enhancing hydrocarbon recovery and sensitivity studies in
TRANSCRIPT
University of Calgary
PRISM: University of Calgary's Digital Repository
Graduate Studies The Vault: Electronic Theses and Dissertations
2017
Enhancing Hydrocarbon Recovery and Sensitivity
Studies in Tight Liquid-Rich Gas Resources
Wang, Min
Wang, M. (2017). Enhancing Hydrocarbon Recovery and Sensitivity Studies in Tight Liquid-Rich
Gas Resources (Unpublished master's thesis). University of Calgary, Calgary, AB.
doi:10.11575/PRISM/25905
http://hdl.handle.net/11023/3850
master thesis
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UNIVERSITY OF CALGARY
Enhancing Hydrocarbon Recovery and Sensitivity Studies in Tight Liquid-Rich Gas Resources
by
Min Wang
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
MAY, 2017
© Min Wang 2017
ii
Abstract
Unconventional tight reservoirs refer to the formations with a permeability ranges from 0.001 to
0.1 millidarcy. Horizontal drilling coupled with multistage hydraulic fracturing is required in these
formations to achieve economic production rates. Recovery factor in tight gas formations is
typically less than 25% of the original gas in-place. Such low recovery is a strong motivation to
investigate the application of enhancing hydrocarbon recovery methods in these reservoirs.
In this study, enhanced hydrocarbon recovery methods are investigated for a Montney liquid rich
gas reservoir, located in the Western Canadian Sedimentary Basin. Firstly, a heterogeneous
reservoir model is built and history-matched based on the production data collected from the field.
Production performance of three EHR methods including cycling gas injection, CO2 flooding and
water injection are then compared and their economic feasibility are evaluated. Sensitivity analysis
of operational and geological factors including primary production duration, bottom hole pressures
(BHP) during primary production and EHR process, pressure-dependent matrix permeability, non-
Darcy effects and hydraulic fracture conductivity is conducted and their effects on the well
production performance are studied. Experimental design is adopted to further study the
mechanism and optimize the enhancing recovery process by cyclic gas injection and CO2 injection.
Results show that both cumulative oil and gas production are increased with fluid injection
compared to primary depletion methods. In addition, cyclic gas and CO2 flooding is more feasible
for the ultra-low unconventional tight gas reservoir than water flooding due to the water injection
difficulty and low sweep efficiency in the reservoir. Cycling gas injection leads to both a higher
gas and oil recovery and lower injection cost due to the on-site available gas source and minimal
transport/purchase costs, gaining more economic benefits than that of CO2 flooding. Thus, it can
iii
be concluded that cyclic gas flooding in tight liquid rich gas reservoirs with hydraulically
stimulated fractures could be a good way to enhance oil and gas production. Optimization study
results indicate that two injection wells, short primary production time, high primary BHP and
injection BHP, short injection time and low later period BHP lead to an optimal scheme of cyclic
gas flooding and CO2 flooding methods.
iv
Acknowledgements
I would like to thank my nice supervisor Dr. Shengnan (Nancy) Chen, who keeps providing
guidance, support and encouragement during my master study at the University of Calgary.
I would also like to thank my respectable examination members: Dr. Zhangxing Chen and Dr. Brij
Maini for their encouragement, valuable suggestions and insightful comments.
I would like to deliver the gratitude to my colleagues and friends for their help during my master
study. I also appreciate the help from Reservoir Simulation Group and the support from the Seven
Generations Energy Ltd.
Last but not the least, I would like to express my appreciation to my family for their love, support
and encouragement.
ii
Table of Contents
Abstract ................................................................................................................................2 Acknowledgements ..............................................................................................................4
Table of Contents ................................................................................................................ ii List of Tables ..................................................................................................................... iv List of Figures and Illustrations ...........................................................................................v List of Symbols, Abbreviations and Nomenclature .......................................................... vii
CHAPTER ONE: INTRODUCTION ..................................................................................1
1.1 Overview ....................................................................................................................1 1.2 Problem Statement .....................................................................................................2 1.3 Objectives ..................................................................................................................4
1.4 Outline .......................................................................................................................5
CHAPTER TWO: LITERATURE REVIEW ......................................................................7 2.1 Unconventional Tight Reservoir ................................................................................7
2.2 Tight Oil .....................................................................................................................8 2.3 Tight Gas ....................................................................................................................9
2.4 Hydraulic Fracturing in Tight Reservoirs ................................................................16 2.5 Enhanced Recovery Method in Tight Reservoir ......................................................19 2.6 Gas Injection Method ...............................................................................................21
2.6.1 Lean Gas Injection Method .............................................................................22 2.6.2 Nitrogen Injection Method ..............................................................................24
2.6.3 CO2 Injection Method ......................................................................................26 2.6.4 Huff-n-puff Method .........................................................................................27
2.7 Water Injection Method ...........................................................................................29
CHAPTER THREE: ENHANCING HYDROCARBON RECOVERY IN TIGHT LIQUID-
RICH GAS RESOURCES ........................................................................................31 3.1 Geologic Model .......................................................................................................32 3.2 Reservoir Simulation Model ....................................................................................37
3.2.1 Model Description ...........................................................................................37 3.2.2 Hydraulic Fracture – Local Grid Refinement ..................................................41 3.2.3 PVT Model ......................................................................................................42 3.2.4 History Match ..................................................................................................44
3.3 Enhanced Hydrocarbon Recovery methods .............................................................45 3.3.1 Reservoir Performance ....................................................................................45 3.3.2 Phase Envelop Change ....................................................................................51
3.3.3 NPV Calculation ..............................................................................................53 3.4 Conclusions ..............................................................................................................54
CHAPTER FOUR: SENSITIVITY STUDIES ON CYCLIC GAS FLOODING
PERFORMANCE .....................................................................................................56
4.1 Effect of BHP ...........................................................................................................56 4.2 Effect of Different Primary Production Time ..........................................................59 4.3 Pressure-dependent Permeability .............................................................................63
iii
4.4 The Effect of Non-Darcy Flow in Hydraulic Fractures ...........................................66
4.5 Hydraulic Fracture Height .......................................................................................67 4.6 Hydraulic Fracture Conductivity .............................................................................69 4.7 Conclusion ...............................................................................................................72
CHAPTER FIVE: OPTIMIZATION OF GAS INJECTION IN TIGHT LIQUID RICH GAS
RESERVOIR ............................................................................................................74 5.1 Parameters Considered in the Simulation Model ....................................................74
5.1.1 Number of Injection Wells ..............................................................................76 5.1.2 Parameters of Primary Production ...................................................................77
5.1.3 Parameters of Injection ....................................................................................78 5.2 Experimental Design ................................................................................................78 5.3 Results and Discussion ............................................................................................87
5.4 Conclusion ...............................................................................................................94
CHAPTER SIX: CONCLUSIONS AND FUTURE WORK ............................................96 6.1 Conclusions ..............................................................................................................96
6.2 Future work ..............................................................................................................98
REFERENCES ..................................................................................................................99
iv
List of Tables
Table 2-1 Marketable natural gas production in Canada (NEB, 2014) ........................................ 10
Table 2-2 Ultimate potential for Montney unconventional petroleum in British Columbia and
Alberta ................................................................................................................................... 14
Table 3-1 Reservoir model properties........................................................................................... 39
Table 3-2 Gas and liquid components table .................................................................................. 43
Table 3-3 Cumulative production for different enhanced hydrocarbon methods ......................... 51
Table 3-4 NPV for different enhanced hydrocarbon methods ...................................................... 54
Table 4-1 Data of the Cumulative production under different well BHPs ................................... 59
Table 4-2 Production data of different primary production time .................................................. 63
Table 4-3 Pressure-dependent permeability table (Cho, 2013) .................................................... 65
Table 5-1 Simulation parameters combinations of cyclic gas flooding ........................................ 82
Table 5-2 Simulation parameters combinations of CO2 flooding ................................................. 85
Table 5-3 Calculated Revenue of cyclic gas flooding .................................................................. 91
Table 5-4 Calculated Revenue of CO2 flooding ........................................................................... 93
v
List of Figures and Illustrations
Figure 2-1 Geological view of the WCSB (Canadian Society of Western Exploration
Geophysicists) ......................................................................................................................... 8
Figure 2-2 Canadian tight oil production (NEB, 2015) .................................................................. 9
Figure 2-3 Tight and shale gas production from 2000 to 2013 (NEB, 2015) ............................... 11
Figure 2-4 Natural gas processing plant ....................................................................................... 12
Figure 2-5 Location of the Montney Formation in the subsurface of Alberta and British
Columbia. (Modified from the Geological Atlas of the Western Canada Sedimentary
Basin.) ................................................................................................................................... 13
Figure 2-6 Mixed hydrocarbon distribution (Momentum Oil & Gas LLC, 2011) ....................... 15
Figure 2-7 Schematic of hydraulic fractured wells (NEB, 2015) ................................................. 17
Figure 2-8 Two dimensional models (Gidley et al. 1989) ............................................................ 18
Figure 2-9 P-T diagram of a retrograde condensate (Larry, 2007) ............................................... 19
Figure 2-10 Huff-n-puff schematic (NETL) ................................................................................. 29
Figure 3-1 Kakwa area type log (Kuppe et al. 2012) .................................................................... 33
Figure 3-2 Four horizons and wells location ................................................................................ 34
Figure 3-3 Mixed hydrocarbon system (Kuppe et al., 2012 ) ....................................................... 34
Figure 3-4 3D View of geologic model ........................................................................................ 36
Figure 3-5 Properties of the geological model .............................................................................. 36
Figure 3-6 Accumap view of well pads ........................................................................................ 38
Figure 3-7 3D view of simulation model containing target wells ................................................ 39
Figure 3-8 Permeability and porosity variation of the simulation model ..................................... 40
Figure 3-9 Relative permeability curves for Montney formation ................................................. 41
Figure 3-10 Local refined grids near the hydraulic fracture ......................................................... 42
Figure 3-11 P-T diagram ............................................................................................................... 44
Figure 3-12 History matching result for well-3 ............................................................................ 45
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Figure 3-13 Cumulative oil and gas production of various injection fluids ................................. 48
Figure 3-14 The Impact of injection fluids on reservoir pressure during production time........... 50
Figure 3-15 P-T diagram of different gas oil ratios during cyclic gas injection ........................... 52
Figure 3-16 P-T diagram of different gas oil ratios during CO2 injection .................................... 52
Figure 4-1 Cumulative production under different well BHPs ..................................................... 58
Figure 4-2 Comparison of different primary production time ...................................................... 62
Figure 4-3 Average field pressure ................................................................................................. 62
Figure 4-4 Comparison of two cases with and without pressure compactions ............................. 65
Figure 4-5 Comparison of Darcy and non-Darcy flow ................................................................. 67
Figure 4-6 Cumulative oil production under two fracture heights ............................................... 69
Figure 4-7 Cumulative production of the two cases ..................................................................... 71
Figure 5-1 2D View of the Simulation Model .............................................................................. 75
Figure 5-2 3D View of simulation models ................................................................................... 77
Figure 5-3 Graphical example of Lk full factorial experimental designs ...................................... 80
Figure 5-4 CO2 fraction in the late injection period ..................................................................... 84
Figure 5-5 Gas saturation in the 2D simulation model of cyclic gas flooding ............................. 89
Figure 5-6 Pressure distribution in the 2D simulation model of cyclic gas flooding ................... 90
Figure 5-7 Revenue value distribution of the 32 tests of cyclic gas flooding ............................... 91
Figure 5-8 Revenue value distribution of the 32 tests of CO2 flooding ........................................ 93
vii
List of Symbols, Abbreviations and Nomenclature
Symbol Definition
𝐶𝑤𝑒𝑙𝑙 Cost of horizontal well
𝐶𝑓𝑟𝑎𝑐𝑡𝑢𝑟𝑒 Cost of hydraulic fracture
𝐶 Total cost
i Interest rate
n Number of periods
𝐹𝐶 Total fixed cost
N Number of horizontal wells
𝑉𝑔𝑎𝑠 Value of gas revenue
𝑉𝑜𝑖𝑙 Value of oil revenue
𝑉𝐹 Future value of gas and condensation liquid revenue
μ Viscosity
v Velocity
k Hydraulic fracture permeability
β Non-Darcy Beta factor
ρ Density of certain phase
𝐶𝑓𝑑 Dimensionless hydraulic fracture conductivity
𝑘𝑓 Fracture permeability
𝑤𝑓 Fracture width
𝑘𝑚 Matrix permeability
𝐿𝑓 Hydraulic feature half-length
𝑘𝑒𝑓𝑓 Effective permeability
𝑤𝑔𝑟𝑖𝑑 Grid width
1
Chapter One: Introduction
1.1 Overview
Canada, the fifth largest natural gas producer of the world, occupies 5% of the gross global gas
production. The country’s natural gas production is mainly supplied by the Western Canadian
Sedimentary Basin (WCSB), which contains substantial natural gas and oil reserves, such as oil
sands, heavy oils, conventional resources, and unconventional tight/shale resources. The
productivity of unconventional gas formations has grown rapidly due to further exploration and
development, while the production of conventional natural gas has decreased.
