential part that needs to be

guaranteed. Therefore, although SAGD is well employed in several parts of the world’s heavy oil

fields, there are also limitations on this process.

According to Edmunds and Chhina (2001), the pay zone thickness plays an essential role

during the SAGD process. The performance will decrease drastically if the reservoir thickness is

less than 15 meters, as the steam chamber may reach the overburden rock during the growing

process, and the enthalpy will disperse to the cap rock layers.

In the geological aspect, the reservoir heterogeneity plays a large role. The existence of

lean zones can heavily influence the shape and the growing process of a steam chamber,

therefore reducing the heat conduction efficiency to the cold oil area. According to Baker et al.

(2008), water zones at the bottom of a reservoir can turn to thief zones, which absorb large

amounts of heat from the steam chamber, increasing the heat loss and limiting the chamber

drainage height. Shale barriers can also become a significant factor that influences the heat

transfer performance. The location of a barrier is essential and the heat conduction is impeded if

it locates in the middle of the horizontal injector and producer. According to Shin and Choi’s

study (2009), a shale barrier can reduce the SAGD performance to the greatest level when it

locates between the injector and the producer. However, it can reach a minimal level when it

locates above an injector, with a vertical distance ranging from 5 to 25 meters.

The oil viscosity is a considerable factor as well. According to Li et al. (2008) the oil

viscosity tends to increase as the reservoir depth increases. However, whether it will exert a

positive or negative effect is not ascertained. Gates et al. believed that SAGD performance

10

deteriorates as the oil viscosity varies vertically (2008) but Chen and Ito (2012) held that by

carrying out a numerical analysis the viscosity variation in the vertical orientation is not obvious.

2.2.3 Steam chamber control

The steam trap control process is an important aspect for operators to consider. Usually there is a

temperature difference between the steam areas around the injector and the producer in a SAGD

pair which is surrounded by the oil and water condensate to be produced. The goal to design this

is to prevent steam from being produced through the bottom producer, so a liquid pool is formed

and submerges the producer. The temperature difference is named subcool, and normally it is

kept around 10 to 20℃to maintain the production (Edmunds et al, 1991). The subcool is

controlled by monitoring the pool’s liquid level (Gates and Chakrabarty, 2008). According to Ito

and Suzuki who carried out a simulation model study in Hangingstone reservoir, Canada (1999),

the Cumulative Steam-to-Oil (CSOR) is minimally reached by controlling the subcool to 30 to

40℃ which is a rare exceptance. As a steam chamber zone is several hundred meters

horizontally in the SAGD process, the subcool should also be monitored along the whole length

of the horizontal well pair (Gates and Leskiw, 2008). Furthermore, a constraint of a producer’s

maximum steam rate should be applied to maintain the steam trap during a SAGD reservoir

simulation process (Gates and Chakrabarty, 2008).

2.3 Other Techniques

2.3.1 ES-SAGD process

ES-SAGD (Expanding-Solvent Steam Assisted Gravity Drainage) is an enhancement of the

traditional SAGD with a small amount of hydrocarbon additive injected along with the steam

11

into an upper injector well (Nasr et al., 2003). The solvent is dissolved into the bitumen at the

chamber edge, reducing the bitumen’s viscosity and making the oil mobile and flow together

with it. It is an enhancement of SAGD and has been successfully field-tested to achieve a better

performance than the SAGD process. Studies show that oil production rates have been improved

as well as OSR (Oil-Steam Ratio) and the water consumption and energy required have been

decreased.

2.3.2 VAPEX process

VAPEX (Vapor Extraction) is also a solvent based process, with a similar well configuration and

solvent chamber with ES-SAGD. The solvents are carefully chosen for this process (e.g., ethane,

propane, butane, etc.). Diffusion plays a vital role in VAPEX while the solvent dissolves into the

bitumen phase and it will process in a slow motion (Das and Butler, 1996). After oil becomes

mobile, it flows along the vapor-liquid interface to the horizontal production well. Butler and

Mokrys (1989) assumed that flow in a mobile oil zone is a laminar flow and the flow streamlines

are parallel to the vapor-liquid interface. The VAPEX is suggested to be a more economical

process especially for thin heavy oil reservoirs as the absence of the heat loss to the overburden

and underburden layers (Butler and Mokrys, 1991) but experiments are still to be implemented

as the diffusion process is too slow, making the production rate lower than that from the normal

SAGD. Also, the cost of a solvent is also a problem to be solved.

12

Figure 2-5 Mechanism of VAPEX process (Butler and Mokrys, 1991)

2.4 Reservoir Software Simulators

Reservoir simulators are the basic computer tools utilizing the high performance of visualization

and computations of CPU cores. They are used in building reservoir models grids, property

iteration calculations, and conveying the overall recovery performance. For CMG’s STARS

simulator, a thermal model is used for its calculations.

Based on the mass conservation law in a reservoir finite unit and diffusivity equations,

basic solutions of oil and water flow rates is obtained in multiphase circumstances in a reservoir.

Different parts of grid blocks contain the information of different phase’s properties, such as

compressibility of rock, permeability, initial water and oil saturation and viscosity. Phase behavior

diagrams are also contained. Numerical techniques such as finite difference formulations are

applied. IMPES (Implicit Pressure-Explicit Saturation) or Fully implicit calculation methods are

options that is adopted during the simulation process.

13

Figure 2-6 Workflow of CMOST module simulation (CMG Manuals, 2016)

CMOST is a module of CMG that is developed to carry out the sensitivity analysis,

optimization, uncertainty analysis, and history match process of reservoir simulations. Using a

base model that is preset, the experimental analysis theory and Monte Carlo simulations are used

to generate different values of several specific reservoir parameters within the preset range,

carrying out simulation using the generated parameter values, analyzing the results and using them

for further parameter value generations (Figure 2-6, CMG Manuals, 2016). Each cycle of the flow

can generate one simulation, or experiment, and every experiment is linked to an objective

function, such as cumulative oil production, an oil rate, or a net present value, which is defined in

the software workflow. After a certain number of experiments are carried out, the best value of an

objective function is adopted as the optimization final result.

2.5 Information of Liaohe Oilfield’s heavy oil operations

Liaohe Oilfield is a field where heavy oil resources consist of a significant portion in China’s main

oil reservoir plays with an overall estimation reserves of 180 million tons. Compared to heavy oil

14

reservoirs in Canada, Liaohe’s oil reservoirs are deeper overall. About 25% of the reservoirs is

within the depth of 600 to 900 meters, 45% within the depth of 900 to 1300 meters, and another

24% portion within the depth of 1300 to 1700 meters. Their heterogeneity is also severe, with a

plenty of reservoirs with bottom water, side water or gas cap, with a large number of faults

contained.

The CSS method started in Liaohe in the 1980s with most wells of vertical configurations.

The SAGD method started to be applied in the late 1990s with dual horizontal well trajectories or

vertical and horizontal well combinations to utilize the previously drilled vertical wells. For some

reservoir cases a recovery factor of more than 30% is achieved after the SAGD approach is

adopted.

Normally CSS is applied with cycles up to twenty, to the circumstance of almost no oil

production, and then shut down operations or other conversion methods are used for following

recovery, which takes a large amount of time, with little cash flow for a single well. Therefore,

we presume there is an optimum timing to concede the CSS process. The switch time from CSS

to SAGD should be optimized to reach a maximum performance of the overall recovery in field

operations. The following chapters will discuss this in more details.

15

Chapter Three: CSS to SAGD Processes

3.1 Simulation Model

The base model is developed to simulate half of the CSS or SAGD process in a typical Canadian

heavy oil reservoir. The basic parameters are listed in Table 3-1.

Table 3-1 Base Model Parameters

Half Model Cross-section area, ft2 54*45 Half Model Length, ft 54 Porosity 0.3 Permeability, k (Darcy) 1000 Reservoir temperature, F 75 Oil zone compressibility, Ct,o, 1/psi 5*10e-4 reservoir pressure, psi 125 Dead heavy oil viscosity @ 75F (cp) 35745 Dead heavy oil density, lbm/ft3 60 Oil saturation, So (vol.%) 0.6 Oil average Thickness, ft 45 Depth, ft 1500

Reservoir model. This homogeneous model is built by the Builder module of the

reservoir simulation software sets CMG, which conprises 270 grid blocks, 18 grid blocks in the

X direction, 1 block in the Y direction, and 15 blocks in the Z direction. Therefore, it is regarded

as a one slice reservoir. With each block’s size of 3×3×3 ft, this model has a dimension of

54ft×3ft×45 ft. So the well spacing is considered as 108 ft in this base case. The initial oil

saturation is set as 0.6 and permeability is set as 1000 mD. The depth of this model is set as 1500

ft.

Wells. All wells in this model are set along the J direction, vertical to the IK plane. For

16

the perforation block, the injector and producer of the CSS well pairs are both located in grid (1,

1, 8) which is the middle block in the K direction. For the SAGD horizontal well pattern, the

injector well locates in (1, 1, 8) and the producer well locates in (1, 1, 15).

Figure 3-1 Reservoir simulation basic model

Viscosity. Figure 3-2 shows the viscosity temperature profile of the two different oil models. The

thermal model from the CMG heavy oil base case is used for viscosity information. A medium

Oil, whose viscosity at reservoir temperature (75F) is 35000 cp and a heavy oil, whose viscosity

at reservoir temperature is 180000 cP, are the two oil models that are used in this study.

17

Figure 3-2 Model Viscosity-Temperature Curves

Relative permeability. The relative permeability’s property of the reservoir fluid is

shown in Figure 3-3 (Detailed data in Appendix 2), where the gas phase is not considered in this

model.

Figure 3-3 Relative permeability curves (Data in Appendix 2)

3.2 Base Case Study

Timing scheme. To determine the optimum timing for starting SAGD after a CSS process, this

study designs a new scheme. First, the net present value (NPV) is set as the objective function of

y=3E+13x-4.923R²=0.98303

y=7E+15x-5.742R²=0.98777

0.10

1.00

10.00

100.00

1000.00

10000.00

100000.00

1000000.00

0 100 200 300 400 500 600 700

Viscosity

(cP)

Temperature(F)

Medium

ViscHeavy

18

the optimization process. Second, a total period of 5 years of the CSS-after-SAGD process is

stimulated. Third, six cases or six combinations are considered:

(1) 5-year CSS

(2) 4-year CSS and 1-year SAGD




(6) 5-year SAGD

After the simulation of these six cases, the NPVs for each of the case are compared, and the

optimum timing is determined.

Operation scheme. Pressure control is one of the most essential operation conditions.

shows the pressure change for the case of two years CSS and then switched to SAGD. It is noticed

that in the injection period of the CSS process, the pressure starts up high at about 950 psi, and

drops off drastically during the soaking period and production period as the oil and water starts to

come up to the surface. Two cycles for the CSS have been implemented and the pressure cycles

also reflects this. The pressure for the last three years remains constant as during the SAGD period.

