Kyushu University Global COE Program
Journal of Novel Carbon Resource Sciences, Vol. 2, pp. 1-7, Sep. 2010

Numerical Simulation of CO2 Enhanced Coal Bed Methane Recovery
for a Vietnamese Coal Seam
Phung Quoc Huy*1#, Kyuro Sasaki*2, Yuichi Sugai*2,
Maneeintr Kreangkrai*2 and Tayfun Babadagli*3*1

Graduate School of Engineering, Kyushu University*2
Faculty of Engineering, Kyushu University*3
School of Mining and Petroleum Engineering, University of Alberta, Canada#
Present address: Institute Mining Science and Technology, Vietnam(Received May 6, 2010; accepted September 6, 2010)
A CO2-ECBMR numerical modeling has been build for the Mao Khe coal seam in Vietnam. The numericalsimulations for sensitivity studies on the dominant factors for CH4 production, such as permeability, CO2 injection
rate and well spacing have been carried out by giving CO2 and CH4 adsorption capacities and viscocities of CO2
and water as a function of the coal seam temperature (40 to 65 °C). Finally, the numerical simulations with fivespot model have been presented to evaluate CO2 injectivity and CH4 productivity by changing the well spacing. The
results show that CO2 injection is roughly proportional to number of injectors, however the time of the maximum
CH4 production rate is delayed with 5-spots unit area. From view of economical evaluation, drilling cost of wells andwell spacing are important parameters to decide the optimum production scheme.

1. Introduction

Greenhouse gases (GHGs), such as carbon dioxide(CO2) and methane (CH4), are increasing due to human(anthropogenic) activities. Among these GHGs, CO2
is the most emitted greenhouse gas. CO2 is emitted
principally from the burning of fossil fuels, both in large
combustion units such as those used for electric power
generation and in smaller, distributed sources such as
automobile engines and furnaces used in residential andcommercial buildings. CO2 emissions also resulted fromsome industrial and resource extraction processes, aswell as from the burning of forests during land clearance.
Currently, CO2 accounts for about 72% of theanthropogenic greenhouse effect and is the mostimportant GHG contributor (IPCC, 2005) 1). Because of
the large contribution of CO2 to climate change, large
reduction in CO2 emissions will be necessary to stabilize
the atmospheric CO2 concentration.
The Kyoto Protocol (1997) calls for industrialized
nations to reduce their CO2 emissions to 95% of 1990
levels by 2012. In this regard, many national andinternational programs have been initiated towards
understanding the magnitude and mitigation optionsof the greenhouse gases. The CO2 concentration in theatmosphere could be controlled either by reducing its
production releasing into the atmosphere, or by capturing
and disposing of the produced CO2 in a safe manner(storage or sequestration).
Various CO2 storage options have been proposed,
including placement in the deep oceans; placement ingeologic formations (deep saline aquifers, abandoned
oil or gas reservoirs, and unmineable coal seams) andconsumption via advanced chemical and biologicalprocesses. These options are under investigation and on
the pilot projects to determine their feasibility in termsof their storage capacity, safety, and costs. CO2 storage

in deep unmineable coal seams is one of the geologic
strategies. Coal seam storage of CO2 is particularly
attractive in those cases where the CO2 could be stored
in the coal seam in an adsorbed state that is expected to
be stable for geologically significant periods. Injectionof CO2 may also enhance the production of the coalbed
methane recovery (CBMR) to generate a profit to help
offset the expense of the CO2 enhanced coalbed methane
recovery (CO2-ECBMR). If so, long-term storage of CO2
in coal seams might be more cost-effective method to
reduce CO2 emission. Additionally, many power plants
are located near coal seams, which would reduce thetransportation costs.
In this study, a CO2-ECBMR numerical modelinghas been done for the Mao Khe coal seam in Vietnam.
The numerical simulations for sensitivity studies on thedominant factors for coalbed methane gas production,such as permeability, CO2 injection rate and well spacing
have been carried out by giving CO2 and CH4 gas
adsorption capacities and viscocities of gases and water
as a function of the coal seam temperature (40 to 65 °C).