Except for small numbers of dry gas producers, heavy hydrocarbon components (e.g., ethane,
propane, butanes and pentanes plus) will separate from the gas state in the form of liquids when
raw natural gas comes from the wellhead. This wet gas, liquid rich gas or natural gas liquid (NGL),
composes an important part of Canada’s energy mix.
The deep part of the Western Canada Sedimentary Basin indicates significant potential for
unconventional gas resources. In this basin, the Montney Formation is considered one of Canada’s
most potential economic gas plays (NEB, 2010). The formation covers approximately 130,000
square kilometres and spans 700 kilometres north to south, traversing the provincial boundary
between northwest Alberta and northeast British Columbia (Seven Generation, 2017).
2
The average daily production in the Montney formation is around 3.5 billion cubic feet of natural
gas per day (Bcf/d), accounting for 25% of natural gas production in the WCSB. Even though the
area’s development is still in the preliminary stages, its estimated potential is noteworthy. The
formation contains 449 trillion cubic feet (tcf) of marketable gas, 14,521 million barrels of
marketable natural gas and 1,125 million barrels of marketable oil.
Hydraulic fracturing in horizontal wells is the main method for extracting products from liquid
rich tight reservoirs. The process is established and commercially successful. During hydraulic
fracturing, tons of fracturing fluid and proppants are pumped into the reservoir matrix to create
hydraulic fractures, significantly improving gas recovery.
1.2 Problem Statement
Pressure depletion is the main recovery method used for the primary production period of tight
liquid rich gas reservoirs. Liquid will drop out when the reservoir pressure decreases below the
dew point, resulting in condensate liquid accumulating in the formation and around the wellbore.
The accumulation blocks the gas flow path, decreasing the gas condensate production significantly
(Moses and Donohoe, 1965; Hichman and Barree, 1985; Vo et al. 1989; Pope et al., 2000; Li and
Abbas, 2000).
Low permeability and low porosity are characteristics of tight and shale reservoirs. The condensate
liquid blocking problem is exacerbated significantly by the ultra-low reservoir permeability and
3
gas production rate could be reduced by 50%-80% in a gas condensate sandstone reservoir within
the first two years (Ayyalasomayajula et al., 2005).
To solve this problem, lean gas injection (Smith and Yarborough, 1968; Abel et al., 1970; Sigmond
and Cameron, 1977; Abasov et al., 2000), CO2 injection (Chaback and Williams, 1994; Goricnik
et al., 1995) and N2 injection (Aziz, 1982) were investigated by several researchers. Their studies,
however, focused on the conventional reservoirs only.
The pressure depletion method by horizontal wells with multistage hydraulic fractures is the
current application for exploring gas condensate in tight reservoirs formations. IOR or EOR
methods have not been largely applied in shale and tight gas condensate reservoirs. Yu et al. (2014)
employed a numerical simulation method to study the efficiency of CO2 injection to enhance gas
recovery in the shale reservoir, considering the adsorption of CO2 in the shale with a high total
organic content. A sensitivity analysis of the CO2 injection lead to the optimal assessment of the
best scenario through the experimental design method. Sheng (2015) constructed a simulation
model of a gas condensate tight reservoir to study the efficiency of enhancing gas and oil recovery
by gas injection, CO2 injection and water flooding. The results indicate that the huff-n-puff gas
injection is a more practical and effective method to enhance gas and oil recovery than CO2 and
water injection. The study, however, used a simplified simulation model containing a single
fracture instead of a multistage fractured horizontal well. More literatures can be found in the
literature review chapter.
4
1.3 Objectives
This study focuses on enhancing hydrocarbon recovery by gas injection in the tight liquid rich gas
condensate reservoir, conducting a sensitivity study of the key parameters and optimizing a gas
injection scheme and controlling crucial factors. A geological model which contains 27 horizontal
wells are built through Petrel and three wells are cut out to build a simulation model, each well
containing about 30 stages of hydraulic fractures, in a tight liquid rich gas reservoir. The interactive
contact of nearby wells and pressure distribution/interaction are considered. The aim is to develop
a simulation study to enhance liquid rich gas and oil recovery at the late stage of the pressure
depletion process in a tight condensate reservoir and to determine a best scenario to maximize gas
and oil recovery.
The detailed objectives are:
(1) To build a comprehensive reservoir model based on field data collected from public domain
and validate such model by the production data.
(2) To investigate the performances of three scenarios of enhanced hydrocarbon recovery methods,
including cycling gas injection, CO2 injection and water injection and compare their economic
feasibility for the target reservoir.
5
(3) To conduct a sensitivity study on the key parameters, including fracture conductivity, stress
compaction, non-Darcy effect, primary production time and production BHP to investigate their
effects on the enhancing hydrocarbon process in the target tight gas reservoir.
(4) To perform an experimental design (DOE) to create a series of reservoir simulations combined
with variable parameters to maximize the NPV from the target reservoir.
1.4 Outline
A summary of the content of Chapters Two to Six follows:
(1) Chapter Two delivers a detailed literature review related to the topic of this thesis, including a
detailed forecast of unconventional tight reservoirs, hydraulic fractures and the EOR or IOR
methods of gas injection, CO2 injection and water injection.
(2) Chapter Three focuses on the construction of the heterogeneous simulation model and the use
of three EHR methods after primary production period to prevent reservoir pressure decline,
complement formation energy and enhance gas and oil recovery.
(3) Chapter Four investigates the sensitivity study of the operational and geological factors,
including primary production duration, bottom hole pressures (BHP) during primary production
and EHR process, matrix permeability and non-Darcy effects.
6
(4) Chapter Five employs an experimental design to calculate a series of combinations of
simulations to that optimize the gas injection method in tight liquid rich gas reservoir. This work
overrides the time-consuming shortcomings of the traditional “vary one parameter at a time”
strategy, significantly saving time and energy.
(5) Chapter Six lists the conclusions and future recommendations resulting from this study.
7
Chapter Two: Literature Review
2.1 Unconventional Tight Reservoir
The Western Canadian Sedimentary Basin (WCSB), situated in Western Canadian, spans the
southwest corner of the Northwest Territories, the northeast of British Columbia and Alberta
southern Saskatchewan and southwestern Manitoba, as shown in Figure 2-1. The basin contains
substantial natural gas and oil reserves, such as oil sands, conventional resources, and
unconventional resources. Different from conventional resources, unconventional resources,
including coalbed methane, tight gas, tight oil and shale gas, are stored in formation with low
porosity and permeability, leading to low recovery efficiency without special stimulation
treatments (e.g., horizontal drilling technique and hydraulic fracturing).
This thesis focuses on the study of tight reservoir, featured with low porosity and permeability,
small drainage radius and low productivity, which is composed with sandstone, siltstone, limestone
and carbonates. The development of tight reservoir requires significant well stimulation mainly
including hydraulic fracturing technique, horizontal wells treatment and multi-lateral wells to
improve the recovery to meet the economic value.
8
Figure 2-1 Geological view of the WCSB (Canadian Society of Western Exploration
Geophysicists)
2.2 Tight Oil
Tight oil is a kind of light crude oil contained in low permeability reservoirs which needing
horizontal drilling and multi-stage hydraulic fracturing technique. Tight oil in the WCSB started
to be developed in the Bakken Formation of southeast Saskatchewan and southwest Manitoba in
2005 and latterly had spread extensively to Alberta with the main formations like Cardium. In
2014, the production of tight oil accounted for over 10 percent of total Canadian crude oil
production. Figure 2-2 shows the growth trend of tight oil production in the past several years. The
production grew from near zero in 2005 to 350,000 barrels per day in 2013.
9
Figure 2-2 Canadian tight oil production (NEB, 2015)
2.3 Tight Gas
Natural gas production in Canada is mainly supplied by the WCSB in British Columbia, Alberta,
and Saskatchewan, and other smaller regions in offshore Nova Scotia, Ontario, New Brunswick,
and Nunavut. Table 2-1 shows the constituent parts of Canada’s total gas production in 2014.
Canada is the fifth largest natural gas producer of the world, occupying 5% of the gross global gas
production. With the further exploration and development of unconventional resources, the
productivity of unconventional natural gas has grown rapidly while the production of conventional
natural gas has decreased.
10
Table 2-1 Marketable natural gas production in Canada (NEB, 2014)
In 2014, tight and shale gas accounted for about 51 percent of total Canadian natural gas
production. Figure 2-3 shows Canadian shale and tight gas production from 2000 to 2013. Gas
production grew from three billion cubic feet per day in 2000 to seven billion cubic feet per day
by 2013. By 2035, tight and shale gas production together is expected to occupy 80 percent of
Canada’s natural gas production (NEB, 2015).
Marketable Production (MMcf/d)
Province NS NB ON SK AB BC YT Canada
Total
Mar. 354 10 7 427 9,781 3,897 13 14,488
Apr. 364 10 7 446 10,017 4,014 11 14,869
May 346 9 11 446 9,732 3,952 12 14,506
Jun. 436 10 11 423 9,469 3,689 11 14,049
Jul. 390 8 10 441 9,899 3,846 11 14,606
Aug. 281 9 12 436 9,994 4,022 11 14,765
Sep. 174 9 12 443 9,630 3,946 10 14,224
Oct. 161 9 12 443 10,249 4,163 9 15,046
Nov. 224 8 12 433 10,183 4,201 10 15,070
Dec. 301 9 12 432 10,423 4,320 12 15,509
11
Figure 2-3 Tight and shale gas production from 2000 to 2013 (NEB, 2015)
Dry gas is mostly composed of methane. According to the U.S. Energy Information Administration
(EIA), dry gas is defined as what remained after all the heavier hydrocarbons (hexane, octane, etc.)
and non-hydrocarbons (helium, nitrogen, etc.) are removed from the natural stream. Wet gas
contains heavier hydrocarbons such as ethane and butane and less than 85% methane. During the
production process, heavy hydrocarbon components (e.g., ethane, propane, butanes and pentanes
plus) will separate from the gas state in the form of liquids when raw natural gas comes from the
wellhead. If the liquid yield greater than 10 bbls from every MMcf sales gas when flowing through
a gas processing plant, the gas is considered “liquid-rich”.
12
This wet gas is called liquid rich gas or natural gas liquids (NGL), composing an important part of
Canada’s energy mix. Most NGLs are produced at the natural gas processing plants (Figure 2-4),
located primarily in the gas- producing areas of Alberta and several plants in British Columbia.
The Deep Basin part of the WCSB indicates that natural gas accounts for significant resource
potential in Canada’s energy mix.
Figure 2-4 Natural gas processing plant
This thesis focuses on producing low-cost, liquids-rich natural gas from the Montney geological
formation, an elongated oval-shaped, lower-Triassic sedimentary basin composed of sandstones,
siltstones and carbonates, which covers approximately 130,000 square kilometres and spans 700
kilometres north to south, traversing the provincial boundary between northwest Alberta and
northeast British Columbia (Seven Generation, 2017). The depth of the formation is very thin on
its eastern and northeastern sides, while very thick, usually ranging from 100 m to 300 m at its
13
western edge. Due to the increase of depth causing increasing pressure and decreasing natural gas
liquids (NGL) and oil content, the reservoir characteristics vary extensively over the formation.
Figure 2-5 Location of the Montney Formation in the subsurface of Alberta and British
Columbia. (NEB, 2013)
The Montney, containing one of the biggest marketable unconventional gas resources, is
considered one of Canada’s most potential economic gas plays. In 2012, its average daily
production rose to an average of 48.6 million m3/d (1.7 Bcf/d), while the total Canadian marketable
gas production was about 392.7 million m3/d (13.9 Bcf/d) (NEB, 2013). Even though Montney
14
development is still in the early stages, its forecast for increased gas production places it in a key
role in Canada’s overall production.
The ultimate potential for unconventional petroleum in the Montney total production is composed
of both the British Columbia and Alberta portions. As shown in Table 2-2 the ultimate expected
marketable volume of natural gas is 12,719 billion m³, while marketable NGLs is 2,308 million
m³ and marketable oil is 179 million m³ (1,125 million barrels).
Table 2-2 Ultimate potential for Montney unconventional petroleum in British Columbia
and Alberta (NEB, 2013)
Hydrocarbon
Type
In-Place
Low
In-Place
Expected
In-Place
High
Marketable
Low
Marketable
Expected
Marketable
High
Natural Gas
(billion m³)
90,559 121,080 153,103 8,952 12,719 18,257
NGLs
(million m³)
13,884 20,173 28,096 1,540 2,308 3,344
Oil
(million m³)
12,865 22,484 36,113 72 179 386
The content of NGLs out of natural gas varies widely from a liquid rich gas (50 bbl/MMcf
condensate) to a light crude system (3,350 scf/bbl), from west to east, with a coinciding rise of
every vertical depth of 100 m.
15
The unconventional Montney reservoir is characteristic of overpressure with a gradient range from
10.5 kPa/m to 13.5 kPa/m; the gradient difference exceeds 3 kPa/m, stretching over 20 kilometers.