The process of chamber growing with the steam injection and oil production from the upper

injector and lower producer, respectively, is consistent throughout three years.

19

a) Producer well block (1, 1, 15) b) Injector well block (1, 1, 8)

Figure 3-4 Pressure control of the 5-year simulation process

NPV. NPV is set to be the economic indicator of the entire process. Regarding to a certain

specific month, it is set as: NPV= Oil per volume price*(CSS Total Oil Production + SAGD Total

Oil Production) - Steam per volume cost*(CSS Total Steam Used + SAGD Total Steam Used).

For a total simulation period of 5 years, The equation is used as below:

𝑁𝑃𝑉 𝑖, 𝑁 = 34567 4

89:; (3-1)

𝑁 – Total number of periods (The number of total processed months at a specific study point).

𝑡 – Timing of the cash flow (The month’s number at the study point).

𝑖 – Discount rate (a 0.007 monthly discount rate is used).

𝑅9 – Net cash flow (oil revenue – water cost) at month t.

It is worthy of noting that $60 per barrel of an oil revenue and $5 per barrel of a water cost are

used. The operation and other operation costs are neglected in this model.

Constraints. Constraints are set for the CSS and SAGD processes: (1) CSS: bottom hole

pressure 1004.5 psi for the maximum and a surface water rate of 5000 bbl/day for the maximum

20

for the CSS injector; bottom hole pressure 200psi for the minimum for the CSS producer. (2)

SAGD: producer: bottom hole pressure 225.4psi for the maximum and a surface water rate of 2

bbl/day for the maximum for the SAGD injector; bottom hole pressure 215.4 psi for the minimum

and a surface liquid rate of 5 bbl/day for the maximum for the SAGD producer.

Performance. The production curves of CSS and SAGD is generated. For the CSS period,

there are two peaks in the oil production rate curve as the blue line in Figure 3-5 (a) shows. The

highest rate is about 12 bbl/d. However, the overall producing time is very short. The cumulative

oil production for the total two CSS cycles is around 38bbl.

After the CSS well pairs shut in and the whole process convert to the SAGD process, the

oil production continues and from the blue line in Figure 3-5 (b), the oil production rate becomes

more consistent and prolonged compared to the previous CSS period. It increases gradually and

the highest oil production rate reaches 0.26 bbl/d at approximate 1 year after the start of the SAGD

process. It decreases in a relatively smooth fashion after the peak point.

a) CSS b) SAGD

Figure 3-5 Oil cumulative production and rate (a: CSS; b: SAGD)

The cumulative oil production for the SAGD period is 110 bbl, which is much higher than

21

the CSS period and gives a better recovery performance for the residual oil left in this model

(Figure 3-6). The water production also expresses a similar shape. For the CSS process the

maximum water production rate for the total two cycle is about 980 bbl/d according to the

simulation results and also continues in a very short production period similar to the oil production

curves. For the SAGD period it reaches about 1.4 bbl/d and comes to 1 bbl/d in the final period.

So the cumulative water production is growing consistently in the 3-year process.

a) CSS b) SAGD

Figure 3-6 Oil and water production of SAGD (a: CSS; b: SAGD)

The CMOST module is a history match and experimental parameter sensitivity analysis

tool in the CMG simulation software. In this study it is utilized to carry out the NPV optimization

process. By running it, the operation of running STARS for a single process is repeated, meanwhile

manipulating the parameters that control the thermal process, such as injection steam pressure,

steam temperature, and a producer well steam rate. The total number of experiments is set in

CMOST and after all the experimental simulation cases are run, the case with the highest NPV is

generated.

Normally up to 200 total experiments is carried out for a single process optimization, if a

22

stable trend for the maximized NPV solution is reached. From Figure 3-7 the optimal solution

with the red dot is the solution with the highest NPV among all the experiments that have been

carried out. The two-year CSS in this base case has a highest NPV for about $300 shown in Figure

7.1 and for the SAGD case the highest NPV result is about $1500.

Figure 3-7 CMOST Optimization graph (CSS is Upper, SAGD is lower)

Optimization process. The model runs for 5 years in six schemes: 0-year CSS 5-years

SAGD, 1-year CSS 4-years SAGD, 2-years CSS 3-years SAGD, 3-years CSS 2-years SAGD, 4-

years CSS 1-year SAGD, 5-years CSS 0-year SAGD. All other parameters such as oil viscosity,

permeability, formation thickness, and well spacing are preset. The CMOST module is utilized to

generate the experiments with different operating conditions like temperature, pressure, and CSS

cycle lengths, and finally the experiment with the highest NPV is adopted as a representation of

the overall case of this timing scheme.

After the simulation process is run by the CMOST module, the production profile for

23

each timing scheme is generated and the profile for two years CSS and three years SAGD is

illustrated as an example in Figure 3-8 as a single production profile for oil and water

production, respectively. The CSS and SAGD production curve trend is seen in this figure, from

which CSS's cumulative oil production is increased incrementally period by period, and SAGD's

is increased smoothly to the end of the period.

Figure 3-8 2-year CSS 3-year SAGD cumulative production (left: oil, right: water)

For this 2-year CSS and 3-year SAGD case, the oil total production for CSS and SAGD is about

150 bbl, and water total production for CSS and SAGD is about 1450bbl. During the CSS and

SAGD period, an oil producing chamber forms around the injector well. The oil saturation graph

generated by STARS (Figure 3-9, a to f) is hereby utilized to show the chamber progression for

the CSS and SAGD periods, respectively. The red colour block indicates the high oil viscosity

and green indicates low oil viscosity. Figure 3.9 shows the chamber shape at the end of a typical

CSS operation. For the end of the SAGD period, almost all the model’s blocks are green (Figure

3-9, f), which shows the chamber shape, as well as the extent of the oil recovery in this reservoir

model after all the recovery processes are done.

24

(a) (b) (c)

(d) (e) (f)

Figure 3-9 Chamber chart CSS+SAGD (a) Day 4 of CSS injection period (b) First day of

production period, (c) Last day of CSS period, (d) Day 2 of SAGD, (e) Day 190, (f) last day

of SAGD period.

3.3 Sensitivity Analysis

In this study, four main reservoir parameters are cross-studied along with these six different time

regimes. They are viscosity, permeability, formation pay-zone thickness and the well spacing

between other well pairs. The value of each parameter analyzed is listed in Table 3-2 and the

medium level of viscosity, 1000 mD of permeability, 45 ft of pay-zone thickness, and 108 ft of

well spacing are adopted for the values adopted in the base case.

25

Table 3-2 Parameters for sensitivity analysis

Parameters value

Parameters

Viscosity Medium Heavy

Permeability 500mD 1000mD 2000mD

Pay-zone Thickness

45ft 60ft 75ft

Well Spacing 108ft 198ft 288ft

3.3.1 Viscosity studies

Two viscous oils, medium and heavy, are studied. The viscosity-temperature profile is shown in

Figure 3-10. It is obvious that after heated, the viscosity of oil drops significantly, which facilitates

its flow in the reservoir. By doing the contrast between the results of these two viscous oils, the

viscosity effect to the final NPV which shows the overall recovery performance is analyzed.

Figure 3-10 Two viscosity profiles (Green: heavy, Red: medium)

After carrying out the simulations for all the six timing schemes in these two viscosity profiles by

y=3E+13x-4.923R²=0.98303

y=7E+15x-5.742R²=0.98777

0.10

1.00

10.00

100.00

1000.00

10000.00

100000.00

1000000.00

0 100 200 300 400 500 600 700

Viscosity

(cP)

Temperature(F)

ViscMedium

ViscHeavy

Power(ViscMedium)Power(ViscHeavy)

26

CMOST, some data relating to the simulation process is generated. The first is the cumulative oil

and water production curves with respect to time (Figure 3-11). In the left of the cumulative oil

figure, the red line indicates that for the medium oil viscosity which is the base case, all the 5-year

period using SAGD can give the greatest oil production at the end of the simulation period. For

heavy oil viscosity, the first year CSS and then switched to SAGD can give the greatest oil

production. For water production versus time curves, all five years SAGD produces much more

water than all other cases for medium viscosity oil, while for heavy viscosity oil, one year CSS

and then switched to SAGD for the remaining four years can produce the most water.

a) Cumulative Oil Production of Medium Oil b) Cumulative Oil Production of Heavy oil

c) Cumulative water production of Medium oil d) Cumulative water production of Heavy oil

27

Figure 3-11 Cumulative oil and water production of case 3-year CSS 2-year SAGD (a, b, c,

d)

The maximum NPV value for all the six time schemes can also be calculated. Figure 3-12

gives the bar view of the maximum NPV which is from the best experiment of each time scheme

generated from CSS and SAGD’s simulation, respectively. Overall the SAGD part can generate

much more NPV than the CSS part. For the heavy oil, only the 2-year CSS 3-year SAGD time

scheme can generate a positive NPV for the CSS part, and the SAGD part also has the greatest

value among all other schemes.

a) Medium Oil (Base Case) b) Heavy OilFigure 3-12 Bar graph of NPVs for six cases (a, b)

Table 3-3 gives the performance of each timing scheme in a detailed fashion, with the

operation parameters generated by CMOST during the simulation meantime. The steam injection

temperature for the CSS period is around 550 Fahrenheit for most timing schemes, and for the

SAGD periods time equal to 2 years and 1 year schemes as well. For the SAGD periods over two

years scheme, steam injection temperature is around 450 Fahrenheit. The CSS period’s maximum

injection time, soak time and production time are also shown in the table, which is the best CSS

timing scheme with the best NPV case given by the CMOST module. The SAGD producer’s

production rate is also generated.

0

1000

2000

3000

0 1 2 3 4 5

NPV

($)

CSSyears

CSS SAGD

0

1000

2000

3000

0 1 2 3 4 5

NPV

($)

CSSyears

CSS SAGD

28

Table 3-3 Best results for medium and heavy viscosity oil scenario

CSS SAGD

Oil Type

Time scheme Inj Temp

Max I. Time

Max S. Time

Max P. Time NPV Inj Temp Prod. Rate NPV

Total NPV

Medium 0CSS+5SAGD N/A N/A N/A N/A 0.0 449.0 1.1 2507 2507.0

Heavy 2CSS+3SAGD 517 12.5 5.8 308 459 450.0 1.0 2068 2527

Figure 3-13 gives steam chamber development for the heavy oil case at the end of the 5-

year for the best NPV case of each timing scheme, which indicates how much oil is recovered by

the reservoir model. From the graphs, we can see that the schemes of 5-year SAGD, 1-year CSS

4year SAGD, and 2-year CSS 3-year SAGD all give the solid recovery of the oil as the green

blocks consist of the most model area. For the case of 3-year CSS 2-year SAGD and 4-year CSS

1-year SAGD, the chamber is relatively small and the oil is not recovered as fully as in the previous

cases. Also, this is shown in the cumulative oil production curves in Figure 3-11. This is the case

for all 5-year CSS as well. The figure shows a normal CSS chamber after several cycles of CSS

operation.