2. Numerical Simulation Modeling
2.1 CO2-ECBMR

CO2 adsorbs more strongly to coal than CH4 so as
CO2 is injected into a coal reservoir, it is preferentiallyadsorbed into the coal matrix, displacing CH4. The
displaced CH4 then diffuses into the cleat system andmigrates to the production wells by Darcy’s flow. This
process is relatively efficient in theory and, as implied
from the isotherms, should require 2 - 3 volumes of
injected CO2 per volume of incrementally produced CH4(see Huy et al., 2009) 2).
In general, commercial projects and researches on coal
bed methane (CBM) simulators were developed to modelprimary recovery processes, taking into account impor-Journal of Novel Carbon Resource Sciences, Vol.2, Sep. 2010

tant features to properly evaluate the performance of
coalbed reservoirs. To correctly model complex reservoir
mechanisms in ECBMR processes using CO2, CBM simulators are being improved to include additional features.
Important features in modeling primary and enhanced
coalbed methane recovery processes are as follows: a)dual porosity, dual permeability; b) multiple gas components; c) multiphase flow (gas and water) in the natural
fracture system (Darcy’s flow); d) pure and mixed gas
diffusions between the coal matrix and the natural fracture system (different diffusion rates); e) pure and mixed
gas adsorption/desorption at the coal surface (extended
Langmuir isotherm relationship); f) coal matrix shrinkage/swelling due to gas desorption/ adsorption 2,6); g)
compaction/dilation of the natural fracture system due tostresses-dependent permeability and porosity models6-9) ;h) non-isothermal adsorption of the injected gas10).
The capability to handle multiple gas components isan essential feature in modeling ECBMR processes
with flue gases (Thomas et al., 2008)3). Recent advancesin numerical simulations of CBM/ECBMR processes
have focused on multi-component gas transport in
the in-situ bulk coal and changes in coal properties
during methane production. Considering the features
required for modeling ECBMR processes, the ECLIPSE
compositional simulator with a CBM module, developedby Schlumberger, was selected to conduct the simulation
studies. ECLIPSETM is a three-dimensional, finitedifference, multiphase, dual-porosity, compositional
simulator. The model for simulating rock compactionis also available in ECLIPSE (Palmer and Mansoori,1998) 4). The simulator is capable of modeling coalbed
methane reservoir performances under primary and/or
enhanced recovery schemes.
Pressure reduction frees methane molecules from thecoal and allows gas migration. To produce gas from coal,
the adsorbed gas must first be desorbed from the coaland this is accomplished by depressurizing the coal tothe critical desorption pressure. This depressurization isaccomplished through the production of formation water,which exists in the natural fracture system. As the wateris withdrawn and formation pressure declines, the gas
volumes produced tend to build from a low initial rate
to a maximum rate after several years. This is indirectcontrast to conventional reservoirs, where the highest
production rates are at the beginning of production anddecline over the years (see Figure 1). Thus, when theinitial reservoir pressure is above the critical desorption
pressure, the reservoir is called an under-saturated
reservoir. As the gas saturation increases in the fracture,gas flows from the matrix to the fracture and krg increases
until the critical saturation is reached, when the reservoir
starts producing gas with water.

2.2 Coal reservoir model and grids system

A reservoir simulation model that is one-fourth of afive-spots pattern (see Figure 2) was built using the
ECLIPSE compositional reservoir simulator developedby Schlumberger. A grid sensitivity study used a singlelayer grid model from 22×22×30 to 72×72×30 grid cells
in a 5-spots pattern with the dimensions of the coalreservoir from 110×110×8.4 m to 360 × 360×8.4 m (seeTable 1).

z

LW

Lz

CH4 Production Rate, std-m3/day

StableProductionStage

Decline Stage

CH4 Production
Water
Production
Time

Fig. 1 Production regime in a coal seam reservoir.

I: injector
Ly

Coal Seam
P: producer

Lx

Fig. 2
Table 1Well
distance
LW (m)
78

Dewatering
Stage

y
x

Diagram of the five spots model.

Numerical parameters for five-spot model
Dimensionof well span
(LX×LY×Lz)(m)
110×110×8.4

106

150×150×8.4

156

220×220×8.4

Area of
1/4 of5-spot(m2)
3025

22×22×30=14520

5625

30×30×30=27000

Total number ofgrid blocks(=nX×nY×nZ)

12100

44×44×30=58080
58×58×30=100920
72×72×30=155520

205

290×290×8.4

21025

255

360×360×8.4

32400

2.3 Adsorption isotherms and diffusion

In this paper, a coal seam at Maokhe coal mine wasselected for this study. As the important parameterof coal, CH4 and CO2 adsorption of the coal havebeen measured and the results are shown in Figure 3.

Numerical Simulation of CO2 Enhanced Coal Bed Methane Recovery for a Vietnamese Coal Seam

Langmuir constants of samples MK-9D have been
selected as input parameters for modeling. The Langmuir
constants for CH4 and CO2 are shown in Table 2.