The dynamic behind the large pressure difference is stems from the slow migration of gas, over
millions of years, from the original hydrocarbon generation, pushing oil to the upper structure with
lower pressure and accumulating into the upper trapped reservoirs. The hydrocarbon composition
of the Montney area is quite variable even within small areas, as discerned by numerous analyses
of gas/liquid ratios and liquid yields. The liquid and gas failed to be re-dispersed more uniformly
due to the low and less diverse combined matrix and natural fracture permeability. Thus, a mixed
hydrocarbon schematic forms (Frank el at., 2012). The transition of dry gas to oil is rough and
uneven; the wet gas areas in the transition region vary largely (Figure 2-6).
Figure 2-6 Mixed hydrocarbon distribution (Momentum Oil & Gas LLC, 2011)
16
2.4 Hydraulic Fracturing in Tight Reservoirs
Low reservoir permeability and porosity in tight formations impede the flow of oil and gas into
the wellbore without the application of stimulation methods. Hydraulic fracturing is the process of
pumping fluid into the wellbore at an injection rate which is high enough to force the formation to
crack. During the process of fluid injection, the resistance towards the flow increases
accumulatively, leading to the increase of pressure to reach an ultimate value called break-down
pressure, composed of the in-situ compressive stress and the strength of the formation. A hydraulic
fracture is created when fracturing liquid is pumped into the pay zone at a high enough rate to
reach the break-down pressure.
At the beginning, a neat fluid, called a ‘pad’, is pumped to initiate the fracture and to establish
propagation. Fluid, mixed with a propping agent (proppant), is injected. This ensures that, in the
event of the pumping operation ceasing, the fractures are kept separated; the pressure in the fracture
decreases below the compressive in-situ stress trying to close the fracture. The fracture is extended
continuously and then the proppant is carried by the slurry into the deeper part of the fracture. At
the late stage, when the injected fluid begins to flow back with a lower viscosity to the wellbore,
a propped fracture with much higher conductivity is created, allowing oil and gas to flow,
unimpeded, from the tight formation into the wellbore.
Hydraulic fracture propagation is influenced significantly by a series of factors, such as the
variation of in-situ rock stresses, variations of pore pressure, bonding of formations, relative bed
thickness of formations near the fractures, mechanical rock properties, and fluid pressure gradients.
17
Typically, horizontal fractures are easily generated at shallow depths while vertical fractures tend
to be created in deeper areas. The higher lateral stress above and below the target formation
constrains the growth of vertical fractures. Fracture height influences the halt length and fracture
configuration significantly. Figure 2-7 shows two forms of hydraulic fractures along horizontal
and vertical wells. With successful applications of multi-stage hydraulic fracturing treatments in
horizontal wells in tight formations, production has increased significantly in recent years.
Figure 2-7 Schematic of hydraulic fractured wells (NEB, 2015)
The hydraulic fracture properties, such as length, width and height, cannot be measured during the
field treatment. The only measurable parameters are the volume of the injected fracturing fluid and
the time to complete the process. Various models are created to predict fracture properties,
including two dimensional models, pseudo three dimensional models, and fully three dimensional
18
models. The most common two dimensional models are the Perkins-Kern-Nordgren (PKN) and
Kristonovich-Geertsma-de Klerk (KGD). The PKN model is used when the fracture length is much
greater than the fracture length. The KGD model is applied when the fracture height is more than
the fracture length, as shown in Figure 2-8.
(a) PKN geometry for a 2D fracture (b) KGD geometry for a 2D fracture
Figure 2-8 Two dimensional models (Gidley et al. 1989)
Tight reservoirs, however, are more complex. Horizontal wells are applied in tight reservoirs due
to their low permeability and porosity. Multiple staged hydraulic fractures are closely spaced along
the horizontal wellbores and the hydraulic fracture of the adjacent wells also tends to transmit
communication pressure. Consequently, in tight reservoirs, the hydraulic fractures are influenced
by many other stress changes from nearby fractures and the adjacent wells. The oversimplified
fracture model fails to describe the hydraulic fractures in tight reservoirs (Olson et at., 2012). In
Olson’s study, a non-planar fracture model simulates complex hydraulic fracture propagation.
19
2.5 Enhanced Recovery Method in Tight Reservoir
Under some special reservoir condition, gas will condensate as liquid when the reservoir pressure
drops below the dew point pressure, as shown in Figure 2-9. The reservoir pressure is point A, at
the initial gas state. When the pressure drops from A to B, liquid appears in the gas phase, opposite
to the regular discipline that the liquid phase will be vaporized as a gas phase when pressure
decreases. The phenomenon is known as retrograde condensate; reservoirs displaying this
condition are considered as retrograde condensate reservoirs.
Figure 2-9 P-T diagram of a retrograde condensate (Larry, 2007)
The development and operation of gas condensate reservoirs differ greatly from crude-oil and dry-
gas reservoirs. A wholly vapor phase always exists at the time of exploration with an initial
pressure above the dew point pressure and a temperature above the critical temperature. Pressure
depletion is the main recovery method during the previous production period. Liquid will drop out
20
when the reservoir pressure decreases below the dew point, resulting in condensate liquid
accumulation around the wellbore. The condensate liquid collects near the wellbore, largely
blocking the gas flow rate and decreasing the gas condensate well production significantly (Moses
P L and Donohoe, 1965; Hichman and Barree, 1985; Vo et al. (1989); Pope et al., 2000; Kewen
Li, and Abbas, 2000).
Tight and shale reservoirs are characteristic of low permeability and low porosity. The pressure
gradient is generally large during the pressure depletion process, which means the rate of growth
and expansion of the condensate bank around the wellbore will be relatively high. Consequently,
the condensate liquid blocking problem is exacerbated significantly by low reservoir permeability
and high production rate (Wheaton and Zhang, 2000). The condensate liquid blocking could reduce
the well recovery by 50%-80% in a gas condensate sandstone reservoir (Ayyalasomayajula et al.,
2005). The productivity factor could be reduced by a factor of 10 in the low permeability reservoir
with 0.15 md (Lin and Finley, 1985). As a result, many studies have been conducted to deal with
the problem of low recovery in gas condensate reservoirs, especially in low permeability reservoirs
(e.g., tight reservoirs and shale reservoirs). The main enhanced condensate recovery methods
explored include natural gas injection, CO2 injection, nitrogen injection and water injection.
As compared with conventional reservoirs, gas injection in tight and shale liquid rich reservoirs
has recently attracted attention. Gas and water injection are seen as the main stimulation methods.
Gas injection includes gas flooding and huff-n-puff modes. In tight and shale reservoirs,
permeability and porosity are extremely low and the pressure gradient is larger during the depletion
process. The condensate blocking problem, therefore, becomes more prominent. The current
technique to produce oil and gas in tight reservoirs is through multiple transverse fractured
21
horizontal wells relying on primary pressure depletion. The study of unconventional plays shows
that, although the reservoir characteristics vary greatly, in the primary production period,
production declines rapidly, leading to a low recovery factor, ranging from 3% to 5% of the total
original oil in place (Liu et al. 2014). The oil recovery factor in oil-saturated shale reservoirs is
very low; for instance, in the Bakken formation, the recovery is approximately 7% (Clark et al.,
2009). At the late production period, massive shale oil remains unproduced unless stimulated
methods are employed. In Lake’s study (Lake et al., 2014), enhanced oil recovery processes are
classified into the following methods: solvent, polymer, surfactant, foam-enhanced oil recovery
and thermal. Research has been conducted to explore ways to address gas condensate issues during
depletion production.
2.6 Gas Injection Method
The gas condensate reservoir is initially saturated with natural gas, with an initial pressure above
the dew point pressure. Once the reservoir pressure drops below the dew point pressure, liquids
will come out from the gas state. Compared with gas, oil is more difficult to flow to the surface.
Condensate oil collecting around the wellbore, blocking the gas flow significantly, adds to the
challenge (Hernandez et al., 1999; Thomas et al., 1995).
Juell and Whitson (Juell et al., 2013) found an optimal production strategy. In the initial stage, the
bottom hole pressure is equal to the saturation pressure, and eventually decreases. In the long term,
however, when the pressure drops below the dew point pressure, the liquid oil will condensate
during the gas phase and accumulate at the wellbore, blocking the gas flowing rate. Thus,
22
maintaining pressure higher than the dew point pressure is essential to prevent liquid condensate
from forming in the later period. The most widely used pressure maintenance method is
revaporization by lean gas flooding (Standing et al., 1948; Weinaug and Cordell, 1949; Smith and
Yarborough, 1968; Abel et al., 1970; Abasov et al., 2000). Nitrogen and CO2 flooding are also
used effectively.
2.6.1 Lean Gas Injection Method
Early in 1948, researchers began to investigate revaporization of liquid condensate. Standing et al.
(1948) performed laboratory tests of the revaporization of liquid condensate using the gas cap in
variable permeability systems and computed the butanes and heavier fraction condensate after
pressure decline. The results revealed that if the reservoir pressure drops down to the upper dew
point pressure followed by lean gas cycling, a lower cycling pressure contributes better to the
butanes’ recovery. Since then, further research has focused on the factors affecting the optimum
methods for exploring a gas condensate reservoir.
Weinaug and Cordell (1949) investigated the influence of revaporization through the use of two
systems of methane-n-butane and methane-n-pentane and one type of sand pack. Their results
indicated that with the presence of sand, the condensate liquids can be revaporized by a sufficient
injection gas.
Oxford & Huntington (1952) studied the influence of various factors including, the rate of gas
flow, original liquid saturation reservoir temperature. They also explored how desorption of
23
hydrocarbons from unconsolidated sand was affected by the presence of water and brine in both
pressure depletion and constant pressure flow methods.
Smith and Yarborough (1968) investigated revaporization in the retrograde condensate recovery
through dry gas injection into a long sand pack. Three rounds of methane revaporization from an
n-pentane-methane mixture with the presence of immobile water were performed in their two
water-wet experiments and one oil-wet test. The fourth-round experiment was conducted by a
methane-hydrogen sulfide mixture revaporized without the presence of water saturation. The
results show that all the heavier components could be recovered by sufficient dry gas injection.
Abel et al. (1970) investigated a two-dimensional, three-phase compositional model to analyze the
effect of revaporization of liquids in a retrograde condensate reservoir in the Carson Creek field,
cycled below the dew point pressure. Three schemes of gas injection included: normal cycling
with low rate gas sales, partial cycling with normal rate gas sales, and reservoir depletion without
gas injection. The results indicate that partial cycling scheme is optimal, resulting in higher
recovery of liquids with better economical assessment in the long run.
Sigmond and Cameron (1977) conducted experiments to investigate the influence of particle size,
initial liquid saturation, dry gas injection rate and immobile water saturation on the revaporization
process in gas condensate reservoirs. The reinjection of cyclic gas for the purpose of improving
formation pressure made it generally uneconomic.
24
More recently, Abasov et al. (2000) detailed the compositional behavior of a lean gas condensate
when depleted in a PVT cell at 1000 C (data for different temperatures are not given). The physical
properties of condensates were collected in the condenser at different pressure intervals during the
four isothermal depletion processes. Special attention was paid to the evaporation of the remaining
liquid condensate after depletion upon contact by lean natural gas. They concluded that more
elevated temperatures result in higher evaporation effectiveness, or recovery, of condensate by
lean gas.
2.6.2 Nitrogen Injection Method
The increasing value of sales gas reduces the commercial assessment to divert the gas from the
sale line (Aziz et al., 1982, Buchanan et al., 1981). Thus, researchers focused on nitrogen, with its
advantages of low price and stable properties, as a substitute for natural gas to maintain pressure
during the cycling operation.
Wilson and Moses (1981) conducted experiments to evaluate the ability of maintaining reservoir
pressure and displacement efficiency of nitrogen in a retrograde gas-condensate reservoir. The
reservoir fluid was studied through static equilibrium tests in a windowed equilibrium cell. The
injected natural gas or nitrogen was mixed with reservoir fluid and the mixture improved the dew
point. The test indicates that retrograde liquid loss will happen in the displacing front in the mixing
region; nitrogen gas injection shows greater mixture effectivity. To further study the mixture
influence on the phase behavior during the reservoir displacement operation, a packed-column
displacement apparatus was built using lean gas and nitrogen, respectively, as displaced injection
25
gases. Both injection methods showed over 98% recovery of fluid and infinite gas/liquid ratio in
the sand tube. The significant liquid recovery indicates that little mixing occurs during the lean
gas/ gas and nitrogen/ gas displacement during the packed-column displacement experiments.
Although the static equilibrium tests and packed-column experiments demonstrated different
liquid loss, nitrogen gas proved similar effectiveness with natural gas in displacing the retrograde
condensate fluid. The liquid flowing in porous media is dominated by the streamline effect of
Darcy's law. The extent of mixing is affected by reservoir heterogeneity, mobility ratio, flow
pattern, molecular diffusion and dispersion under the actual reservoir conditions. Thus, mixing
will be reduced by controlling the above factors. Compared with lean gas, the mobility ratio of
nitrogen injection is more stable and more easily maintained. If the injection and production rates
are controlled, flow pattern changes could be minimized.