CSS 0yr SAGD 5yr CSS 1yr SAGD 4yr

29


CSS 4yr SAGD 1yr CSS 5yrs SAGD 0yrs

Figure 3-13 Chamber Development at the end of 5 year

3.3.2 Permeability studies

Besides the base case, two more types of reservoir permeability, the 500mD and 2000mD cases,

have been studied in this study to see the effect permeability causes to the total NPV. From the oil

and water production curves for these two permeabilities with all the timing schemes (Figure 3-

14), for oil production in the 500mD case, 1-year CSS 4-year SAGD gives the highest oil

production which is 150 bbl at the end of the five year simulation period; 2-year CSS 3-year SAGD

and 5-year SAGD give almost similar oil productions at about 142 bbl; the other time schemes

30

come lower than these schemes. The 2000mD case gives a more similar and closer oil production

value for the previous three time schemes, all close to 150 bbl, and the oil production grows faster

during the start part of the five-year period compared to the 500mD case.

Oil Production (500 mD) Water Production (500 mD)

Oil Production (2000 mD) Water Production (2000 mD)

Figure 3-14 Cumulative oil and water production for 500mD and 2000mD case

For water production, the 500mD case shows a more diverse curve trend compared to the

2000 mD case. The 1-year CSS 4-year SAGD generates the highest water production for about

1750bbl as the blue line of the water production curve shows. For the 2000mD case, 1-year CSS

4-year SAGD also gives the highest, with a little margin between it and the 5-year SAGD curve

which comes the second.

31

Except for the 5-years SAGD time scheme in the 500mD case, all the water production

curves for the SAGD part are horizontal to others for different time schemes, and compared with

the oil production curves, a water production curve is more straight as the water production rate

can remain at a relative constant level. The maximum total water production between the 500 mD

case and the 2000 mD case among all their time schemes are very close, to about 1750 bbl.

From the bar graph (Figure 3-15), the NPV contribution from SAGD and CSS is analyzed.

The 500mD case shows that the NPV generated by SAGD is higher than the NPV generated by

CSS for almost all the time schemes, and the NPV for SAGD and CSS both shows a declining

pattern as CSS years increase. For the case 2000 mD from CSS years of the total process increasing

to 3 years, the NPV for SAGD shows a rough increasing pattern while NPV for CSS shows a

decreasing pattern. For the comparison between the 2000 mD case and the 500 mD case, the 2000

mD can generate more NPV for either of their best time schemes for about $600 in total.

(a) (b)

0

500

1000

1500

2000

0 1 2 3 4 5

NPV

($)

CSSYears

500mD

CSS SAGD

0

1000

2000

3000

0 1 2 3 4 5

NPV

($)

CSSyears

1000mD(BaseCase)

CSS SAGD

32

(c) (d)

(e) (f)

Figure 3-15 Bar graph and total NPV vs CSS years for 3 permeability scenarios (a to f

from 500mD to 2000mD)

Table 3-4 Best time schemes for six cases for 500mD, 1000mD and 2000mD

CSS SAGD

Cases Time Scheme Inj Temp.

Max I. Time

Max S. Time

Max P. Time NPV Inj

Temp Prod. Rate NPV Total

NPV 500mD 0CSS+5SAGD N/A N/A N/A N/A 0 450.0 3.6 1614 1614

1000mD 0CSS+5SAGD N/A N/A N/A N/A 0.0 449.0 1.1 2507.0 2507.0 2000mD 3CSS+2SAGD 536 14 7.5 354 258 538.0 3.9 1970 2228

0

500

1000

1500

2000

2500

0 1 2 3 4 5

NPV

($)

CSSyears

2000mD

CSS SAGD

y=5.3214x2 - 386.29x+1672.8R²=0.95901

-500

0

500

1000

1500

2000

0 1 2 3 4 5

TotalN

PV($)

CSSyears

TotalNPVvs.CSS TimeLength(500mD)

y=-131.03x2 +279.58x+2284.2R²=0.79475

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5

TotalN

PV($

)

CSSyears

TotalNPVvs.CSSTimeLength(1000mD)

y=-284.38x2 +1188.1x+855.25R²=0.83786

0

500

1000

1500

2000

2500

0 1 2 3 4 5 6

TotalN

PV($)

CSSyears

TotalNPVvs.SAGDTimeLength(2000mD)

33

Figure 3-17 also shows the oil recovery performance in a view of the oil saturation graph

for each time scheme. For the 500 mD case, 1-year CSS 4-year SAGD can give the best oil

recovery as almost all the blocks turn green. 5-year SAGD and 2-year CSS 3-year SAGD can also

give a relatively decent oil recovery at the end of 5 years. For CSS time over 3 years, as the SAGD

time decreases, the steam chamber expansion area starts to shrink. For the 2000mD case and CSS

years below 3 years, the overall oil recovery is achieved. For 4-year CSS the oil recovery extent

decreases a lot. For all cases with 5-year CSS, both cases show absolute no recovery as for the 5

years all using the CSS method, CMOST is not able to generate an operation scheme to carry out

the recovery in a positive economical fashion, and, therefore, a non-injection-non production result

is given eventually.

From the figure between the total NPV value and the CSS years applied in the 5-year

simulation period of these three permeability scenarios (Figure 3-15, d to f), a trend line between

these two parameters is generated for each of the scenarios. For the case of 1000mD (base case),

as an example, using a 2-order polynomial trend line to simulate the relationship of the total NPV

and CSS years applied gives an equation of y = -284.38x2 + 1188.1x + 855.25 (R² = 0.8379, y:

total NPV value, x: CSS years). Using this equation and the solver tool of Microsoft Excel, the

maximum NPV value is reached at 2.09 CSS years, which means if the conversion from CSS to

SAGD happens after around the first month of the third year, the highest total NPV value is reached

for a better forecast.

A relationship between the different permeability and the CSS years adopted is also

analyzed. From the results of the best time scheme generating the total NPV value of each

permeability case (Table 3-4), a figure of permeability and the best CSS years adopted to switch

34

is drawn and a two-order polynomial trend line of these two parameters can also be generated

(Figure 3-16). Therefore, a prediction of the best conversion years from CSS to SAGD with

reservoir cases of other permeability values is forecasted at a rough level as well.

Figure 3-16 Case comparison for best NPV and CSS years (Permeability)

3.3.3 Formation Pay Zone Thickness

60 ft and 75 ft are the two more formation pay zone thickness levels studied besides the base case’s

45 ft. As the model volume is changed, the total recoverable oil volume is also changed compared

to the base case and some numbers of the analyzed parameters are varied.

The time scheme with the greatest total NPV in the 75 ft case is 2-year CSS 3-year SAGD

with the value of over $6300 (Table 3-5). 1-year CSS 4-year SAGD and all years with SAGD also

give a relatively closer NPV value. In the 60ft thickness case, the greatest NPV time scheme

appears at 1-year CSS 4-year SAGD, with all five years SAGD, 2-year CSS 3-year SAGD a close

NPV value as well.

The oil saturation graphs for the 75ft thickness level case at the end of the 5-year simulation

period for all the time schemes (Figure 3-20) also show the phenomenon illustrated above where

y=2E-06x2 - 0.003x+1R²=1

0

1

2

3

0 500 1000 1500 2000

CSSyears

Permeability(mD)BestCSSyrstoconvert

35

1-year CSS 4-year SAGD generates the most oil recovery.

500mD 2000mD

0-year CSS 5-year SAGD



36




Figure 3-17 Chamber development at the end of the simulation period of the best NPV case

37

(a) (b)

(c) (d)

(e) (f)

Figure 3-18 Bar graph and total NPV vs. CSS years three thickness scenarios (a to f)

0

1000

2000

3000

0 1 2 3 4 5

NPV

($)

CSSyears

45ft(BaseCase)

CSS SAGD

0

1000

2000

3000

4000

0 1 2 3 4 5

NPV

($)

CSSyears

60ft

CSS SAGD

0

2000

4000

6000

8000

0 1 2 3 4 5

NPV

($)

CSSyears

75ft

CSS SAGD

y=-131.03x2 +279.58x+2284.2R²=0.79475

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5

TotalN

PV($

)

CSSyears

TotalNPVvs.CSSTimeLength(45ft)

y=-246.95x2 +532.02x+3292.5R²=0.96883

0

1000

2000

3000

4000

0 1 2 3 4 5

TotalN

PV($)

CSSyears


y=-373.39x2 +740.19x+5567.8R²=0.90758

0

1000

2000

3000

4000

5000

6000

7000

0 1 2 3 4 5 6

TotalN

PV($)

CSSyears


38

Table 3-5 Results best time scheme cases of 45ft, 60ft and 75ft pay zone thickness scenario

CSS SAGD Thickness Time Scheme Inj

Temp. Max I. Time

Max S. Time

Max P. Time NPV Inj


NPV 45ft 0CSS+5SAGD N/A N/A N/A N/A 0.0 449.0 1.1 2507.0 2507.0 60ft 1CSS+4SAGD 550 12 18 160 612 449 6.5 3160.0 3772 75ft 2CSS+3SAGD 530 24.4 6.9 186 1908 450.0 2.0 4395 6303

For the single process’s NPV contribution, in the 75 ft pay zone thickness case, as CSS

years increase, SAGD’s consists of a less portion of the total NPV for each time scheme’s best

NPV case (Figure 3-18, c), while the CSS’s contribution got to a peak level at the 2yrs CSS case

and decreases as the CSS period time turns longer. Overall this proves that 2yr CSS and 3yr

SAGD can give a more balanced recovery for both processes in regards of NPV generated and

also generates the highest 5-year cumulative oil recovery.

Also, the trend line between the total NPV value and CSS years is generated for each pay

zone thickness scenario (Figure 3-18 d to f). For the scenario of 60 ft, an equation of y = -246.95x2

+ 532.02x + 3292.5 (R² = 0.9688, y: total NPV value, x: CSS years) is generated. Using this

equation, a more accurate switching time from CSS to SAGD is estimated as well, which accounts

for the influence of all the time schemes’ results. After solved by Excel, the maximum total NPV

is reached at CSS years of 1.08, meaning that switching to SAGD after the first month of the

second year can reach a maximum NPV value using this trend line approximation method. The

relationship between the best CSS years to convert to SAGD and the payzone thickness can also

be generated, and other payzone thickness scenarios’ best CSS conversion years is predicted as

well.