Volume Adsorbed,

std-cm3/g

15.0
12.5

CO2 Langmuir curve

10.0

Fi = Dc ,i .S g .RFi (mi − ρ c Li )

7.5
5.0

CH4 Langmuir curve

0

0.5

1.0 1.5
2.0
2.5
3.0
Equilibrium Pressure, MPa

3.5

4.0

Fig. 3 CO2 and CH4 Langmuir curves for Mao Khecoal samples2,5,7,8).
Table 2

Input parameters for numerical simulations

Parameters for numerical simulation
Coal Matrix Porosity
x- direction Permeability, kx

Units
mD

Value
0.01
1.0

mD

1.0

mD

0.1

MPa

5.5

y- direction Permeability, ky
z- direction Permeability, kz
Initial Pressure of Coal, Pint
Temperature of Coal Seam, T
Coal Thickness, m

CH4 Desorption time, τ,

CH4 Langmuir Pressure, PL
CO2 Langmuir Pressure, PL
CO2 Injection Pressure (BHP)
Production Pressure (BHP)

45
8.4
524
0.05

-

0.95

day

20

day

10

m3/t

7.35

MPa

0.76

m3/t

15.58

MPa

1.24

CO2 Desorption time, τ;

CO2 Langmuir Volume, VLCm-Initial CH4 Saturation
Initial Water SaturationomDepth of Reservoir, D

CH4 Langmuir Volume, VL

MPa

8

MPa

0.14

nc δ jThe success of a CO2-ECBMR process is dependent
on a number of operating parameters such as injection
pressures and producer-injector spacing. Other factors
dominating the process are determined by the actual
static and dynamic qualities of the reservoir. To reducerisk in a new CO2-ECBMR project, a sensitivity analysis
should be carried out to obtain the optimized wellspacing, CO2 injection rate and the end point of CH4
production. This study analyzes the sensitivity in fourparameters as next sentences.

2.4.2 Sensitivity of injection-production well spacing
Assuming a constant injection pressure Pinj = 8 MPa,different wells spacing were investigated LW = 78, 106,
156, 205 and 255 m.
2.4.3 Sensitivity of permeability
Assuming a fixed well spacing LW = 106 m and aconstant CO2 injection pressure Pinj = 8 MPa, different
permeabilities were investigated k = 0.5, 1 and 2 mD.

In this model, the extended Langmuir isotherm wasapplied as follows:

pδ i
p Li

2.4 Sensitivity analysis for CO2-ECBMR

2.4.1 Sensitivity of CO2 injection
Comparison of the base case model (no CO2 injectiongas) and the CO2 injection model with a wells spacingof LW = 106 m and an injection pressure of Pinj = 8 MPa.

* BHP= Bottom Hole Pressure, mD = 10 −15m2 (SI unit)

G si = G sLi [1 − (wa + wwe )](2)

where mi = molar density in the matrix coal; ρc = rockdensity (coal density) (kg/m3); Dc,i = diffusion coefficient(coal) component i; RFi = read sorption factor componenti; Sg = gas saturation

2.5
0storage capacity of component i (m3/t); wa = ash content(%); wwe = equilibrium moisture content (%); pLi or pLj =single component Langmuir pressure of component i orj (MPa); δi or δj = mole fraction of component i or j in
the free gas phase (%); nc = number of components; p =pressure of free gas phase (MPa).
The diffusive flow between the matrix and the fracture
is given by(1)

1+ p ∑

j =1 p Lj

where Gsi = multi-components storage capacity ofcomponent i (m3/t); GsLi = single component Langmuir

2.4.4 Sensitivity of coal seam temperature
Assuming a fixed well spacing LW = 106 m and constantCO2 injection rate Pinj = 8 MPa and permeability kx = ky
= 1 mD, different temperatures were investigated T =40, 50 and 65 °C.

3. Simulation Results And Discussion
3.1 Saturation of gases

CO2 and CH4 saturation in the Mao Khe model are
shown in Figures 4 and 5, for operating times of 3, 6,
9 and 12 months. The well spacing in this case was 156
m and the permeability was kx = ky = 1 mD. The results
show that CH4 and CO2 saturation were slow because of
their low permeabilities. At a time of 12 months after thewells were opened, the CO2 and CH4 saturation levels
were about 40% of total saturation.

Journal of Novel Carbon Resource Sciences, Vol.2, Sep. 2010

1.0
IW

IW
0.8

PW

0.4
IW

IW

0.2

PW

PW
t = 09 months

Fig. 40.0
t = 12 months

CO2 saturation at different operating times.
1.0
IW

IW
0.8

PW

PW
t = 03 months

Mao Khe model

0.6
t = 06 months
0.4
IW

IW

0.2

PW

PW
t = 09 months

Fig. 50.0
t = 12 months

CH4 saturation at different operating times.