Buchanan et al. (1981) investigated the economic feasibility of using nitrogen as an alternative to
natural gas during the cycling operation. Three nitrogen injection scenarios were created. Factors,
such as gas prices, stock-tank liquid content, and the degree of reservoir heterogeneity, were
considered. The study indicated that a gas reservoir containing liquid richer than 100 bbl/MMcf
should be considered for potential nitrogen injection.
In a study of Eckles et al. (1981) in the Fordoche Field, USA, injected natural gas was shown to
be more readily miscible with displaced liquids in the hot and high-pressured sands, when the
initial bottom hole pressure was about 11,018 psig and the bottom hole temperature was 278°F.
As the cost of natural gas increases rapidly, a mixture of natural gas and nitrogen is considered as
a more economic substitute. The mixture of 30% nitrogen and 70% natural gas was injected as
26
make-up gas after a previous injection of natural gas. The nitrogen is blocked against the reservoir
oil and gas by the previous injected natural gas. The previous injected gas can also be displaced
and recovered by the nitrogen mixture. In rich retrograde condensate-gas reservoirs, one problem
with nitrogen injection is that mixing it with condensate liquid will lead to significant in-situ
condensate drop-out. The experiment indicated that liquid drop-out takes place in the system, in
both the methane and nitrogen injection front. The methane creates less liquid drop-out than does
the nitrogen and shows better PVT static behaviour under the condition of mixing with the
condensate liquids.
If the Peclet number, a ratio of convective mass transfer to dispersive mass transfer, is high,
however, the dispersion scale is insignificant, which will cause less negative influence on recovery.
If the Peclet number is low, the nitrogen injection causes lower oil recovery than does the methane
injection. If the Peclet number is high enough, the nitrogen injection recovery approaches that of
the natural gas injection (Sigmund and Cameron, 1977). Gas injection will inevitably raise the dew
point pressure, leading to an incomplete recovery of liquid. Thus, recovery is partially influenced
by the pressure/composition (p-x) behavior of the injection gas and condensate fluid.
2.6.3 CO2 Injection Method
Chaback and Williams (1994) investigated the p-x behavior of a rich gas condensate reservoir with
CO2 and N2-CO2 mixture injections under two reservoir temperatures (2150 F and 316°F) and
high pressure. The PVT test indicated that the CO2 injection is more efficient than the N2-CO2
mixture in revaporizing retrograde liquid.
27
Goricnik et al. (1995) conducted experiments to compare the effect of CO2 and natural gas using
pressure-composition and pressure-retrograde liquid dropout diagrams. The results demonstrated
that CO2 achieved more efficiency than natural gas in revaporizing retrograde liquid in the gas
condensate reservoir.
A sensitivity analysis in a dry gas reservoir in Barnett reservoir was conducted by Yu et al, (2014)
to study CO2 injection in improving recovery. The result indicated that CO2 injection is an effective
way to enhance gas recovery.
2.6.4 Huff-n-puff Method
The huff-n-puff (Figure 2-10) injection scheme entails injecting a well with a recovery
enhancement fluid and, after a soaking period, returning the well to production. Huff-n-puff can
include either gas or CO2. In a gas condensate reservoir, pressure depletion is the main recovery
method. To improve production, large pressure differences and an optimal flowing are needed. In
the depletion mode, optimal operation conditions exist for liquid rich gas tight reservoirs.
Gamadi et al. (2013) are the first to launch studies on the performance of huff-n-puff gas injection
in shale oil reservoirs. A shale core plug, saturated with oil, was placed inside a large container
saturated with gas. The space between the core plug and container was regarded as fractures.
Initially, the gas pressure increased more than did the oil in the core plug; the gas was pushed into
the core plug, which imitates the injection period. After a gas soaking period, the pressure on the
28
gas declined below the core pressure. The oil in the core plug was displaced, which represents the
puff period. The analysis of the effects of the soaking pressure and soaking time on oil recovery
showed that soaking pressure had a more significant effect on oil recovery than did soaking time.
The study indicated that maintaining pressure in shale and tight reservoirs is the leading
mechanism to enhance oil and gas production.
Wan et Al, (2013) simulated the huff-n-puff method through a black oil model in a shale oil
reservoir. Their result shows that cycle time is a significant factor in incremental oil recovery. The
optimal huff-n-puff scheme is to use a shorter injection time and longer production time.
After the earlier study on the huff-n-puff method in shale oil reservoirs (Wan et al., 2013; Gamadi
et al., 2013, 2014; Wan et al., 2014), a series of simulations were conducted to investigate it in in
a shale gas condensate reservoir (Sheng, 2014; Sheng, 2015; Meng and Sheng 2015). In a
simplified simulation model containing one well with two half-length fractures as injector and
producer, huff-n-puff shows greater advantage than gas flooding in many aspects, such as early
response to gas injection, high drawdown pressure, effective evaporation to decrease oil saturation
near the wellbore, and averting pressure transport due to low reservoir permeability. They
concluded that the huff-n-puff method has the capacity to improve oil and gas recovery more
effectively than natural gas flooding and pressure depletion.
29
Figure 2-10 Huff-n-puff schematic (NETL)
According to Yu et al, (2014), the CO2 huff-n-puff method did not show significant efficiency
because, during the puff phase, a large amount of injected CO2 flows back to the surface in advance
of the natural gas. The separation of mixed CO2 and natural gas also increase costs.
2.7 Water Injection Method
Water flooding is another technique used to boost gas condensate reservoirs’ recovery (Hernandez
et al., 1999). Hernandez’s study investigated continuous and simultaneous gas cycling with water
injection (CSGW) and continuous gas cycling with alternating water injection (CGAW). They
concluded that water is not only a good reservoir void space filler, but also increases the mobility
ratio, improves the sweep efficiency and enhances recovery significantly.
30
Mattews et al. (1988) conducted experimental and theoretical studies focused on the feasibility of
water injection in gas condensate reservoirs. They concluded that water flooding was advantageous
in improving oil and gas recovery as compared with original pressure depletion methods.
Cullick et al. (1993) investigated simulation work on the water-alternating-gas process (WAG), in
which water and gas are combined in water flooding. A compositional reservoir simulation model
was set up to study the influence of different parameters. The results show that the WAG method
is more effective in improving condensate reservoir production than is pure gas injection.
In this study, cyclic gas flooding, CO2 flooding and water flooding are investigated in a
heterogeneous simulation model in a tight liquid rich gas condensate reservoir. The efficiency of
the three methods to enhance hydrocarbon recovery are compared. The optimization study is also
conducted to maximize the tight reservoir recovery.
31
Chapter Three: Enhancing Hydrocarbon Recovery in Tight Liquid-Rich Gas Resources
The development of the hydraulic fracturing technique in horizontal wells to produce natural gas
from tight liquid rich gas reservoirs has increased over the past few years in North America and is
playing a crucial role in the world’s energy supply. When field pressure drops below the reservoir
dew point pressure, however, oil will be condensate out of the gas phase during the pressure
depletion process. The oil remains unproduced in the reservoir, bringing profound changes from
single phase to two-phase flow, which can reduce well productivity. Thus, pressure maintenance
is critical in maximizing gas and oil recovery in the Montney Formation.
In this study, a simulation model for a liquid rich gas reservoir in Montney formation is established
and history-matched to optimize well performance and pressure maintenance through cycling gas
flooding, CO2 flooding and water flooding methods. More specifically, a heterogeneous geological
model containing 27 parallel horizontal wells is created based on the geologic data collected from
the Montney formation, while a section with 3 horizontal wells is cut out for the numerical
simulations. A PVT model is constructed based on sampling and experimental data, then the model
is validated by history match. Daily well bottom-hole pressure and gas-oil production data are used
to estimate and adjust the model parameters. After the primary production, three scenarios of EHR
methods, including cyclic gas flooding, CO2 flooding and water flooding, are employed to
maintain and increase oil and gas production. The EHR efficiency and economic estimation are
compared and optimized. The influence of injected cyclic gas on the PVT model is also
investigated.
32
3.1 Geologic Model
The Montney formation is a foremost example of unconventional gas plays in the Western
Canadian Sedimentary Basin, covering an area of 130,000 square kilometers from northeast British
Columbia to northwest Alberta. The formation consists of siltstone and dark grey shale, with fine
grained sandstone on the top and dolomitic siltstone in the base. It has unconformable contact
between the Doig formation (in the above layer) and the Belloy formation (in the lower layer).
The depth of the Montney ranges from 2800 m to 3500 m; the average formation thickness is 200
m. The two production zones - the upper Montney and the lower Montney - contain 449 trillion
cubic feet of marketable natural gas, 14,521 million barrels of marketable natural gas liquids and
1,125 million barrels of oil, as estimated by Canada’s National Energy Board. A middle Montney
wedge, which is not pervasive throughout the entire area, spreads between the upper and lower
Montney, separating the two main intervals, as shown in Figure 3-1. Multiple hydraulic fractures
placed along the horizontal wells is the main completion method in the Montney area to achieve
commercial production rates (Kuppe et al.2012).
The geological model (34,000 m × 18,000 m × 200 m), containing 27 horizontal wells in this study
is built by PETREL (Schlumberger), based on a block in a liquid-rich gas reservoir in the Great
Kakwa area of the Montney formation. Structural surfaces are built based on well tops where four
horizons - Doig, top Montney, middle Montney and low Montney are generated. The horizons
consist of three zones: the top Montney zone (Doig to top Montney), the middle Montney zone
(top Montney to middle Montney) and the low Montney zone (middle Montney to low Montney)
33
(Figure 3-1). Most of the horizontal wells underlie the upper Montney and overlie the low
Montney, spreading into the middle Montney zone. The same trend appears in the wells shown in
Figure 3-2 and Figure 3-3.
Figure 3-1 Kakwa area type log (Kuppe et al. 2012)
34
Figure 3-2 Four horizons and wells location
Figure 3-3 Mixed hydrocarbon system (Kuppe et al., 2012 )
35
The depth of the Montney top to the surface ranges from 2800 m to 3500 m and average formation
thickness is 200 m. The model consists of 4,896,000 grids, including 680 grids in the I direction,
360 grids in the J direction and 20 grids in the K direction. The geological model and collected
wells are shown in Figure 3-4.
The formation is characterized as being over-pressured, lacking aquifer and having variable
liquid/gas rations, which, combined, leads to the thermal cracking of the oil, forming gases over
geological time (Figure 3-3). Due to the higher temperature in the deeper part of the Montney,
thermal cracking is continuous and generates enormous gas, resulting in mixed hydrocarbons and
an over-pressured system. Thus, the gas is forced by the overly high pressure to migrate to the
upper dip, forming a regional pressure gradient (Kuppe et al.,2012).
Figure 3-5 depicts the permeability and porosity distribution of the geological model, where the
matrix permeability ranges from 0.004 to 0.009 md, porosity is between 2% and 9%, and connate
water saturation is 30%.
36
Figure 3-4 3D View of geologic model
(a) matrix permeability distribution (b) ) porosity distribution
Figure 3-5 Properties of the geological model
37
3.2 Reservoir Simulation Model
3.2.1 Model Description
The geological model is updated and imported into the CMG, creating an original simulation
model. The gas-liquids concentrations in Montney is determined by formation temperature,
pressure and facies. Pad 2, Pad 8 and Pad 19 (Figure 3-6) are the main research fields of this study.
Based on the geological model, the numerical simulation model is created. First, the geological
model constructed by Petrel is upscaled. Then, a target model, including three wells as shown in
Figure 3-7, is cut out as a sub-model and exported directly into CMG GEM to create the simulation
model.
The length of the multi-fractured well-1 is 2,500 meters with 28 stages, well-2 is 2,100 meters with
27 stages and well-3 is 3,000 meters with 31 stages. The average stage spacing is 80 m and the
perforation type is open-hole. The reservoir model has the dimensions of 1,050 m x 3,800 m x 60
m. There are 21 grids in the I direction, 76 grids in the J direction and 7 grids in the L direction,
which corresponds to the reservoir model’s width, length, width and thickness. Local refining grids
are generated to represent the hydraulic fractures in the reservoir model.
38
Figure 3-6 Accumap view of well pads
The properties of the heterogeneous simulation such as initial reservoir condition, permeability,
porosity and hydraulic properties, are listed in Table 3-1. Relative permeability curves of the
matrix are obtained from a reference paper (Lan, 2015) on experiments of sample studies from the
Montney tight gas play, as shown in Figure 3-9. In hydraulic fractures, the relative permeability
curves are applied as two straight lines.