39

Figure 3-19 Case comparison for best NPV and CSS years (Thickness)

SAGD 5yrs CSS 1yr SAGD 4yrs CSS 2yr SAGD 3yrs

CSS 3yr SAGD 2yrs CSS 4yr SAGD 1yr CSS 5yr

Figure 3-20 Chamber development at the end of the simulation period (thickness)

y=0.0667x- 3R²=1

0

1

2

3

0 20 40 60 80BestCSSyearsto

con

vert(yr)

PayzoneThickness(ft)

CasecomparisonforbestNPVandCSSyears(PayzoneThickness)

BestCSSyrstoconvert

40

3.3.4 Well Spacing Study

Besides the base case’s 108 ft well spacing studied, two more well spacing levels are studied,

which are 198 ft and 288 ft, meaning that the half models are set to be 33 and 48 grid blocks in the

I direction, respectively. As the model’s total grid number in these two cases is more than in the

base case, the STARS simulation time for the sub-base case and the CMOST simulation will turn

longer overall, which will take about 3 hours per time scheme for CMOST’s optimization

simulation process. The best time scheme with the greatest NPV in the case of 198 ft is 0yr CSS

5yrs SAGD, for the value $2319 (Table 3-6), which means that for the best recovery performance

regarding NPV, no CSS operation is needed for well spacing of 198ft. 2 year CSS 3 year SAGD

can give a value of $2199, which is also a favorable value.

From the cumulative oil and water production curves over the 5 years period (Figure 3-21,

a, b), 1 year CSS 4 year SAGD can generate the highest oil cumulative oil production over the

five-year period for about 220 bbl. 5 year SAGD comes with a little margin behind. For the

cumulative water production, 1 yr CSS 4 year SAGD can give a number of 2100 bbl, which is

about 400 bbl over the 5yr SAGD and 2 year CSS 3 year SAGD cases.

(a) (b)

41

Figure 3-21 Cumulative oil and water production of 198ft well pair spacing (a: oil;

b: water)

From the bar graph in Figure 3-22, we can see that for the time scheme of SAGD 5 yrs,

the blue column is higher than the summation of the orange and blue columns for all other schemes.

For the case of 2yr CSS 3yr SAGD, the CSS generates more NPV than the SAGD portion, which

is unique among all other cases from the previous parameters analysis. For the spacing 288 ft case,

SAGD cannot generate oil production and it is all CSS process that can give a positive NPV.

108ft 198ft

288ft

Figure 3-22 NPVs for three well pair spacing levels (0+5; 1+4; 2+3; 3+2; 4+1; 5+0)

The cumulative oil production can also be shown from the chamber development figure.

Figure 3-23 shows the best NPV case’s oil saturation distribution at the end of the simulation

period. We can see that 1yr CSS 4yr SAGD can give the highest number of green blocks among

0

1000

2000

3000

0 1 2 3 4 5

NPV

($)

CSSyears

CSS SAGD

0

500

1000

1500

2000

2500

0 1 2 3 4 5

NPV

($)

CSSyears

CSS SAGD

0

1000

2000

3000

4000

NPV

($)

CSSyearsCSS

42

all other time regimes. All CSS 0yr SAGD 5yr to CSS 2yr SAGD 3yr can give a close performance

of oil recovery. From CSS 3yrs SAGD 2yrs to CSS 5yrs SAGD 0yrs, the oil saturation distribution

figure shows a classical steam chamber phase of the start of the SAGD process as well as the steam

chamber phase of the CSS process. They still deliver a solid amount of oil production, however,

inferior to the previous time regime of the 1yr CSS 4yr SAGD case.

Table 3-6 Results of best time scheme cases of 108ft, 198ft and 288ft pay zone thickness

CSS SAGD

Spacing Time Scheme Inj Temp.

Max I.

Time

Max S.

Time

Max P. Time NPV Inj


NPV

108 0CSS+5SAGD N/A N/A N/A N/A 0.0 449.0 1.1 2507.0 2507.0 198 0CSS+5SAGD N/A N/A N/A N/A 0 549 3 2319 2319 288 2CSS+3SAGD 546 25.3 11.1 286 3164 N/A N/A N/A 0

SAGD 5yrs CSS 1yr SAGD 4yr


43

CSS 4yr SAGD 1yr CSS5yr SAGD 0yr

Figure 3-23 Chamber development at the end of the simulation period of the best NPV case

3.4 Chapter Summary

Viscosity, permeability, formation pay zone thickness and well spacing all exert impacts on the

overall thermal recovery performance implemented by CSS and SAGD, and the switching time

point from CSS to SAGD.

1. For a viscosity effect, heavy oil will generate a less total NPV value for nearly all the

time scheme across the five-year simulation span. Also, for the CSS period, the light oil

case will generate a positive NPV for most time schemes, while in the heavy oil case only

the 2 years CSS 3 years SAGD will have a positive NPV value for the CSS period.

2. For a permeability effect, the 1000mD case can generate a highest total NPV across the

5-year simulation period among all three cases. Also, the potential cumulative oil and

water production is reached faster. At the same time, for the CSS period, higher

permeability cases can generate a greater NPV for relatively similar time schemes than

lower permeability cases.

3. For a pay zone thickness effect, the NPV for the CSS period takes a more portion as the

thickness increases. Also, the total NPV will increase as the thicker the reservoir is, the

more oil there is in place to recover.

44

4. For a well spacing effect, the total NPV of the CSS period takes more percentage when

spacing goes larger. Also, SAGD period’s NPV turns less as spacing increases.

5. The 2-order polynomial trend line relationship of the total NPV value and applied CSS

years for the total 5-year simulation period is generated, which is used to predict a switch

time up to months for accuracy. Also, the relationships of the values of permeability and

payzone thickness versus the applied CSS years is generated as well, which is used for

the prediction of the best switch time from CSS to SAGD for other values of permeability

and pay-zone thickness of reservoir cases.

45

Chapter Four: SAGD to CSS Processes

4.1 Introduction and simulation model

This chapter studies the reverse process, which gives a contrast group result to see whether the

recovery process from SAGD to CSS can give higher NPVs. This part of study also focuses on a

5-year simulation, from 2015 to 2020. Six timing schemes are arranged similar to the schemes

executed in the previous chapter: SAGD 0yrs CSS 5yrs, SAGD 1yr CSS 4yrs, SAGD 2yrs CSS

3yrs, SAGD 3yrs CSS 2yrs, SAGD 4yrs CSS 1yr, and SAGD 5yrs, and the reservoir parameters

are oil viscosity, permeability, formation pay zone thickness, and well pair spacing (the spacing

between two different well pairs).

4.2 Base Case Study

The perforation control of the simulation model is the same with the previous chapter’s process,

with the producer and injector of CSS in block (1,1,8) and the producer of SAGD to be in (1,1,15).

The injector of CSS is the same well with the injector of SAGD within the total 5 years. The

experiment case with the highest NPV is also generated by CMOST software simulation.

The pressure curve for this process is opposite to Chapter 3, as the SAGD process is implemented

prior to CSS (Figure 4-1). About 5 months’ time is required for the SAGD producing period as

the pressure needs to build up to about 470 psi to make the steam chamber growing consistently,

which is the preheating period of SAGD. The horizontal injector well’s pressure is also several psi

higher than the producer well’s pressure to make the oil between these two wells flow through. 2

cycles are generated for the two-year CSS period, and the pressure curve also illustrates a similar

pattern as in Chapter 3, showing an injection period of pressure build up, a soaking period of

46

pressure declining drastically and a production period of pressure declining slowly. The maximum

pressure in the CSS period is 600 psi which is in the injection period and the minimum about 80

psi in the production period.

Figure 4-1 Pressure control of the process SAGD to CSS (3yr SAGD 2yr CSS)

Figure 4-2 gives a typical oil production curve of the cases in this chapter, which is the

SAGD 3 yrs and then converted to CSS 2 yrs case. In the SAGD period, the oil production starts

normally about 4 months since the simulation starts as it takes time for the preheating process

between the horizontal injector and the producer. During this period, the reservoir fluid is heated

to be movable enough and the steam is able to progress under the SAGD operation pressure.

During the 3-year SAGD production, about 145 bbls of oil is recovered from the reservoir

model. For the oil rate, it grows up high since the steam builds the connection from the injector to

the producer with about 0.2 bbl/day. Over the 3 years the oil rate remains fluctuating with the

highest period to be 0.3 bbl/day.

47

SAGD period CSS period

Figure 4-2 Typical cumulative oil production curve

For the two years of the CSS period after the previous SAGD period, two cycles are

generated from the CMOST simulation process. As there is not much oil left in the reservoir model

and the CSS injection and production process is optimized by CMOST in regards to the best NPV

which means the steam injection is limited for less water cost, the oil recovery within the two

cycles is only about 0.7 bbl, much less than the total amount of the SAGD period’s recovery. The

highest oil rate is about 5.5 bbl/d, and only lasts a very short time which is also similar to the CSS

period of the recovery process of CSS switch to SAGD.

(a) (b)

Figure 4-3 Typical cumulative water production curve (a: SAGD; b: CSS)

48

For the water production, the first three years SAGD period delivers a stable water

production rate which is around 1 bbl/day (Figure 4-3, a). Therefore, the cumulative water

production shows a steady line increasing pattern, to about 1000 bbl at the end of three years.

For the latter 2 years CSS part, the highest water rate is about 1000 bbl/d and also lasts very

short. The cumulative water production for this two-cycle period accumulates to about 1100 bbl.

(a) (b)\

(c) (d)

(e) (f)

49

Figure 4-4 Chamber Chart of SAGD to CSS process (SAGD 3yrs + CSS 2yrs) (a to f. a: the

start of SAGD process; b: chamber expand of SAGD. c: Chamber reach the producer. d: At the

end of the SAGD period. e: After the first year of CSS. f: At the end of the Simulation period.)

The chamber phase growing chart can show the steam progressing level and give a direct view of

the oil recovery at different time points of this thermal progress. In the progress of SAGD to CSS,

the time scheme 3 year SAGD and 2 year CSS is used as an example. For thermal recovery to start

with SAGD, normally a preheating progress is needed to ensure that the injection steam can

advance through the viscous reservoir fluid and propel the oil out, recovering it from the production

well. In this study, the change for the oil saturation table becomes visible after about 3 months

after the simulation starts which shows that the preheating process is a fundamental process for

this SAGD part. The chamber then forms and starts to grow as the green blocks are increasing

through time (Figure 4-4.a). After the chamber reaches the horizontal producer which is seven

blocks below the injector, it grows horizontally in the I direction (Figure 4-4.b). After the SAGD

period is finished, almost all the original red blocks are replaced by the green blocks with only 2

layers of yellow or orange blocks at the bottom of the model which shows a decent recovery of the

SAGD process (Figure 4-4.c).