39
Table 3-1 Reservoir model properties
Reservoir temperature (℃) 98
Reservoir Pressure (MPa) 30.5
Matrix permeability(md) 0.004~0.009
Matrix porosity 0.02~0.09
Matrix water saturation 0.3
Dew point pressure (MPa) 21.2
Hydraulic facture half-length (m) 125
Hydraulic facture height (m) 40
Primary facture width (m) 0.008
Intrinsic permeability (md) 8000
Figure 3-7 3D view of simulation model containing target wells
40
(a) Permeability distribution
(b) Porosity distribution
Figure 3-8 Permeability and porosity variation of the simulation model
41
(a) Oil and water relative permeability curve (b) Liquid and gas relative permeability curve
Figure 3-9 Relative permeability curves for Montney formation
3.2.2 Hydraulic Fracture – Local Grid Refinement
To make the hydraulic fracture model more explicit, local grid refinement is adopted to create
smaller and more accurate grids to simulate the hydraulic fracture. The local grid refinement of
the hydraulic fracture is shown in Figure 3-10.
42
Figure 3-10 Local refined grids near the hydraulic fracture
Assuming that the conductivity of the actual fracture is equal to the conductivity in the fracture
fairway blocks in the simulation model:
𝑘𝑒𝑓𝑓 ∙ 𝑤𝑔𝑟𝑖𝑑 = 𝑘𝑓 ∙ 𝑤𝑓
The minimum grid block width in the simulation cannot be smaller than the well radius. The
fracture grid is equals to the smallest grid width, which is set to 2 feet.
3.2.3 PVT Model
The area of interest is a liquid rich gas zone. Oil and gas samples are collected from the separator
and recombined with the production gas oil ratio of 1200m3/m3 to analyze the phase behavior of
the reservoir fluids. Table 3-2 shows the gas and liquid components. Accurate evaluations of gas-
oil ratios are crucial for the history matching and oil and gas production forecasts. Based on raw
data from sampling and laboratory PVT tests, the PVT models were developed and the reservoir
fluid system were estimated. Figure 3-11 depicts the calculated phase envelope of the recombined
fluid. The dew point temperature is 64℃ and the dew point pressure is 23.2 MPa. The reservoir
43
condition (98 ℃, 30.5 MPa) belongs to the retrograde condensation area of the generated phase
envelope, as shown in Figure 3-11.
The reservoir pressure decreases during the primary production, while the reservoir temperature
remains constant. When the pressure drops below the dew point pressure, oil begins to condense
from the gas phase, entering the two-phase envelope area. Gas condensate forms in the reservoir
and remains immobile until a critical saturation has been reached. The newly-formed liquid
reduces the amount of condensate (oil) production at the surface and blocks gas from flowing
towards the wellbore, thus reducing the gas production at the same time. Maintaining reservoir
pressure above the dew point pressure while developing the liquid rich gas reservoirs is critical for
the development of liquid rich gas reservoirs.
Table 3-2 Gas and liquid components table
Component Gas (%) Liquid (%)
CO2 0.06003 0.059964
CH4 11.94597 80.45947
C2H6 5.902951 10.83688
C3H8 7.653827 5.197216
IC4 2.341171 0.787521
NC4 6.193097 1.566574
IC5 3.051526 0.356713
NC5 3.941971 0.376825
FC6 5.242621 0.205348
C7+ 53.66683 0.153482
Sum 100 100
44
Figure 3-11 P-T diagram
3.2.4 History Match
History matching was performed to tune the reservoir simulation model. The bottom-hole
pressures of the producers were applied as constraints while oil and gas rates were matched. Figure
3-12 shows the history matching result for well-3. It can be seen that, the gas rate and oil rate
match well with the production history. The production history has been honored and the model is
accurate and reliable enough for reservoir simulations and production predictions. The model can
also be used to evaluate the performance of enhanced recovery methods, which are reported in the
next section.
45
(a) Gas rate history match (b) Oil rate history match
Figure 3-12 History matching result for well-3
3.3 Enhanced Hydrocarbon Recovery methods
3.3.1 Reservoir Performance
As aforementioned, it is essential to keep the reservoir pressure above the dew point pressure for
a liquid rich gas reservoir, as indicated by the phase diagram. Primary production studies suggest
that the average reservoir pressure drops to 22.8 MPa after 6 years of depletion, as shown in the
base case in Figure 3-14. The base case represents the scenario where the primary production is
applied. The P-T diagram of the reservoir fluids (see Figure 3-11) has suggested that liquid would
be condensed out below such pressure and reservoir fluids enters the two-phase region. Pressure
maintenance technique needs to be applied by injecting fluids into the reservoir to keep a preferable
pressure in the formation. Thus, Well-2, which locates in the middle, is then converted into an
46
injection well while well-1 and well-3 are kept as producers. Water, CO2 and cyclic gas are injected
into the formation, respectively, for 10 years to increase reservoir pressure.
It should be noted that the cyclic gas flooding is different from the cyclic gas huff-n-puff method.
In the cyclic gas flooding, the separated gas produced from the production wells is injected into
the injection well continuously to maintain the reservoir pressure. While for the cyclic gas huff-n-
puff method, the produced gas from the puff period is separated and re-injected into the same well
during the huff period. The huff and puff operations are conducted via the same producer and no
particular injector is needed.
Figure 3-13 shows the cumulative gas and oil production of cyclic gas flooding, CO2 flooding, and
water flooding for the targeted formation. The injection pressure for all three scenarios are 45 MPa.
As aforementioned, the base case represents the scenario of primary production without any
injection. Cyclic gas flooding leads to the highest gas and oil cumulative production, as compared
with the CO2 and water injection cases. It should be noted that Figure 3-13a depicts the total
cumulative gas production, which contains produced CO2 for the CO2 flooding and a portion of
injected natural gas for the cyclic gas scenario. Take CO2 flooding for example, although the total
gas production rate is higher than that of the base case, the cumulative gas production of the CO2
injection scenario is lower than the base case after removing the CO2 from the produced mixture.
Table 3-2, which demonstrates that the cumulative natural gas production are close among
different scenarios while that of the base case is slight higher than the rests.
47
Cyclic gas flooding and CO2 flooding both enhance cumulative oil production significantly. The
cumulative oil production of the cyclic gas flooding is 52.7% higher than that of the base case and
CO2 flooding indicates a 40.0% improvement in cumulative oil production as shown in Figure 3-
13b. It indicates the applicability of cyclic gas flooding in the liquid rich gas reservoirs. In addition,
the water injection scenario results in a lower cumulative gas production but a higher cumulative
oil production than those of the base case scenario. This is because the injected water reduces the
relative permeability of the gas phase, decreasing its ability to flow to the wellbore. Meanwhile
the higher reservoir pressure due to water injection helped preventing oil from condensing in the
reservoir.
There is a high gas saturation near well-2 for the cyclic gas flooding and needs to be re-produced
at the end of the enhanced hydrocarbon recovery process. After 10 years’ injection, well-2 is
converted back into a producer and put on production. A large amount of gas and oil are produced
during such process, significantly increasing both the cumulative gas and oil production. It should
be noted that the volume of the injected gas needs to be subtracted to achieve the net cumulative
gas production for cyclic gas flooding. Table 3-2 shows the calculated net natural gas production
of the four scenarios.
48
(a) Cumulative gas production
(b) Cumulative oil production
Figure 3-13 Cumulative oil and gas production of various injection fluids
49
Figure 3-14 compares the reservoir pressure of the base case with that of the cyclic gas, CO2 and
water injection scenarios during the production period. The primary production period is from the
beginning to 2190 days. At that point, the production well-2 is converted into an injection well and
different injection scenarios are conducted.
The figure shows that the reservoir pressure increases for all the injection scenarios, while the
cyclic gas flooding scenario indicates the highest rise in reservoir pressure, followed by the CO2
and water scenarios. All injection scenarios share the same injection pressure of 45 MPa at the
injector. Well-2 of the cyclic gas flooding scenario, is opened to production again at 5475 days;
the average reservoir pressure starts to drop fast since this process starts. An intense pressure
drawdown exists between the reservoir formation and well bottom hole, which leads to a
significant enhancement of oil and gas production. Overall, cyclic gas flooding is the most
effective for improving the average pressure. CO2 flooding has the secondary ability to improve
reservoir pressure, while water flooding sits at third place, due to the low porosity and permeability
of shale reservoirs and weak liquid injection capacity.
50
Figure 3-14 The Impact of injection fluids on reservoir pressure during production time
The barrel of oil equivalent (BOE) is adopted to assess the gas and oil productivity. BOE is
industrial unit of energy equivalent to the amount of energy released by burning one barrel of crude
oil. The calculated BOE results are shown in Table 3-2. Cyclic gas flooding displays the largest
BOE calculation, followed by CO2 flooding, base case and water flooding. In addition, the BOE
of the water flooding is lower than that of the base case. This is because the injected water has
decreased the effective gas permeability in the formation, leading to a lower gas production rate.
In other words, the increase of oil production due to a higher reservoir pressure during water
flooding cannot compensate for the loss of gas production, as compared with the base case. The
51
cumulative oil production of the base case is the lowest among all scenarios, as the low reservoir
pressure of the base case promotes oil to be condensed and left unproduced in the reservoir.
Table 3-3 Cumulative production for different enhanced hydrocarbon methods
Cyclic gas CO2 Water Base case
Cumulative injected volume (m3) 1.00×109 1.71×109 1.51×106 0
Cumulative natural gas production (m3) 2.60×109 1.60×109 1.52×109 1.74×109
Net cumulative gas production (m3) 1.60×109 1.60×109 1.52×109 1.74×109
Cumulative oil production (m3) 576,924 528,924 421,922 377,781
BOE 1.43×107 1.39×107 1.25×107 1.34×107
NPV ($) 3.11×108 2.50×108 2.40×108 2.69×108
3.3.2 Phase Envelop Change
The phase diagram will change during the cyclic gas flooding and CO2 flooding process due to the
compositional change of the reservoir fluids. Figure 3-15 and Figure 3-16 show the new phase
diagram with the production GOR equaling 1500 and with CO2 injection. It can be seen that both
the critical pressure and temperature decrease and the two-phase region shifts to the left, compared
52
to Figure 3-11. Such changes will help prevent the oil condensation in the formation under
reservoir condition and further increase the oil production at the surface.
(a) Original P-T diagram without gas injection (b) P-T diagram with cyclic gas injection
Figure 3-15 P-T diagram of different gas oil ratios during cyclic gas injection
(a) Original P-T diagram without gas injection (b) P-T diagram with CO2 injection
Figure 3-16 P-T diagram of different gas oil ratios during CO2 injection
53
3.3.3 NPV Calculation
The net present value of the enhanced hydrocarbon recovery processes has been briefly estimated
via the following equation (Yu and Sepehrnoori, 2014):
𝑁𝑃𝑉 = ∑(𝑉𝑜𝑖𝑙+𝑉𝑔𝑎𝑠−𝐶𝐹)𝑗
(1+𝑖)𝑗 − [∑ (𝐶𝑤𝑒𝑙𝑙 + 𝐶𝑓𝑟𝑎𝑐𝑡𝑢𝑟𝑒) + 𝐹𝐶𝑁𝑘=1 ]𝑛
𝑗=1 (3-1)
Where 𝑉𝑜𝑖𝑙 and 𝑉𝑔𝑎𝑠 are annual gas and oil revenue, 𝐶𝐹 is all the related cost due to injection,
𝐶𝑤𝑒𝑙𝑙 and 𝐶𝑓𝑟𝑎𝑐𝑡𝑢𝑟𝑒 are the costs of the horizontal wells and hydraulic fractures, N is the number
of horizontal wells, n is number of periods and i is the discount rate or interest rate, FC is other
cost, such as cost related to well type conversion and operations. There is no well type conversion
cost for base case.
For the comparison of the four scenarios, 𝐶𝑤𝑒𝑙𝑙, 𝐶𝑓𝑟𝑎𝑐𝑡𝑢𝑟𝑒, N, n and i are the same. The equation is
simplified as:
𝑁𝑃𝑉 = ∑(𝑉𝑜𝑖𝑙+𝑉𝑔𝑎𝑠−𝐶𝐹)𝑗
(1+𝑖)𝑗𝑛𝑗=1 − 𝐶 (3-2)
In this study, the gas price of $3.0/Mcf, the oil price of $50/Barrel, and the interest rate of 10% are
used to calculate the revenue. Cyclic gas uses the produced gas from the producers, so no
transportation costs occur. The CO2 cost is $1.0/Mcf plus a $0.50/Mcf transportation charge (Cook,
2012), while water cost is $6/ Barrel. The NPV for each scenario appears in Table 3-3. Cyclic gas
flooding presents the best economical result, increasing the NPV by 16% compared with that of
the base case. CO2 flooding does not show advantages in the NPV calculation due to the high cost.
Water flooding shows obvious negative BOE effects in this tight liquid rich gas reservoirs.
54
In summary, cyclic gas flooding has considerable influence in pressure maintenance and
hydrocarbon production improvement, while CO2 flooding also leads to favorable production
enhancement. Water injection is not feasible in the target reservoir. The availability of the
produced gas on the well site and little transportation cost proves cyclic gas as the best choice to
enhance production in the Montney liquid rich gas play.
Table 3-4 NPV for different enhanced hydrocarbon methods
Cyclic gas CO2 Water Base case
Cumulative natural gas production (m3) 1.60×109 1.60×109
1.52×109 1.74×109
Cumulative oil production (m3) 576,924 528,924 421,922 377,781
NPV ($) 3.11×108 2.50×108
2.40×108 2.69×108
3.4 Conclusions
The simulation approach is applied to study the characters of liquid rich gas tight reservoir. Three
injection methods, including cyclic gas flooding, CO2 flooding and water flooding are conducted
to compare the enhanced hydrocarbon recovery. We arrived at the following conclusions:
(1) Cyclic gas and CO2 flooding are more feasible in the targeted tight liquid rich gas reservoirs
than water flooding. After 6 years of primary production and 10 years of gas flooding in the
hydraulic fractured tight gas reservoir, cumulative oil and gas production are increased
significantly as compared to the production from keeping the depletion process.
55
(2) Cyclic gas flooding brings better results in increasing cumulative gas and oil production. The
cumulative oil productions is 52.7% higher than that of the base case. The NPV calculation also
indicates that cyclic gas is the most economical method, considering the easy access of the
injection gas resource and no gas separation charge.
(3) CO2 flooding displays a secondary outcome, being 40.0% higher than that of the base case, but
it costs more to acquire a CO2 gas source. Transportation charges and separation fees should be
considered.
(4) Water flooding is the worst option to enhance production or improve field pressure due to poor
injection ability in low permeability reservoirs.
(5) The PVT models’ study shows that cyclic gas and CO2 flooding will change the critical
temperature and pressure and increase the gas phase area in the PVT diagram, resulting in more
gas production and less oil condensation. This result supports the EHR capacity of cyclic gas and
CO2 flooding from the phase state theory.
56
Chapter Four: Sensitivity Studies on Cyclic Gas Flooding Performance
The performance of cyclic gas flooding in the tight reservoir is dependent on numerous parameters
including the fracture properties, such as fracture half-length, fracture conductivity and height,
operational parameters, such as production bottom hole pressure and injection time, and geologic
parameters, such as reservoir permeability and porosity. This complex and interactive effects of
the above factors have not been sufficiently studied in the tight liquid rich gas reservoirs. Thus, in
this study, several simulation models are constructed to conduct the sensitivity analysis. The
operational and geological factors, including primary production duration, bottom hole pressures
(BHP) during primary production and EHR process, matrix permeability and non-Darcy effects,
are conducted and their effects on well production performance are studied.
4.1 Effect of BHP
A base simulation model was constructed based on the tight liquid rich gas reservoir model
investigated in the former chapter. The sensitivities of the geological reservoir and hydraulic
fracture parameters for a horizontal well with multiple hydraulic fractures in the tight gas reservoir
are analyzed. The model dimensions are 1,050 meters in length, 3,800 meters in width, and 60
meters in height. Only one horizontal well is included when investigating the effect of BHP on
well performance and the well is 2,100 meters in length, with 27 stages of fractures.
The volume of the liquid condensed from the gas phase is determined by the in-situ pressure. A
lower BHP leads to a higher gas production rate at the well bottom hole but more condensate
57
formed in the reservoir. Such condensate liquids are typically immobile and cannot be produced.
Two scenarios are created to study the influence of BHP on gas and oil recovery:
Scenario 1: Pressure depletion production is conducted under a BHP of 15 MPa during a
production period of 20 years.
Scenario 2: Pressure depletion production is conducted under a BHP of 5 MPa during a production
period of 20 years.
Figure 4-1 depicts the cumulative oil and gas production under a high BHP of 15 MPa and a low
BHP of 5 MPa. The results show that in the first couple of months, the oil and gas production
under the low BHP are higher than those under the high BHP, which is in accordance with the fact
that a larger pressure drawdown yields a higher production rate. The low BHP at the well has not
penetrated deep in the formation, during such a short timeframe. The high in-situ pressure in the
deep section of the formation has kept the heavy components (i.e., condensate) in the gas phase.
Under such circumstances, a higher gas production rate brings more heavy components to the
wellhead simultaneously, resulting in high gas and oil production.
As production proceeds, oil starts to condense from the gas phase and is left behind in the
formation. The cumulative gas production of the 5 MPa scenario remains high, yet the oil
production rate is much lower than that of the 15 MPa scenario.
58
(a) Cumulative gas production
(b) Cumulative oil production
Figure 4-1 Cumulative production under different well BHPs
59
The BOE (Table 4-1) of the two scenarios after 20 years is 4,881,367.18 in the 15 MPa scenario
and 7,501,329.30 in 5 MPa scenario. The BOE of the 5 MPa scenario is 54% higher than that of
the 5 MPa.
Table 4-1 Data of the Cumulative production under different well BHPs
BHP (MPa) Gas production
(106m3)
Oil Production
(103m3)
BOE
15000 580 175 4881367.18
5000 1132 100 7501329.30
4.2 Effect of Different Primary Production Time
At the end of the primary production stage, gas injection is used to supplement the reservoir energy.
The primary production duration is a critical parameter to optimize the entire production process.
A simulation model containing three wells, similar to Figure 3-7, is created. Three scenarios of
different primary production times of 5 years, 10 years and 15 years are examined to determine an
appropriate primary production period.
Scenario 1: The pressure depletion method is conducted in the primary production for 5 years, then
cyclic gas flooding is adopted for the following10 years. Afterwards, the injection well is re-altered
as a production well. The three wells operate as production wells for 20 years. The total production
duration is 35 years.
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Scenario 2: The pressure depletion method is conducted in the primary production for 10 years,
then cyclic gas flooding is adopted for 10 years following. Afterwards, the injection well
reconfigured as a production well. The three wells operate as production wells for 15 years. The
total production duration is 35 years.
Scenario 3: The pressure depletion method is conducted in the primary production for 15 years,
then cyclic gas flooding is adopted for 10 years following. The injection well is re-altered as the
production well. The three wells operate as production wells for 10 years. The total production
duration is 35 years.
Scenario 4: The pressure depletion method is conducted for 35 years; no injection method is
conducted.
The cumulative productions for oil and gas at the end of the production process are shown in Figure
4-2. As can be seen in Figure 4-2b, the cumulative oil productions of the cyclic gas flooding
scenarios are 37% to 50% higher than that of the no injection scenario. The injected gas improves
the reservoir pressure significantly and prevents the oil from being condensed out. As shown in
Figure 4-3, the reservoir pressure of the cyclic gas flooding is much higher than that of the no
injection scenario. Also, the scenario which implements cyclic gas flooding in year 5 yields the
highest oil production, followed by the 10-year scenario and 15-year scenario. Thus, the sooner
the cyclic gas is injected, the higher the cumulative oil production.
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The cumulative gas productions of the three cyclic gas flooding scenarios are almost the same at
the end of the production period. The sudden increase of gas production in Figure 4-2 and decrease
in pressure in Figure 4-3 are due to the start of reservoir depletion. It should be noted that for the
cyclic gas flooding scenarios, part of the produced gas will be injected and re-produced from the
reservoir; the net gas cumulative production, as shown in Table 4-2, is even a little less than that
of the no injection scenario. Cumulative oil production, however, has increased significantly.
Overall, the 5-year scenario shows the largest BOE result.
(a) Cumulative gas production
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(b) Cumulative oil production
Figure 4-2 Comparison of different primary production time
Figure 4-3 Average field pressure
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Table 4-2 Production data of different primary production time
Scenario 15-year 10-year 5-year No injection
Cumulative gas (106m3) 2891.91 2885.97 2870.81 1961.08
Injected gas (106m3) 1118.90 1061.64 1006.68 0
Net cumulative gas(106m3) 1773.01 1824.33 1864.14 1961.08
Cumulative oil(103m3) 566.02 580.39 596.91 398.11
BOE 1.54107
1.54107
1.56107
1.57107
1.49107
4.3 Pressure-dependent Permeability
Natural fractures may present and be activated during the hydraulic fracturing in tight liquid rich
gas reservoirs. These natural fractures are usually not propped or are poorly propped, compared
with hydraulic fractures, which are well propped by the proppant during the fracturing process.
The reservoir pressure will decrease significantly during the initial production period. The
conductivity of the natural fractures is sensitive to the pore pressure (Palmer et al. 2007; Navarro,
2012). Compared with the matrix, natural fractures are more deformable and their conductivity is
the dominate factor influencing the liquid and gas flow within. (Tao et al. 2009). Researchers have
conducted experiments and constructed theoretical equations to illustrate the relationship between
natural gas permeability and changes of stress. In this study, the changing permeability with
pressure is considered in the simulation model.
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The following relationship between natural fracture permeability and pressure as shown in Table
4-3. It is applied in the reservoir simulation to investigate the effect of pressure-dependent
permeability on well production. Two scenarios are generated to study the sensitivity:
Scenario 1: A pressure dependent permeability is considered in the simulation model, with a
production time of 4 years.
Scenario 2: A constant permeability is set up in the simulation model, with a production time of 4
years.
Cumulative oil and gas productions of the pressure-dependent permeability scenario and constant
permeability scenario are shown in Figure 4-4. As expected, scenario 1 considering pressure
dependence produces less gas and oil than those of scenario 2, the constant permeability. In
addition, the change in permeability of the hydraulic fracture has insignificant influence on the
well during after stimulation production in this study. This is a consequence of the hydraulic
fractures being well propped and the ultralow matrix permeability (0.001mD), making the
hydraulic fractures ‘infinite’ conductivity across the changing range.
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Table 4-3 Pressure-dependent permeability table (Cho, 2013)
Pressure(MPa) Porosity Current Permeability/Initial
Permeability
21.5 99.7% 10%
25.5 99.8% 50%
27.5 99.9% 70%
29.5 99.9% 90%
30.5 100% 100%
(a) Cumulative gas production (b) Cumulative oil production
Figure 4-4 Comparison of two cases with and without pressure compactions
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4.4 The Effect of Non-Darcy Flow in Hydraulic Fractures
In tight liquid rich gas reservoirs, non-Darcy flow behavior appears, resulting in additional
pressure loss in hydraulic fractures when the gas flow rate exceeds the limit for Darcy’s Equation
application scope. The Reynolds number and the Forchheimer number are key criteria to identify
the non-Darcy flow. The Forchheimer equation (Equation 4-1) is used to study the non-Darcy
effect in gas condensate reservoirs (Rubin, 2010, Yu. 2014).
−∇𝑝 =𝜇
𝑘𝑣 + 𝛽𝜌𝑣2 (4-1)
Where μ is viscosity, v is velocity, k is hydraulic fracture permeability, β is the non-Darcy Beta
factor, ρ is the density of certain phase.
Two scenarios are created to study the impact of the non-Darcy effect on the gas and oil flow rates:
Scenario 1: The non-Darcy effect is considered in the simulation model with the pressure depletion
production method.
Scenario 2: The non-Darcy effect is not considered in the simulation model with the pressure
depletion production method.
Figure 4-5 depicts the well production performance while considering and ignoring the non-Darcy
flow effects. As shown in the figure 4-5a, considerable differences exist between the gas
production rates with the two scenarios. Ignoring the non-Darcy flow effects can over-estimate the
gas flow rate by 40% after rate curve stables in the first 3 month. Figure 4-5b demonstrates that
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the oil rates are almost unchanged due to a low oil flow rate in the fractures compared to the gas
rate.
(a) Gas rate of Darcy and non-Darcy flow (b) Oil rate of Darcy and non-Darcy flow
Figure 4-5 Comparison of Darcy and non-Darcy flow
4.5 Hydraulic Fracture Height
The Montney formation is composed of different rock types, such as limestone, shale stone,
siltstone and so on. Siltstone is a clastic sedimentary rock composed of silt-sized particles. Shale
are rocks that contain mud, with a variable range of silt and clay. Siltstone is differentiated in being
predominately silt, not clay. Shale is harder than siltstone. Hydraulic fracture height growth is
easily influenced by several factors, as fracture azimuth is strongly determined by in situ stress but
hardly changed by other factors. During the hydraulic fracturing process, fractures will grow in
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one direction in the same rock layer. Once they meet different sediment rock, the vertical height
will interfere, thereby stopping growth in height while promoting growth in length.
Except for the observed permeability and porosity, several factors are uncertain, especially the
hydraulic fracture parameters, such as half-length and facture height. As observed from the
geology reports, the grand layer is mainly composed of siltstone, mixed with bits from the shale
stone layer at about 3107 meters’ depth, which will inhibit the growth of fracture height. In this
study, the possible influence of the mixed shales on fracture height is investigated. Two scenarios
with different fracture heights are created:
Scenario1: The fracture fails to grow through the nearby shale stone, with a fracture height of 40
meters. History match is conducted first in the primary 400 days, then the well is set to produce
with BHP of 10000 kPa for 5 years.
Scenario2: The fracture grows through the nearby shale stone, with a fracture height of 60 meters.
History match is conducted first in the primary 400 days, then the well is set to produce with BHP
of 10000 kPa for 5 years.