For the CSS process after the SAGD start at 2018-01-01, the chamber chart shows a very

small change to the overall oil saturation, which is of a significant difference to the CSS process

in Chapter 3. As in this sequence of thermal recovery, the SAGD process is predominant,

recovering most of the oil existing in this model. Also, to generate a best regime for the most NPV,

the CMOST module does not give the plan for most oil production in the CSS period as the steam

injection may cost more. For the time scheme of fewer SAGD years, such as SAGD 1yr CSS 4yr

50

and SAGD 2yr CSS 3yr, the chamber chart will show a more apparent pattern of the CSS chamber

view, compared to the case shown here.

4.3 Results and Discussion

This table shows the studied parameters of the recovery process from SAGD to CSS in this chapter,

which is exactly the same combination to show a better contrast with the results of the CSS to

SAGD process. The base case is also set to be medium viscosity, 1000mD for permeability, 45ft

pay-zone thickness, and 108ft well spacing, the same as in Chapter 3.

Table 4-1 Parameters for Sensitivity Analysis

Parameters

Viscosity Permeability Pay-zone Thickness Well

Spacing 500mD

Base Case Medium 1000mD 45ft 108ft Heavy 2000mD 60ft 198ft 75ft 288ft

4.3.1 Effect of Viscosity

The effect of viscosity is studied in the process of SAGD to CSS to verify whether there is a

difference between the process of CSS to SAGD on this parameter’s impact. For the first SAGD

part, the oil production curve of 5 years SAGD is in line with the time scheme of 4 years SAGD

and 1 year CSS (Figure 4-5, a). Also, the case is similar to 2yr SAGD 3yr CSS and 1yr SAGD 4yr

CSS, as well as 3yr SAGD 2yr CSS, where their SAGD oil production curves are nearly identical

for the overlapped SAGD year periods. For the CSS process in success of SAGD, the oil recovery

it contributes is much less consistent than the previous SAGD period within these six timing

schemes, which means that the CSS period’s effect for recovering oil is far less efficient than the

51

SAGD method.

(a) (b)

(c) (d)

Figure 4-5 Viscosity Effect on Cumulative oil and water production (3-yr SAGD + 2-yr

CSS, a to d. Upper oil, lower water. Right for heavy, left for medium. )

The bar graphs of the NPV values for these five time schemes, respectively, for CSS and

SAGD process’s contribution are also listed (Figure 4-6, a, b), for both the heavy oil case and the

base case. From the graph it is easy to identify that the SAGD process delivers more NPVs than

the CSS process executed after it for all the time schemes (except for the 5 years CSS scheme).

Also, to compare the NPVs between the heavy oil case and the base case, the base case can deliver

52

more NPVs for the same time scheme. Furthermore, to analyze the NPV for one thermal process

across these six time schemes, CSS’s NPV reaches the top at 1yr SAGD 4yr CSS, for both the

base case and the heavy oil case, and SAGD’s NPV reaches the top at 4yr SAGD 1yr CSS for the

base case and 3yr SAGD 2yr CSS for the heavy oil case.

(a) (b)

Figure 4-6 bar graph of NPVs for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0. a: medium, b:

heavy)

Table 4-2 gives data values of the operation parameters CMOST generated during its

optimization simulation as well as the total NPV of each time scheme. For the highest NPV of the

base case which is the 4yr SAGD 1yr CSS scheme, the steam injection temperature in the SAGD

period that CMOST generates is 449F, with the production rate of 1.0 bbl/d, and the steam injection

temperature in the CSS period is 354F with the maximum injection time, soak time and production

time to be 30, 10, and 446 days (Table 4-2.1), respectively. For the heavy oil case’s highest NPV

scheme, 3 yr SAGD 2yr CSS, the steam injection temperature for SAGD is 548F and producer’s

production rate is 2.5 bbl/d; the steam injection temperature for CSS is 350F, with the maximum

injection period time, soaking period time and production period time to be 13, 6 and 100 days

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5

NPV

SAGDTimePeriod

SAGD CSS

0

500

1000

1500

2000

2500

0 1 2 3 4 5

NPV

SAGDTimePeriod

SAGD CSS

53

(Table 4-2.2), respectively.

Table 4-2 Results for six cases (0+5; 1+4; 2+3; 3+2; 4+1; 5+0)

1000mD Medium Oil SAGD CSS Total

SAGD years Years Inj

Temp Prod. Rate NPV Inj

Temp. Max I. Time

Max S. Time

Max P. Time NPV

0 0SAGD+5CSS N/A N/A 0 501 18 11.7 430 305 305 1 1SAGD+4CSS 550.0 2.5 636 350 11.5 11 438 413 1049

2 2SAGD+3CSS 550.0 1.8-3.8 1834 350 30 8.8 326 281 2115

3 3SAGD+2CSS 549.0 2.7-3.5 2653 350 19.4 6.2 418 5 2658

4 4SAGD+1CSS 449.0 1.0 2701 354 30 10 446 7 2708 5 5SAGD+0CSS 449.0 1.0 2432 N/A N/A N/A N/A 0 2432

Base Case (Table 4-2.1)

1000mD Heavy Oil SAGD CSS Total



Temp. Max I. Time

Max S.

Time

Max P.

Time NPV

0 0SAGD+5CSS N/A N/A 0 N/A N/A N/A N/A 0 0 1 1SAGD+4CSS 547.0 3.0-3.7 405 350 5 12 368 65 470 2 2SAGD+3CSS 548.0 2.1-3.3 960 350 18 8 350 49 1009 3 3SAGD+2CSS 548.0 2.5 2047 350 13 6 100 8 2055 4 4SAGD+1CSS 450.0 3.5 1536 400 25 7 400 2 1538 5 5SAGD+0CSS 450.0 2.0 565 N/A N/A N/A N/A 0 565

Heavy Oil Case (Table 4-2.2)

The steam chamber developing phase graphs (Figure 4-7, a to l, and also Oil Saturation

Distribution graph) are also generated from the simulation software module. The oil saturation

scale is the same as the chamber development graph in Chapter 3, in which green color indicates

the oil saturation of 0.1 in the specified block and red color indicates the oil saturation of 0.6.

54

Visc Medium (Base)

(a) SAGD 0yrs CSS 5yrs (b) SAGD 1yr CSS 4yr

(c) SAGD 2yr CSS 3yr (d) SAGD3yr CSS2yr

55

(e) SAGD4yr CSS1yr (0.7 scale) (f) SAGD 5yrs CSS 0yrs

Visc Heavy

(g) SAGD 0yrs CSS 5yrs (h) SAGD 1yr CSS 4yr

(i) SAGD 2yr CSS 3yr (j)SAGD3yr CSS2yr

56

(k) SAGD4yr CSS1yr (0.7 scale) (l) SAGD 5yrs CSS 0yrs

Figure 4-7 Chamber development at the end of 5-year graph

From the number of the green blocks shown in the graphs for both cases, the more time period of

the SAGD process taken, the greener blocks generated by the simulation. For the base case whose

viscosity is less than in the heavy oil case, the 5 yr SAGD 0 yr CSS time scheme has the greenest

blocks, which proves that this time scheme generates the most oil out of all the time schemes. The

greatest NPV scheme, 4yr SAGD 1yr CSS scheme also has a decent number of green blocks

compared to the 5yr SAGD 0yr CSS scheme, as the steam injection is less than in the 5yr SAGD

scheme; it delivers a better NPV performance.

For the case of the heavy oil model, the 3yr SAGD 2yr CSS scheme has the greatest NPV

than other time schemes though the number of green blocks of this scheme is less than 4yr SAGD

1yr CSS and 5yr SAGD 0yr CSS for an apparent margin.

4.3.2 Effect of Permeability

500 mD and 2000 mD are the two levels of permeability studied in the SAGD to CSS process,

which is the same as in Chapter 3. After the CMOST module carried out the optimization of a

57

NPV experimental analysis, 6 time schemes’ best NPV experiments are generated with its

cumulative production of oil and water within the 5 years’ simulation range for these two

permeabilities (Figure 4-8, a to d).

500mD Oil & Water 2000mD Oil & Water

(a) (b)

(c) (d)

Figure 4-8 Cumulative oil and water production of 500mD and 2000mD (a to d)

In the 500 mD case, the 5 years SAGD scheme gives the most oil production at the end of

the simulation period (red line). 4yr SAGD 1yr CSS comes second with approximately 10 bbl less

58

than in the 5 years SAGD case. Other time schemes’ oil production curves are shown in Figure 4-

8.1 with all 5 year CSS scheme comes the lowest oil production. For the start time of recovery,

the 5 years SAGD gives the latest oil recovery, which is at the time of about 2015.7, while 1yr

SAGD 4yr CSS gives the fastest oil recovery, which is about 2015.2.

For the case of 2000mD, 4 yr SAGD 1yr CSS (green curve) and 3 yr SAGD 2 yr CSS (blue

curve) deliver an almost equal oil production at the end of the simulation period, which is

approximately at 150 bbl indicated by the blue line and the green line, respectively (Figure 4-8

.b). 2yr SAGD 3yr CSS and 5yr SAGD deliver a lower amount than them, which is about 10 bbl

and 15 bbl less. The time scheme with the most oil production in the 2000mD case is also about

10bbl more than the most oil production scheme in the previous 500mD case, and generates much

faster oil across the 5 years’ simulation period among all the six time schemes.

For the water production, the time schemes of 4yr SAGD and 1yr CSS deliver the most

with around 1100bbl in the 500 mD case (Figure 4-8, c). The 5yr SAGD scheme and the 2yr SAGD

3yr CSS scheme produce around 1000bbl of water. The time scheme of the least water production

is 1yr SAGD 4yr CSS, for around 250bbl of water production. For the 2000mD case, overall all

the schemes of cumulative water production give an equal or more water production compared to

the previous 500 mD case with 3yr SAGD and 2yr CSS for the most at about 1450bbl and 1yr

SAGD 4yr CSS and 5yr CSS at around 450bbl of cumulative water production.

For the case of the best overall NPV and the contribution of each thermal process, the 5yr

SAGD scheme can give the most NPV compared to other time schemes in the case of 500 mD at

around $1900 (Figure 4-9.1, Table 5), while for the case of 2000mD, 2yr SAGD 3yr CSS can

generate the most NPV among all time schemes at about $3700 (Figure 4-9.2, Table 5). For the

time scheme of 1yr SAGD 4yr CSS in the 2000 mD case, the CSS process can generate NPV at

59

around $1600, which is higher than by the SAGD portion. For all other time schemes across the

two permeability cases, the SAGD process generates much more NPV than its latter CSS process.

Table 4-3 illustrates the operation parameters for these best experiments of each time scheme

across the two permeability cases.

500mD 2000mD

(a) (b)

(c) (d)

Figure 4-9 Bar graph of NPVs for six time schemes of 500mD and 2000mD cases(a to d)

Table 4-3 Results for six cases for 500mD and 2000mD (0+5; 1+4; 2+3; 3+2; 4+1; 5+0)




Temp. Max I. Time

Max S. Time

Max P. Time NPV

0 0SAGD+5CSS N/A N/A 0 492 15.375 8.85 433 342 342

y=29.804x2 +230.67x+130.96

0

500

1000

1500

2000

0 1 2 3 4 5

TotalN

PV

SAGDTimePeriod

0

1000

2000

3000

4000

0 1 2 3 4 5

TotalN

PV

SAGDTimePeriod

0

500

1000

1500

2000

0 1 2 3 4 5

NPV

SAGDTimePeriodSAGD CSS

0

1000

2000

3000

4000

0 1 2 3 4 5

NPV

SAGDTimePeriodSAGD CSS

60

1 1SAGD+4CSS 543.0 1.8 7 400 12.5 12 100 0 7 2 2SAGD+3CSS 546.0 2.3 617 570 8 8.4 435 107 724 3 3SAGD+2CSS 488.0 3.3 1260 400 5 8.4 350 -10 1250 4 4SAGD+1CSS 547.0 3.9 1640 433 25 4.4 431 18 1658 5 5SAGD+0CSS 567.0 2.32 1904 N/A N/A N/A N/A 0 1904

500 mD




Temp. Max I. Time

Max S. Time

Max P. Time NPV

0 0SAGD+5CSS N/A N/A 0 490 27.6 7 450 210 210 1 1SAGD+4CSS 550.0 2.65 1466 312.5 18.25 9.2 231.6 1626 3092 2 2SAGD+3CSS 547.0 2.78 3661 300 18 10.5 450 30 3691 3 3SAGD+2CSS 546.0 3.16 2252 318 2 3.8 400 -4 2248 4 4SAGD+1CSS 453.0 1 2287 310 25 11 271 0 2287 5 5SAGD+0CSS 448.0 1.255 2415 N/A N/A N/A N/A 0 2415

2000 mD

The chamber development for the 500mD and 2000mD cases for most time schemes is

more distinct between each other than in other parameters chamber development differences,

showing that the fewer SAGD years implemented within the 5 years’ period, the more different

the simulation results are (Figure 4-10, a to l).

For the time scheme of 5yrs SAGD, both the 500mD and 2000mD cases have a decent

number of green blocks in their chamber progression figures, respectively, as the steam chamber

almost takes up all the simulation volume. Starting from 4yr SAGD 1yr CSS, the difference

between 500mD and 2000mD becomes distinct. The lower part of 500mD shows more orange

colour for the blocks, while for 2000mD the lower part’s blocks show green colour. For 3yrs

SAGD 2yrs CSS and 2yrs SAGD 3yrs CSS, the steam chamber green blocks become less

significant for the 500mD case while for 2000mD the green blocks still remain a large volume.

For 1yr SAGD 4yr CSS and 0yr SAGD 5yr CSS, both the 500mD and 2000mD cases have more

61

red or orange blocks than green blocks, and show the pattern shape of a round circle around the

injector well, which more resembles as the classical CSS process steam chamber shape.

500mD 2000mD SAGD 5yrs

(a) (b)

SAGD 4yr CSS 1yr

(c) (d)

62

SAGD 3yr CSS 2yr

(e) (f)

SAGD 2yr CSS 3yr

(g) (h)

SAGD 1yr CSS 4yr

63

(i) (j)

SAGD 0yr CSS 5yr

(k) (l) Figure 4-10 Chamber development at the end of simulation period of 500mD and 2000mD

(a to l)

Overall for the 5-year simulation period, the 2000mD case shows more steam progression

and coverage than the 500mD case for all the time schemes. Also, when the CSS time period is

less than 4 years, the figure shows a more SAGD chamber-like shape, with a green blocks funnel-

like shape end to the producer well at the bottom. For the CSS period equal to or more than 4 years,

the shape of the steam chamber turns to an injector well centered shape and the green blocks

64

become much fewer than in the previous time schemes, as the overall 5 years thermal process is

more dominated by the CSS process.

4.3.3 Effect of Well Spacing

A well spacing effect is studied here to see the influence it exerts on different time schemes of the

SAGD to CSS process. 198 ft and 288 ft are two levels of well spacing that are studied.

From oil and water cumulative production curves generated by CMOST simulation results, the

198 ft well spacing case shows that for the process of the SAGD part, all time schemes’ curves

are in line with each other (Figure 4-11 a, b). The CSS process continues to progress after the

SAGD process ends for each time scheme and for the SAGD period more than or equal to two

years for the best NPV case, only one cycle is generated for the CSS period from the CMOST

optimization, both for the oil and water cumulative production curves. For the time scheme

where the SAGD period is less than two years, no oil production is generated from the SAGD

process. Overall the time scheme with the most oil or water cumulative production is the SAGD

5yrs, for about 205 bbl. and 1700 bbl. respectively.

198ft 288ft

Oil

(a) (b)

65

Water

(c) (d)

Figure 4-11 Cumulative oil and water productions for well spacing of 198ft and 288ft

(a to d)

For the 288 ft case, there is no production from the SAGD period for all six time

schemes. The scheme for most oil production and most water production are both SAGD 2yrs

CSS 3yrs (Figure 4-11 c, d) with the amount of around 125bbl and 980bbl, respectively. Three

cycles of the CSS period are generated from the best NPV case of the CMOST simulation. For

the time scheme of 5yrs CSS or 5 yrs SAGD, no production curves are acquired for positive

NPV numbers.

(a) (b)

0

500

1000

1500

2000

2500

0 1 2 3 4 5

NPV

SAGDyears

198ft

SAGD CSS

0

500

1000

1500

2000

2500

0 1 2 3 4 5

NPV

SAGDyears

288ft

SAGD CSS

66

(c) (d)

Figure 4-12 Spacing of 198ft and 288ft spacing NPV simulation results (a to d)

Figure 4-12 shows the maximum NPV number and the operation parameters related to

each time scheme in these two cases. For the 198 ft spacing case, 5 years SAGD gives the

greatest NPV with the value of $2318 (Figure 4-12. a). For 288 ft spacing, 3yr SAGD 2yr CSS

gives the greatest value of $1506. Also, Figure 4-12 shows that the total NPV has an increasing

pattern as the time of the SAGD period increases in the 198 ft case. For the 288ft case the total

NPV peaks at the SAGD period equal to 3 years.

From the chamber shape shown in Figure 4-13, it shows a similar case to the previous

permeability parameter analysis. For the 198ft, the number of green blocks is decreasing as the

SAGD period becomes shorter, and its shape becomes closer to CSS process’s shape. For the

288ft, as there is no time scheme containing SAGD production from the CMOST simulation

results from CSS 1yr to 4yrs, all the figures show a CSS-like chamber, and the shape of the

chamber is larger as the CSS years increase from 1yr to 4yr. For the time scheme of CSS 5yrs

and SAGD 5yrs, as no positive NPV number is generated from all producing experiments after

0

500

1000

1500

2000

2500

0 1 2 3 4 5

TotalN

PV($)

SAGDyears

TotalNPVvs.SAGDTimeLength(198ft)

0

500

1000

1500

2000

2500

0 1 2 3 4 5

TotalN

PV($)

SAGDyears


67

CMOST carried out its simulations, the original oil saturation is shown with no steam chamber

generated.

198ft 288ft

SAGD 5yrs CSS 0yrs

SAGD 4yrs CSS 1yr

SAGD 3yrs CSS 2yrs

68

SAGD 2yrs CSS 3yrs

SAGD 1yr CSS 4yrs

SAGD 0yrs CSS 5yr

Figure 4-13 Steam chamber phase progression for 198 ft and 288 ft

4.3.4 Effect of Payzone Thickness

60 ft and 75 ft are the two levels of thickness that are analyzed for the payzone thickness effect

besides the 45ft base case. From the bar graph analysis (Figure 4-14, c), for the 60 ft thickness

case, the NPV value of the SAGD part shows an increasing pattern as SAGD years increase to 3

years. After SAGD reaches 3 years, the NPV of SAGD decreases from CMOST simulation

experiments.

69

Table 4-4 Simulation Results of 60ft and 75ft thickness level (upper 60ft; lower 75ft)

SAGD CSS SAGD years Years Inj Temp Prod.

Rate NPV Inj Temp.

Max I. Time

Max S. Time

Max P. Time NPV Total

NPV 0 0SAGD+5CSS N/A N/A 0 N/A N/A N/A N/A 0 0 1 1SAGD+4CSS 548.0 6.2 560 350 5.3 12 404 880 1440 2 2SAGD+3CSS 548.0 4.6 2304 350 20.5 7.1 288 610 2914 3 3SAGD+2CSS 547.0 5.7 4668 350 26 6 176 0 4668 4 4SAGD+1CSS 457.0 6.5 4172 350 10 6 150 0 4172 5 5SAGD+0CSS 450.0 5.0 3219 N/A N/A N/A N/A 0 3219

SAGD CSS SAGD years Years Inj


Temp. Max I. Time

Max S. Time

Max P. Time NPV Total

NPV 0 0SAGD+5CSS N/A N/A 0 530 29 10.6 350 430.6 430.6 1 1SAGD+4CSS N/A N/A 0 511 22 10.5 342 1006 1006 2 2SAGD+3CSS 550.0 2.6 2028 350 30 12 378 1407 3435.1 3 3SAGD+2CSS 550.0 3.0 5841 N/A N/A N/A N/A 0 5841 4 4SAGD+1CSS 550.0 3.2 6201 N/A N/A N/A N/A 0 6201 5 5SAGD+0CSS 450.0 2.4 5404 N/A N/A N/A N/A 0 5404

For the 75 ft thickness case, the NPV value of SAGD becomes positive after 2 years of

SAGD, and shows an increasing manner to SAGD time of 4 years (Figure 4-14, d). The NPV for

the CSS period also increases before SAGD reaches the third year. Overall, the 4yr SAGD 1yr

CSS scheme generates the highest NPV among all the schemes from CMOST simulation results.

70

(a) (b)

(c) (d)

Figure 4-14 Bar graphs and total NPV with CSS years of 60ft and 75ft thickness level.