It should be noted that, the two scenarios share the same fracture volume, which can be estimated
by the tonnage of the injected proppants. Results of the cumulative oil are shown in Figure 4-6. As
can be seen that with the same production history, scenario 1 shows higher oil production potential
than Scenario 2 in the long-term production. During hydraulic fracturing, if the fractures do not go
through the barrier shale (vertical direction), it will grow in horizontal directions, promoting
69
production from the formation. This is in accordance with the knowledge that the mix of shale
stone disturbs the vertical growth of the fracture height.
Figure 4-6 Cumulative oil production under two fracture heights
4.6 Hydraulic Fracture Conductivity
Dimensionless fracture conductivity is an important design parameter in hydraulic fracturing
design, and include reservoir permeability, fracture length, fracture width, and proppant
permeability. Dimensionless fracture conductivity is a useful method to evaluate the adequacy of
fracture conductivity. It compares the ability of the hydraulic fracture to deliver the fluids and gas
into the wellbore with the capacity of the formation to transmit the fluid into the fracture (Pearson,
2001).
The equation of dimensionless hydraulic fracture conductivity:
70
𝑐𝑓𝑑 =𝑘𝑓∙𝑤𝑓
𝑘𝑚∙𝐿𝑓 (4-1)
Where 𝑐𝑓𝑑 is the dimensionless hydraulic fracture conductivity, 𝑘𝑓 is the fracture permeability, 𝑤𝑓
is the fracture width, 𝑘𝑚 is the matrix permeability, and 𝐿𝑓 is the hydraulic feature half-length.
In the study’s simulation model, three scenarios, with a dimensionless conductivity of 10, 50,100,
are adopted. As shown in Figure 4-7, the cumulative gas of dimensionless conductivity of 100 is
the highest, followed by that of 50 and the dimensionless conductivity of 10 scenario displays the
lowest cumulative gas production. The higher dimensionless fracture conductivity indicates larger
cumulative gas production, which corresponds to the definition of fracture conductivity in
representing the fracture’s capacity to transmit fluid.
The cumulative oil production curves, however, demonstrate different behavior. At the primary
production period of the first 500 days, the dimensionless conductivity of 100 and 50 are close in
showing a larger oil production while the dimensionless conductivity of 10 has the lowest oil
production. During 500 to 1000 days, the oil production rate of dimensionless conductivity of 100
and 50 tends to grow more slowly than that of the dimensionless conductivity of 10. During 1000
to 1600 days, the cumulative oil production of the dimensionless conductivity of 10 catches up
with the two higher scenarios. At the end of 1600 days, the oil production of the conductivity of
10 exceeds the other two scenarios.
71
(a) Cumulative gas production
(b) Cumulative oil production
Figure 4-7 Cumulative production of the two cases
72
In the two higher dimensionless conductivities, the fracture transmit ability is much higher, which
means that the reservoir pressure drops faster. The reservoir pressure declines quickly down to the
dew point pressure; liquids begin to condensate near the wellbore and block the gas from flowing
to the wellbore. The condensate liquid remains unrecovered in the reservoir, decreasing the oil
production rate significantly. Thus, in the scenario of the dimensionless conductivity of 10, the
pressure drops more slowly, resulting in higher oil production.
4.7 Conclusion
The study shows that production behaviors are very sensitive to primary bottom hole pressure
(BHP), primary production time and hydraulic fracture conductivity, while non-Darcy can affect
the gas flow rate but has no significant effect on oil production rate.
(1) A lower BHP leads to a higher pressure difference and, thus, higher gas production. In the long
term, pressure rapidly drops below the dew point pressure, leading to a large amount of liquid
condensation, which significantly decreases oil production.
(2) Gas injection methods are adopted to maintain the field pressure, while primary pressure
depletion time becomes a key factor to optimize the pressure maintenance performance. Through
the comparison of the three scenarios, 5 years of primary production time outperforms the other
two scenarios.
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(3) Non-Darcy flow behavior exists with a high gas rate doesn’t have a noticeable difference in
the oil production. This is because that the oil flow rate in the fractures is much lower compared
to that of the gas.
(4) Different fracture heights are applied in the history matching process and the long production
performance of the wells are investigated. The results show that the shorter fracture height and
longer fracture length leads to a higher oil production.
(5) A higher hydraulic fracture conductivity is beneficial to both cumulative gas and cumulative
oil production during the initial production period. As the reservoir pressure drops below the dew
point pressure, however, significant quantities of condensate oil will emerge from the gas phase,
blocking the gas flow to the wellbore and reducing oil production.
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Chapter Five: Optimization of gas injection in tight liquid rich gas reservoir
Three EHR methods, including cycling gas injection, CO2 flooding and water injection are
investigated for the Montney liquid rich gas reservoir in Chapter 3. Results show that cyclic gas
and CO2 flooding are more feasible in this ultra-low unconventional reservoir than water flooding
due to the injection difficulty and low water sweep efficiency in the reservoir. This chapter further
studies the mechanisms and optimization of the performances of cyclic gas and CO2 flooding. The
experimental design technique is adopted to maximize the cumulative production and the net
present value of the targeted section. Results indicate that more injection wells, shorter primary
production time, higher BHP for primary production and injection BHP, shorter injection time and
lower later period BHP lead to an optimal scheme of cyclic gas flooding and CO2 flooding
methods. Details are presented in this Chapter.
5.1 Parameters Considered in the Simulation Model
Based on the previous investigation of pressure maintenance methods, cyclic gas flooding and CO2
flooding are both feasible to enhance the recovery factor from the targeted tight liquid rich gas
reservoir. The well operational parameters, such as the number of injection wells, primary
production time, BHP during the primary production, injection pressure, injection time are studied
and their effects on the well production are analyzed.
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The reservoir simulation model (Figure 5-1) contains 21 grids in the I direction, 76 grids in the J
direction and 7 grids in the K direction, with dimensions of 1050 m x 3800 m x 60 m. It includes
five hydraulic fractured horizontal wells. The development of the reservoir involves three periods:
the primary production period, the injection period, and the late production period. In the primary
production period, all wells are production wells using pressure depletion mode. In the injection
period, the reservoir pressure drops below the dew point pressure, a significant amount of liquids
condensate, cumulating around the wellbore, blocking the gas flow path and significantly
decreasing the production rates. Thus, several production wells are selected to be converted as
injection wells for cyclic gas flooding or CO2 flooding. At the end of the injection period, the
injection wells are converted back to production wells to make the best use of reservoir energy for
the cyclic gas flooding.
Figure 5-1 2D View of the Simulation Model
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5.1.1 Number of Injection Wells
Based on the previous chapter, two injection scenarios, including one injection well (well-3) and
two injection wells (well-2 and well-4) are designed, as shown in Figure 5-2. In the tight reservoir,
it is harder for the low pressure at the producers to spread far away as the low reservoir
permeability limits the flow of the reservoir fluids. Consequently, injection wells located at the
axial and central part are more efficient to improve the sweep efficiency and enhance gas and oil
recovery.
(a) Simulation model with one injection well
77
(b) Simulation model with two injection wells
Figure 5-2 3D View of simulation models
5.1.2 Parameters of Primary Production
In the primary period, a low pressure at the producers creates a pressure difference, forcing
reservoir fluids flow to the producer while reservoir pressure keeps reducing. In this stage, all the
five wells are production wells. With further exploration and development of the reservoir,
formation energy decreases continuously and reservoir pressure drops, approaching the dew point
pressure. Fluid injection should be conducted to complement formation energy to prevent the form
of liquids condensate once this happens.
78
The primary period production duration is an important parameter in sensitivity analysis and
optimization of the reservoir performance. In this study, the four primary production times of 4, 6,
11 and 16 years are investigated, respectively. Another vital parameter in the primary period is
bottom hole pressure (BHP). Four BHP of 6 MPa, 9 MPa, 12 MPa and 15 MPa are considered in
the optimization process.
5.1.3 Parameters of Injection
According to Shahin and Gautam et.al. (1990), when the reservoir pressure drops to a certain
extent, the revaporization ability of the reservoir fluids will be influenced by the dry gas. Thus, the
injection method should consider many factors, such as injection time, injection pressure,
economic assessment and so on. Cyclic gas and CO2 are both feasible recovery methods based on
the previous study discussed in Chapter 3, and will be analyzed here.
Injection pressure candidates include 35 MPa, 40 MPa, 45 MPa, and 50 MPa while the durations
of the injection time are 5 years, 10 years, 15 years and 20 years. During the injection period and
last production stage, the BHP of production wells also affect the ultimate recovery significantly.
The production BHP includes 3 MPa, 6 MPa, 9 MPa and 12 MPa.
5.2 Experimental Design
The simulation of the reservoir performance in an unconventional tight liquid rich gas formation
is time-consuming, especially in the case of many parameters and variables. In this study,
parameters include the number of injection wells (with 2 variables), the primary period production
79
time (with 4 variables), the producer BHP during primary production (with 4 variables), the
injection pressure at injectors (with 4 variables), the injection duration (with 4 variables) and the
producer BHP during the injection period (with 4 variables). If all the combinations, which is to
vary one parameter at a time while keeping all other parameters unchanged, are traversal, there
will be 2,048 groups (2×4×4×4×4×4). This require lots of time and energy as one simulation run
takes over one day to finish. Thus, it is important to achieve maximum optimized results using
relatively less reservoir simulation runs.
Experimental design (DOE, DOX, or the design of experiments) is a design of any task that targets
the variation of parameters under certain conditions. It conducts a new selection method instead
of the rule of “vary one at a time” strategy. In experimental design, two or more parameters can
be varied simultaneously by a predefined rule and pattern. It explains the different choice of
variables and parameters according to certain standards and outputs a series of simulation
combinations. This strategy acquires the same results as that of the “vary one parameter at a time”,
with relatively fewer simulation runs, significantly saving time and energy.
The theory of experimental design was initially developed for agricultural use in the 1920’s. The
theory shifted into computer applications in the 1980’s (Sacks et al., 1989; Welch et al., 1992;
Morris et al., 1993). More and more scientific problems are investigated by the complex computer
models or codes. Chu (1990), Elvind et al. (1992) and Egeland et al. (1992) followed up and
applied experimental design in reservoir simulation. More recently, White et al. (2003), Yeten et
al. (2005) and Peng (2004) adopted experimental design to perform uncertainty analyses,
parameter estimation, forecasting, and optimization in reservoir simulations.
80
The full factorial design is the most common and widely applied strategy of experimental design.
For instance, if there are k factors with L levels per factor, the full factorial design will list every
combination of the factor, which are the Lk combinations. The full factorial design is orthogonal,
as shown in the graphic examples (Figure 5-3).
Figure 5-3 Graphical example of Lk full factorial experimental designs
As the number of factors increase, the full factorial design can be onerous and time-consuming.
The idea of the fractional factorial design only considers the subset of the full factorial design,
greatly reducing the number of combinations but guaranteed to provide enough information for
the main effects. Full factorial design and fractional factorial experimental designs are all
orthogonal.
81
The orthogonal design aims to test the comparative effectiveness of multiple intervention
components. The parameters include allocating two or more levels by using an orthogonal array.
Orthogonal arrays are intended to describe the combinations in the statistical design of
experiments. The orthogonal array is represented as Ln (tc), with L for the orthogonal table code,
n for the number of tests, t for the number of levels, c for the number of columns. For example,
L9(34) means nine tests with a maximum of 4 factors with 3 levels for each factor are run. The
orthogonal array also involves variable factors with a different number of levels; the mixed-level
orthogonal array. For instance, L8 (41×24) represents 8 combinations (tests) with 5 factors, among
which one factor has 4 levels and 4 factors have 2 levels.
In this study, six variables present during cyclic gas flooding. The factors involve the number of
injection wells, primary period production time, BHP during the primary period, injection
pressure, injection time and producer BHP during the injection period. The distribution of levels
are as follows:
Factor 1: Number of injection wells contains two levels (one injection well and two injection
wells).
Factor 2: Primary period production time contains four levels (4 years, 6 years, 11 years and 16
years).
Factor 3: Primary period BHP contains four levels (6 MPa, 9 MPa, 12 MPa and 15 MPa).
82
Factor 4: Injection pressure contains four levels (35 MPa, 40 MPa, 45 MPa and 50 MPa).
Factor 5: Injection time contains four levels (5 years, 10 years, 15 years and 20 years).
Factor 6: Injection period BHP contains four levels (3 MPa, 6 MPa, 9 MPa and 12 MPa).
Factor 1 has 2 levels; the other 5 parameters have 4 levels. A mixed-level orthogonal array of L32
(21×45) is constructed by MINITAB. One factor contains two levels and five factors contain four
levels. 32 combinations of simulation cases are created. By applying the above reservoir
parameters into the orthogonal table, Table 5-1 is constructed.