For the steam chamber progression in the 75ft thickness case (Figure 4-15, a to f), SAGD

shows good performance for the time schemes when the SAGD period is over 2yrs. For other time

schemes, the saturation figure shows more of CSS characteristics and less oil is recovered

compared to the previous time schemes. For the 5 years SAGD schemes, 75 ft case shows a

thorough recovery, showing this pay zone thickness has a low limit for the SAGD process to carry

0

1000

2000

3000

4000

5000

0 1 2 3 4 5

TotalN

PV($)

SAGDyears


01000200030004000500060007000

0 1 2 3 4 5

TotalN

PV($)

SAGDyears


0

1000

2000

3000

4000

5000

0 1 2 3 4 5

NPV

SAGDyears

60ft

SAGD CSS

0

2000

4000

6000

8000

0 1 2 3 4 5

NPV

SAGDyears

75ft

SAGD CSS

71

out.

(a) SAGD 5yrs CSS 0yrs (b) SAGD 4yrs CSS 1yr (c) SAGD 3yrs CSS 2yrs

(d) SAGD 2yrs CSS 3yrs (e) SAGD 1yr CSS 4yrs (f) SAGD 0yr CSS 5yr

Figure 4-15 Steam chamber growth of thickness 75ft at the end of 5 years (a to f)

4.4 Chapter Summary

This chapter illustrates the outcomes that SAGD simulation is implemented first and then

converted to the CSS method for the entire 5 years simulation period. Overall several points is

generated from the simulation results:

According to all various scenarios, it is better to implement SAGD at least 3 years to produce the

greatest NPV for the simulation model for all the six time schemes analyzed. Effects of analyzed

parameters exert in the NPV results:

1. Permeability: Increasing of permeability can increase the NPV value in regards to the same

72

time scheme (except for 5 years CSS). Compared to the CSS to SAGD process in the

previous chapter, theSAGD to CSS process delivers a higher NPV for the highest time

schemes.Viscosity: For each time scheme in the SAGD to CSS process, heavy oil’s NPV

result is lower than the counterpart of the medium oil NPV result, which indicates that a

viscosity increase leads to a decrease in the overall NPV performance. Compared to the

CSS to SAGD process, SAGD to CSS takes advantage in the medium oil scenario for the

maximum NPV time scheme, while CSS to SAGD reaches a better NPV for the heavy oil

scenario.

2. Payzone thickness: for the three different scenarios of thickness analyzed for the total NPV

value, the SAGD to CSS process takes advantage in the 45 ft and 60 ft thickness levels by

a relatively big margin (4yr SAGD 1yr CSS vs. 1yr CSS 4yr SAGD for 45ft thickness, 4yr

SAGD 1yr CSS vs. 1yr CSS 4yr SAGD for 60ft thickness), while CSS to SAGD takes

advantage in the 75 ft level(2yr CSS 3yr SAGD vs. 4yr SAGD 1yr CSS).

3. Well spacing: CSS takes more NPV percentage as the well pair spacing increases from 108

ft (the base case) to 288 ft. At the 288 ft level, only CSS can generate a positive NPV value,

which is similar to the previous chapter’s results. Also, taking the well grids into account,

as the 198 ft level’s total NPV is greater than 108ft’s for most time schemes, the 5 years’

total NPV generated per reservoir volume will decrease as the well pair spacing increases.

73

Chapter Five: Case Study

5.1 Introduction

This chapter focuses on simulation of a field model of a heavy oil reservoir, which uses the similar

approach of CSS to SAGD and SAGD to CSS processes with all six timing schemes adopted in

the previous chapters’ analysis, and a rough comparison is made between the results of this field

case model and previous homogeneous models. The NPV value of each single thermal process as

well as the total NPV value for all the timing schemes are generated as well.

The previous two chapters illustrate the best optimization timing scheme under different

reservoir parameters. This chapter investigates the validity of the optimization scheme in a real

heavy oil reservoir. The geological model is from Liaohe Oilfield in China, which is of a different

kind from the previous chapters’ models as it is a heterogeneous model.

Figure 5-1 Case Model

The heavy oil reservoir model has 12×14×8 grids. It is a deep heavy oil reservoir with an

average depth of 1340 meters. The oil saturation of every blocks of this model ranges from 0.47

74

to 0.75, the average pay zone thickness is 15 meters, and permeability ranges from 800 mD to

1000 mD horizontally, 70 mD to 300 mD vertically, and 80 mD to 100 mD for the most middle

part. The viscosity of oil in this reservoir is around 5000 mPa.s at reservoir situations. Horizontal

well pair spacing is around 70 meters.

The shape of the reservoir is declining downwards, and two horizontal wells are located in

this reservoir, with the upper well used as both the CSS well and SAGD injectors, and the lower

well as SAGD horizontal producers. Due to the decline, the two well trajectories and perforations

are not fully overlapped horizontally in the JK plane. More information of the reservoir model is

listed below (Table 5-1).

Table 5-1 Data of Liaohe field model

Average IJ Cross-section area (m) 100*70 Length (m) 100 Porosity (%) 0.178-0.247 Horizontal Permeability, k (mD) 800-1000 Vertical Permeability, k (mD) 80-300 Reservoir temperature, T (C) 50C Surface pressure, Psc (kPa) 1.01325*102 reservoir pressure (kPa) 1800 Dead oil viscosity (mPaS, at 30°C) 9926 Dead oil density (g/cm3) 0.987 Oil Saturation, So (vol.%) 0.52 Oil Thickness(average, m) 15 Depth (m) 1320-1356

The history match is also carried out between the simulation results of the original placed injectors

and producers of this model with the original production history for the previous 16 years (year

1993-2009). From the results of the field cumulative oil production (Figure 5-2), it can be seen

that the simulation result for most of the period gives a good match of the production history, in

75

terms of its trend and the cumulative oil number, which proves its validity of this field model’s

petrophysical properties for further studies.

Figure 5-2 Field Model History Match

Overall, the reservoir properties are covered in the case studies in Chapters 3 and 4:

medium oil viscosity, permeability of 1000 mD, well spacing of 198 ft, and payzone thickness of

45ft. Therefore, conclusions from the previous chapters is referred to determine the operating

scheme.

5.2 Field Case Simulation Process

The goal of doing this Liaohe field model simulation is to show that the screening method for the

best timing scheme to convert from CSS to SAGD in this thesis delivers a better economic value

than the scheme used normally in field operations.

During heavy oil operations, CSS operations are frequently used as initial stage thermal

methods prior to other methods as it is relatively more applicable. When the economic limit is

reached, CSS operations is terminated and a follow-up recovery method is applied, such as SAGD.

76

In this thesis, the CSS termination point is altered in an overall view of the total five-year recovery

period to increase the economic outcome to the maximum amount.

In order to set the termination criteria of CSS operation, the economic profit is analyzed.

For this analysis, each month is used as a timing unit and each CSS cycle is regarded as one

evaluation timing period to calculate the Net Present Value (NPV). If one evaluation timing

period’s NPV turns from a previous positive value to a negative value, this cycle’s timing implies

that the CSS operation should be terminated and it is the timing to switch to the SAGD process.

NPV is analyzed in the equation below.

𝑁𝑃𝑉 𝑖, 𝑁 = 34567 4

89:; (5-1)

𝑁 – Total number of periods (in this case it is the total months in the five year simulation period)

𝑡 – Timing of the cash flow (In this case it is the month’s number)

𝑖 – Discount rate (a monthly discount rate is used, converted from 0.1 yearly discount rate which

used in CMOST is 0.007)

𝑅9 – Net cash flow (oil revenue – water cost) at month t (60$/bbl adopted for the oil price, 5$/bbl

for the water price)

It is assumed that CSS is the method that field operations are going to carry out for the total

five years of the studying period, and, therefore, the CMOST module is utilized for the five-year

CSS timing scheme to find the best case available for CSS operations. The cycle in which NPV is

generated indicates within which cycle NPV starts to turn from a positive value to a negative one.

When a negative value emerges, the cycle is considered to be termination timing.

In this reservoir model, after simulation using CMOST for the 5-year CSS and 0-year

SAGD scheme, 5 cycles are generated. All the present value is carried out for each cycle (Table

77

5-2), and cycle 4 is the one in which the NPV value starts to turn negative. So, based on the

previous assumption, Cycle 4 should not be executed in field operations and CSS should be

terminated at the third year. Therefore, 3-year CSS and 2-year SAGD is the timing scheme that

should be adopted in field operations.

Table 5-2 NPV calculation data results for each CSS cycle

Cycle Num Month

Num. of Months

Oil Production By month (bbl)

Water Injection By month (bbl)

NPV for the Month ($)

Cycle NPV ($)

Cycle 1 9/16 1 0.0 1272.0 -6310 5584 10/16 2 201.4 11893

Cycle 2 9/17 13 0.0 1278.0 -5763

1522 10/17 14 126.8 6809 11/17 15 8.9 477

Cycle 3 9/18 25 0.0 1308.3 -5363

155 10/18 26 0.0 0 11/18 27 114.0 5518

Cycle 4 10/19 38 0.0 1395.4 -5159 -74 11/19 39 115.5 5085

Cycle 5 10/20 50 0.0 1522.8 -5119

-377 11/20 51 91.3 3654 12/20 52 27.4 1087

5.3 CSS to SAGD results

In this field case model study, all the six timing schemes is analyzed and optimized for the best

NPV scheme based on the total five-year period using the CMOST module. During the CSS

period, the injector bottom hole pressure is set to be 5000 kPa, and the producer bottom hole

pressure is 1000 kPa. The CSS simulation process is carried out first for each timing scheme, and

then we use the best optimized CSS case’s operation parameter of each timing scheme to

continue the remaining period’s SAGD process optimization to finally acquire the overall five

years’ total NPV results.

78

According to the simulation results (Table 5-3, Figure 5-3), the 1-year CSS and 4-year

SAGD scheme outperforms other schemes for the total NPV value, which reaches $17259. 2-

year CSS and 3-year SAGD also gives a good performance of $16522, all higher than the

scheme (3-year CSS and 2-year SAGD) that is commonly applied in the field.

Table 5-3 NPV table for different timing schemes from CSS to SAGD

CSS SAGD CSS years

Timing Schemes

Inj Temp.