Table 5-1 Simulation parameters combinations of cyclic gas flooding
Test
Injection Primary Primary Injection Injection Production
wells time(year) BHP(MPa) time(year) pressure(MPa) BHP(MPa)
1 1 4 6 5 35 3
2 1 4 9 10 40 6
3 1 4 12 15 45 9
4 1 4 15 20 50 12
5 1 6 6 5 40 6
6 1 6 9 10 35 3
83
7 1 6 12 15 50 12
8 1 6 15 20 45 9
9 1 11 6 10 45 12
10 1 11 9 5 50 9
11 1 11 12 20 35 6
12 1 11 15 15 40 3
13 1 16 6 10 50 9
14 1 16 9 5 45 12
15 1 16 12 20 40 3
16 1 16 15 15 35 6
17 2 4 6 20 35 12
18 2 4 9 15 40 9
19 2 4 12 10 45 6
20 2 4 15 5 50 3
21 2 6 6 20 40 9
22 2 6 9 15 35 12
23 2 6 12 10 50 3
24 2 6 15 5 45 6
25 2 11 6 15 45 3
26 2 11 9 20 50 6
84
27 2 11 12 5 35 9
28 2 11 15 10 40 12
29 2 16 6 15 50 6
30 2 16 9 20 45 3
31 2 16 12 5 40 12
32 2 16 15 10 35 9
Optimization of the CO2 flooding is almost the same as that of the cyclic gas flooding. The only
difference is that in the late stage of production, the injected wells do not need to be transferred
back to production wells because the CO2 fraction is extremely high around the injection well
(Figure 5-4).
Figure 5-4 CO2 fraction in the late injection period
85
In the orthogonal experimental design of CO2 flooding, injection time will not be considered as a
variable. The five variables involve the number of injection wells, primary period production time,
primary period BHP, injection pressure, and producer BHP of the injection period, almost the same
as the cyclic gas flooding. The orthogonal array and simulation parameters combinations are
shown in Table 5-2.
Table 5-2 Simulation parameters combinations of CO2 flooding
Test
Injection Primary Primary Injection Production
wells time(year) BHP(MPa) pressure(MPa) BHP(MPa)
1 1 4 6 35 3
2 1 4 9 40 6
3 1 4 12 45 9
4 1 4 15 50 12
5 1 6 6 35 6
6 1 6 9 40 3
7 1 6 12 45 12
8 1 6 15 50 9
9 1 11 6 40 9
10 1 11 9 35 12
11 1 11 12 50 3
86
12 1 11 15 45 6
13 1 16 6 40 12
14 1 16 9 35 9
15 1 16 12 50 6
16 1 16 15 45 3
17 2 4 6 50 3
18 2 4 9 45 6
19 2 4 12 40 9
20 2 4 15 35 12
21 2 6 6 50 6
22 2 6 9 45 3
23 2 6 12 40 12
24 2 6 15 35 9
25 2 11 6 45 9
26 2 11 9 50 12
27 2 11 12 35 3
28 2 11 15 40 6
29 2 16 6 45 12
30 2 16 9 50 9
31 2 16 12 35 6
32 2 16 15 40 3
87
5.3 Results and Discussion
After the 32 reservoir simulation combinations created by experimental design are conducted,
cumulative oil and gas are collected by years and evaluated by NPV model. Based on the study in
Chapter Three, the NPV equation is simplified as:
𝑁𝑃𝑉 = ∑(𝑉𝑔𝑎𝑠+𝑉𝑜𝑖𝑙)𝑗−𝐶𝑗
(1+𝑖)𝑗𝑛𝑗=1 (5-1)
In this study, the natural gas price of $3/Mcf, the oil price of $50/Barrel, and the interest rate of
10% are used to calculate the revenue.
The estimated revenue of the 32 cyclic gas flooding scenarios are shown in Table 5-3. The scatter
diagram of Figure 5-7 intuitively reflects the value distribution of the 32 tests. Test 20 shows the
largest revenue calculation result at 158.99 million dollars. Test 23, with a revenue of 151.36
million, and Test 19, with a revenue of 150.82 million, are comparable, ranking in second place.
Test 32, with a revenue of 123.36 million dollars, and Test 16, with a revenue of 124.44 million
dollars, show the worst results.
In Test 20, the injection wells are two, the primary production time is 4 years, the primary BHP is
15 MPa, the injection time is 5 years, injection pressure is 50 MPa and late period production BHP
is 3 MPa. The values of parameters in Tests 19 and 23 reveal the same trend. To demonstrate the
88
mechanism of this phenomenon, the injected gas sweep efficiency is greatly improved with two
injection wells and high injection pressure of 50 MPa.
Figure 5-5 and Figure 5-6 compare the gas saturation and pressure distribution of Test 20, 23, 19
and Test 32 (the worst one). The two figures respectively show the injected cyclic gas saturation
and reservoir pressure at the end of injection time. The average gas saturation of Test 20 is 0.62,
Test 23 is 0.59, and Test 19 is 0.58 while Test 32 is 0.55. The reservoir pressure of Test 20 is about
45,200 kPa, while that of Test 23 is 37,230 kPa, and Test 19 is 37,040 kPa. The reservoir pressure
of the three scenarios is much higher than the 16,900 kPa in Test 32. The design scheme of Test
20 displays greater efficiency than that of Test 32.
(a) Gas saturation of Test 20 (b) Gas saturation of Test 32
89
(c) Gas saturation of Test 23 (d) Gas saturation of Test 19
Figure 5-5 Gas saturation in the 2D simulation model of cyclic gas flooding
(a) Pressure distribution of Test 20 (b) Pressure distribution of Test 32
90
(c) Pressure distribution of Test 23 (d) Pressure distribution of Test 19
Figure 5-6 Pressure distribution in the 2D simulation model of cyclic gas flooding
It is difficult to inject gas and fluid into tight reservoirs due to their low matrix permeability and
porosity. The effect of sweep efficiency is particularly vital. In the primary production stage,
pressure depletion is the development method. Once the reservoir pressure drops below the dew
point pressure, gas and oil recovery will decline significantly. A short primary production time
and high bottom hole pressure tend to postpone the rapid decline of reservoir pressure. The cost of
injected cyclic gas also warrants consideration. The annual interest rate factors greatly, as the
longer the recovery time cost, the lower the income yielded. Thus, a short injection time (cycle
time) with a high injection pressure provides a rapid gas injection method, saving time and gas
injection expense. A low production bottom hole pressure, after cyclic gas flooding, will maximize
gas liquid production and recover the injected cyclic gas significantly.
91
Table 5-3 Calculated Revenue of cyclic gas flooding
Test 1 2 3 4 5 6 7 8
Revenue 148.09 141.83 138.72 136.14 140.48 145.01 132.89 134.37
(106USD)
Test 9 10 11 12 13 14 15 16
Revenue 135.35 134.76 132.61 133.75 138.77 131.36 131.92 124.44
(106USD)
Test 17 18 19 20 21 22 23 24
Revenue 131.75 142.23 150.82 158.99 136.03 131.76 151.36 144.83
(106USD)
Test 25 26 27 28 29 30 31 32
Revenue 142.92 140.24 131.12 129.37 142.01 136.39 127.94 123.36
(106USD)
Figure 5-7 Revenue value distribution of the 32 tests of cyclic gas flooding
92
CO2 flooding is also investigated in this study. The factors considered in the NPV model are more
complex than those in natural gas injection. The cost of injected CO2 is related to oil price.
According to Cook (2012), the cost of injected CO2 is divided into two parts: a delivery charge of
$0.50/Mcf and 2% of the oil price. Table 5-4 and Figure 5-8 reveal that the optimized revenue of
Test 1 is 149.27 million dollars, followed by Test 6 with 147.64 million dollars. Test 32, with a
revenue of 127.37 million dollars is the worst one; approximately 17% less than Test 1.
The parameters in Test 1 involve four primary production years, one injection well, a primary
bottom hole pressure of 6 MPa, an injection pressure of 35 MPa and late stage production BHP of
3 MPa. The factors in Test 6 are comparable. An early injection time and low production BHP are
beneficial to increase oil and gas productivity
The difference with cyclic gas flooding is that one injection well behaves better revenue potential
in the CO2 flooding. Different with taking situ produced natural gas as injected gas source in cyclic
gas flooding, the gas source of CO2 flooding is a significant cost factor influencing the final
economic evaluation. Although more injection wells are beneficial for improving reservoir
pressure, the cost of injected CO2 will double. Thus, Test 1 and 6, with one injection well, display
greater economic advantage.
93
Table 5-4 Calculated Revenue of CO2 flooding
Test 1 2 3 4 5 6 7 8
Revenue 149.27 143.72 139.5 135.61 143.47 147.64 133.15 136.49
(106USD)
Test 9 10 11 12 13 14 15 16
Revenue 141.44 134.56 140.12 133.13 142.14 138.34 133.94 129.57
(106USD)
Test 17 18 19 20 21 22 23 24
Revenue 144.34 143.88 142.94 140.16 142.49 142.87 138.96 137.89
(106USD)
Test 25 26 27 28 29 30 31 32
Revenue 141.46 136.91 137.11 131.99 141.48 138.23 133.22 127.37
(106USD)
Figure 5-8 Revenue value distribution of the 32 tests of CO2 flooding
94
5.4 Conclusion
In this study, the optimization of cyclic gas flooding and CO2 flooding considering the main
operational parameters are investigated. Due to the series of parameters that need to be
investigated, the orthogonal experimental design is adopted to reduce the simulation runs, time
and costs. The NPV model is used as the evaluation criterion of the 32 combinations created by
the orthogonal experimental design. We can conclude that:
(1) The optimal combination of cyclic gas flooding is with two injection wells, a short primary
production time (starts injection early), a high well bottom hole pressure during primary
production, a short injection time, a high injection pressure and a low late period well bottom hole
pressure.
(2) More injection wells help to improve the cyclic gas swipe efficiency, greatly enhancing the
reservoir pressure and preventing liquid condensate from the gas phase. A short production time
and high bottom hole pressure during the primary period help to prohibit the rapid drop of reservoir
pressure. High injection pressure, combined with a short injection time, bring about quick gas
injection and guarantee the injection efficiency.
(3) The optimal combination of CO2 flooding resembles cyclic gas in some respects, specifically
with the early injection time and low production pressure in the late period. One injection well and
a low injection pressure, however, are more economical for CO2 flooding due to the high cost of
95
CO2 gas sources and transportation charges. The NPV analysis for CO2 flooding is much more
complicated than cyclic gas flooding.
(4) Compared with CO2 flooding, cyclic gas displays a better NPV assessment, requires lower
operation charges and involves a simplified process.
96
Chapter Six: Conclusions and Future work
6.1 Conclusions
The major conclusions and findings of this thesis are summarized.
(1) Production performances of the cycling gas injection, CO2 flooding and water injection are
investigated in this study. Results show that cumulative oil productions of cyclic gas flooding and
CO2 flooding are 52.7% and 40.0% higher, respectively, than that of the base case (no injection).
As for NPV, cyclic gas flooding offers a better economical assessment than CO2 flooding due to
the low cost of cyclic gas resource, no transportation fee and no separation charge.
(2) Water flooding leads to a slightly higher oil production, which is 11.7 % higher than that of the
no injection case, but its gas production is reduced by 15.4%. Water flooding is the worst option
to enhance the production or improve field pressure due to the poor injection ability in the studied
tight liquid rich gas reservoirs.
(3) The PVT models’ study shows that cyclic gas and CO2 flooding will change the critical
temperature and pressure and, thus, increase the gas phase area, resulting in more gas production
and less oil condensation.
(4) A sensitivity study shows that production behaviors are very sensitive to well bottom hole
pressure during primary production, fracture conductivity and primary production time. In the
97
short term, a lower bottom hole pressure and a higher hydraulic fracture conductivity are beneficial
for production; over the long term, the rapid pressure drop below the dew point pressure leads to
liquid condensation. Five years of primary production time performs the best, as compared to the
other scenarios. Non-Darcy flow behavior exists with a high gas rate and affects the gas flow rate
to a considerable extent. The non-Darcy flow has no obvious difference on oil production. The
fracture height study shows that a 40 meters’ fracture height leads to a higher oil production.
(5) The experimental study of the optimization of gas injection indicates that the optimal
combination of the parameters in cyclic gas flooding is with two injection wells, a short primary
production time (early injection time), a high primary bottom hole pressure, a short injection time,
a higher injection pressure and a low well bottom hole pressure during late period. More injection
wells will improve the cyclic gas swipe efficiency and enhance the reservoir pressure. A short
production time and high bottom hole pressure during the primary period minimize the rapid drop
of reservoir pressure. A high injection pressure, combined with a short injection time, brings about
quick gas injection and guarantees the injection efficiency.
(6) The CO2 flooding optimization results resemble cyclic gas flooding in some respects, such as
early injection time and low production pressure in the late period. Considering the high cost of
the CO2 gas source and transportation charge, one injection well and low injection pressure are
more economical for CO2 flooding.
98
6.2 Future work
(1) More enhancing hydrocarbon recovery methods can be tried in tight liquid rich gas resources,
such as an alternative injection of cyclic gas and water flooding, a mixture injection of lean gas
and nitrogen, and so on.
(2) The sensitivity study can be verified by CMOST, which can test the interactive influence
among different parameters, resulting in a more accurate estimation.
(3) In the experimental design, more parameters and variation levels can be considered for a more
comprehensive factor analysis of the optimization study.
99
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