Max I. Timing

Max S. Timing

Max P. Timing NPV Inj


NPV 0 0CSS+5SAGD N/A N/A N/A N/A N/A 306.2 9 15196 15196 1 1CSS+4SAGD 312.5 16.5 12 50 9763 312 8.8 7496 17259 2 2CSS+3SAGD 312.5 27.4 5.6 116 9355 310.6 8.1 7167 16522 3 3CSS+2SAGD 312.5 29.6 12 192 8755 306.8 6.4 5032 13787 4 4CSS+1SAGD 311.3 29.1 11.6 328 7903 312.5 9 3734 11637

5 5CSS+0SAGD 312.5 30 8.8 338 7205 N/A N/A N/A 7205

Figure 5-3 Total NPV vs. CSS timing and Bar values of CSS and SAGD process

Also, the trend line analysis method is utilized in this field case study. An equation of y =

-680.84x2 + 1702.6x + 15586 (R² = 0.9815, y: total NPV value, x: CSS years) is generated by

Microsoft Excel and using its solver function, and the maximum NPV value is reached at 1.25 year

y=-680.84x2 +1702.6x+15586R²=0.98149

0

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12000

16000

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0 1 2 3 4 5 6

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CSSyears(yr)

TotalNPVvs.CSSTiming

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0 1 2 3 4 5

NPV

($)

CSSyears(yr)

CSS SAGD

79

of the CSS process, indicating that to implement the CSS to SAGD conversion at around 3 months

during the second year has a better chance to reach the maximum value of the total NPV.

Compared with the corresponding case of the homogeneous model in Chapter 3 (Section

3.3.4, 198ft well spacing), this case shows a certain grade of similarity on the shape of the bar

graph, especially for the first 4 timing schemes from all five years SAGD to 3-year CSS and 2-

year SAGD (Figure 3-21, b). Both cases have a relatively high value of the total NPV for all five

years SAGD and the 2-year CSS and 3-year SAGD timing scheme. Compared with other scenarios

in Chapter 3 with different viscosity, permeability and pay-zone thickness, in both cases the CSS

process consists of a higher percentage of the total NPV value, which all indicates a certain

resemblance between these two cases.

5.4 SAGD to CSS results

The SAGD to CSS process is also analyzed on this reservoir model, similar to the procedures in

Chapter 4, with timing schemes of all five years executing CSS, 1year SAGD 4year CSS to 5years

all executing SAGD. From the simulation results (Table 5-4, Figure 5-4), 4-yr SAGD 1-yr CSS

generates the highest NPV at a value of $29319, and as the SAGD year increases within the five-

year period, the NPV value increases in a line fashion. It is also noticed that 4-yr SAGD 1-yr CSS

can generate more NPV than any other timing schemes in this case study.

Compared to results in Chapter 4, the NPV of CSS of total 5-year for each timing scheme

is very close, of series of viscosities, permeabilities, pay zone thicknesses, and well spacing.

Table 5-4 NPV table for different timing schemes from SAGD to CSS

SAGD CSS SAGD years

Timing Schemes

Inj Temp

Prod. Rate NPV Inj

Temp. Max I. Timing

Max S. Timing

Max P. Timing NPV Total

80

0 0SAGD+5CSS N/A N/A N/A 312.5 30 8.8 338 7205 7205 1 1SAGD+4CSS 305 6.2 7507 187.5 30 9.4 50 6527 14034 2 2SAGD+3CSS 312.5 9.9 16881 187.5 17.5 7.2 350 2159 19040 3 3SAGD+2CSS 312.5 9.9 22531 187.5 24.8 10 114 2311 24842 4 4SAGD+1CSS 312.5 9.4 25762 204 18.3 6.8 418 3557 29319 5 5SAGD+0CSS 306.2 9 15196 N/A N/A N/A N/A N/A 15196

Figure 5-4 Total NPV vs. SAGD timing and bar values of SAGD to process

Also, the trend line analysis method is utilized in this SAGD to CSS process of the field

model case study to account for the influence of other timing schemes’ total NPV results. An

equation of y = -1908.5x2 + 12160x + 5367.3 (R² = 0.8105, y: total NPV value, x: SAGD years)

is generated. In this case, the maximum NPV value is reached after implementing SAGD for

3.18 years, which means that the conversion point from SAGD to CSS is reached at the second

month of the fourth year within the 5-year simulation period. For the resemblance with the

previous 198ft well spacing homogeneous case of SAGD to CSS (Section 4.3.3 in Chapter 4),

there exists some major difference in the timing scheme of one year SAGD four years CSS, and

the five year SAGD timing scheme, but overall the similarity still remains as the SAGD and CSS

both takes up a certain amount for the other timing schemes.

y=-1908.5x2 +12160x+5367.3R²=0.810530

10000

20000

30000

40000

0 1 2 3 4 5

TotalN

PV($)

SAGDTimingPeriod(yr)

TotalNPVvs.SAGDTiming

0

10000

20000

30000

40000

0 1 2 3 4 5

TotalN

PV($

)

SAGDTimingPeriod(yr)

SAGD CSS

81

5.5 Summary

Though some major discrepancies between each other exist, the overall results show the

rationality and feasibility of the NPV analysis method that was adopted throughout this chapter.

For the CSS-to-SAGD process, using this optimization method can find the best timing scheme

that gives a better switching point from CSS to SAGD to generate more revenues than that

adopted in field operations.

Also, for SAGD-to-CSS, 4-year SAGD and 1-year CSS can generate the largest NPV for all the

timing schemes, with SAGD contributing to most of the NPV.

The conclusions from CSS-to-SAGD with homogeneous models are worthy of referring to for

real heterogeneous cases.

82

Chapter Six: Conclusions and Recommendations

6.1 Conclusions

This thesis implemented the analysis of the CSS to SAGD process in a thin sliced homogeneous

3-D reservoir model, with the impact of four different reservoir parameters, viscosity,

permeability, pay zone thickness and well pair spacing, for a total of five-year recovery

simulation. The SAGD to CSS process is also carried out as a contrast study with these four

reservoir parameters. Finally, a heterogeneous field heavy oil reservoir model from Liaohe

Oilfield is utilized to validate the conclusions acquired from the homogeneous model study. The

following conclusions is made from this thesis:

1. For the CSS to SAGD process, optimizing the 5-year recovery process within the scope of

the whole period, by implementing six different timing schemes, is able to give a better

solution of the switching time than carrying out the CSS process to its economic limit and

then switched to the SAGD recovery process, regarding the highest total NPV of the whole

process reached.

2. For the effect of permeability, viscosity, pay-zone thickness, and well pair spacing, each

exerts a certain effect on the total NPV and total oil recovery, and also the recovery

percentage of each thermal process is changed with different parameters of a reservoir

model taken into simulation.

3. For the SAGD to CSS process, the overall effect of the previous four reservoir parameters

gives a similar impact to the total NPV result. The total NPV value of SAGD to CSS is

higher than CSS to SAGD for most reservoir parameter scenarios.

4. The switch timing from CSS to SAGD is estimated to a higher extent by using the

83

polynomial trend line regression method. Also, the best CSS to SAGD switch time for other

reservoir properties (viscosity, permeability, pay-zone thickness, and well spacing) is

roughly estimated, which is also beneficial for forecasting the switching point for a variety

of different reservoir parameter values.

Overall, this optimization method is a novel way to optimize the recovery strategy of certain

heavy oil reservoirs.

6.2 Recommendations

In future, the following research work is recommended to improve the optimization strategy for

multiple thermal recovery processes:

1. Larger ranges of operating conditions should be considered, for example, a range of steam

temperatures for CSS and SAGD.

2. More thermal recovery processes, such as steamflooding, hot/cold water flooding, and in

situ combustion, is included in next step studies.

3. More sensitivity analysis should be conducted. For example, two oil viscosity profiles

properties are investigated, but in future more scenarios should be considered.

84

References

Edmunds, N.R., Kovalsky, J.A. Gittins, S.D., and Pennacchio, E.D., Review of the Phase A Steam Assisted Gravity Drainage to un Underground Test Facility; SPE 21529, presented at the SPE International Thermal Operation Symposium, Bakersfield, CA, February 7-8, 1991. Green D.W., Willhite G.P. Enhanced oil recovery, SPE textbook series, vol. 6, Henry L. Doherty Memorial Fund of AIME, Society of Petroleum Engineers, Richardson, Texas (1998) Butler, R.M. Thermal recovery of oil and bitumen. United States: N.P., 1991. Web. Edmunds, N., & Chhina, H. (2001, December 1). Economic Optimum Operating Pressure for SAGD Projects in Alberta. Petroleum Society of Canada. doi:10.2118/01-12-DAS Baker, R. O., Fong, C., Li, T., Bowes, C., & Toews, M. (2008, January 1). Practical Considerations of Reservoir Heterogeneities on SAGD Projects. Society of Petroleum Engineers. doi:10.2118/117525-MS Gates, I. D., Chakrabarty, N., Moore, R. G., Mehta, S. A., Zalewski, E., & Pereira, P. (2008, September 1). In Situ Upgrading of Llancanelo Heavy Oil Using In Situ Combustion and a Downhole Catalyst Bed. Petroleum Society of Canada. doi:10.2118/08-09-23 ITO, Y., SUZUKI, S. and YAMADA, H., Effect of Reservoir Parameters on Oil Rates and Steam Oil Ratios in SAGD Projects, presented at the 7th UNITAR International Conference on Heavy Crude and Tar Sands, Beijing, China, 28-31 October 1998 Joshi, S. D. (1991). “Thermal Oil Recovery With Horizontal Wells (includes associated papers 24403 and 24957).” Journal of Petroleum Technology 43(11): 1302‐1304. Nasr, T. N., Beaulieu, G., Golbeck, H., & Heck, G. (2003). Novel Expanding Solvent-SAGD Process" ES-SAGD". Journal of Canadian Petroleum Technology, 42(01). Ito, Y., & Suzuki, S. (1999). Numerical simulation of the SAGD process in the Hangingstone oil sands reservoir. Journal of Canadian Petroleum Technology, 38(09). Butler R.M., Mokrys I. J. (1989). "Solvent Analog Model of Steam-Assisted Gravity Drainage." AOSTRA Journal of Research, 5, 17-32. Das, S. K., & Butler, R. M. (1996). Diffusion coefficients of propane and butane in Peace River bitumen. The Canadian journal of chemical engineering, 74(6), 985-992. CMOST Manual, CMGL Company, 2016

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Appendix

1. Units used in Tables

CSS years

Timing Schemes

Inj Temp.

Max I. Timing

Max S. Timing

Max P. Timing NPV Inj


NPV

CSS years years

Inj Temp. Fahrenheit

Max I. Timing days

Max S. Timing days

Max P. Timing days

NPV Dollar ($)

Prod. Rate bbl/day

Total NPV Dollar ($)

2. Value of Relative Permeability Curves Value of the Basic Simulation Basic Model

Sw Krw Krow 0.45 0.0 0.4 0.47 0.000056 0.361 0.50 0.000552 0.30625 0.55 0.00312 0.225 0.60 0.00861 0.15625 0.65 0.01768 0.1 0.70 0.03088 0.05625 0.75 0.04871 0.025 0.77 0.05724 0.016 0.80 0.07162 0.00625 0.82 0.08229 0.00225 0.85 0.1 0.0

All the relative permeability data comes from the CMG Tutorial Files of version 2016

optimum switch timing for steam-assisted gravity drainage

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