3.2 Gas injection sensitivity analysis

Comparison of the base case model (no gas injection)and the CO2 injection model were carried out. The
operating parameters in this sensitivity analysis areshown in Table 3.

Table 3Operating parameters for sensitivity analysis

Operating Parameters
CO2 Injection (BHP)
Producer-Injector spacing, LW
Production Pressure (BHP)
Reservoir Initial Pressure, Pint
x-direction Permeability, kx
y-direction Permeability, kyz-direction Permeability, kz
Temperature of Coal Seam, T

Units
MPa
m
MPa
MPa
mD
mD
mD
°C

Value
Shut-in / 8 MPa
106
0.14
5.5
1.0
1.0
0.1
45

4.5

20

CH4 Cum. prod.

16

3.0
CH4 Cum. Prod.
1.5
CO2-ECBMR
CBMR
0Fig. 624

CH4 Prod. rate

0

0.5

Time,

1.0
years

CH4 Prod. Rate1284

Water Prod. rate
1.5

0

6

Mao Khe model

Cumulative CH4 Production 10 std-m3

t = 03 months

0.6
t = 06 months

CH4 and Water Production Rates3, 10 std-m3/day

PW

Figure 6 shows the CH4 production rate by CO2
injection (CO2-ECBMR) and without CO2 injection(CBM). The CO2-ECBMR results show that CO2
injection enhanced the maximum CH4 production rate by
195%, from 2069 to 4052 sdt-m3/day. Cumulative CH4
production also increased 168% from 1.2×105 to 2.0×105
std-m3 with CO2 injection. The CH4 production rate
reached the maximum at around 6 months after start ofoperation and then declined gradually. It was applied tonumerical simulations as an operation strategy that CH4
production well is shut down when the CO2 concentrationin the producer exceeds 20%, since it would be costly
to separate CO2 from CH4. In the operation, water inthe coal seam is produced initially, and then CH4 isproduced. Water production in CO2-ECBMR is around
one month faster than that of CBMR. The production
rate increased sharply after the first month and reacheda maximum production rate at around the 6th month.
Without CO2 injection, water production resulted fromthe natural water pressure in the coal reservoir (5.5 MPa).
Thus, water remained in the coal seam, leading to a lower
CH4 production rate. Furthermore, CO2 molecules could
displace CH4 molecules and enhance CH4 recovery.
In summary, the CO2-CBMR processes gives the dual
benefits of enhancing CH4 production and storage of CO2.
Enhancing the CH4 production increases revenues fromselling the gas and improves the gas recovery factor fromthe coal reservoir. CO2 stored in the coal seams may also
generate revenue from environmental funds.

Comparisons of CH4 production by ECBMR and
CBMR (with and without CO2 injection).

3.3 Injection – production wells spacing sensitivity
analysis on economic evaluation

CO2 Capture and Storage (CCS) technology has been
approved as a method for clean development mechanism(CDM) projects. Therefore, economic evaluation including
CO2 credits is important. Sensitivity study of injectionproduction well spacing on the injection and production
rates is an effective approach to decide the optimized
well-spacing and shut-in time of CH4 producer. Thesesimulations are used be helpful to reduce operation costand economic risks included in CO2-ECBMR projects.
In this study, the sensitivity analysis of injectionproduction well spacing for the Mao Khe coal seam

Operating parameters for sensitivity analysis
on injector-producer well-spacing

Operating Parameters
CO2 Injection Pressure(Bottom Hole)

Units
MPa

Producer-Injector spacing, LW

m

Production Pressure (Bottom Hole)Reservoir Initial Pressure, Pint
x-direction Permeability, kx
y- direction Permeability, ky
z- direction Permeability, kz
Temperature of Coal Seam, T

MPa
MPa
mD
mD
mD
o
C

Value
8
78, 106,
156, 205,
255
0.14
5.5
1.0
1.0
0.1
45

Figure 7 shows the CO2 injection and CH4 production
rates using with different LW. The results show little
difference in the maximum CH4 production rates between
the cases. The CH4 production and for CO2 injection
rates were approximately 4000 and 10,000 std-m3/day,
respectively . The CH4 production rate of LW = 78m wasslightly higher than other LW and the shut-in time of the
producer was less than one year.
The cumulative injection/production of CH4 and CO2
for different well-spacings are shown in Figure 8. The
results show that cumulative CH4 production in the caseof LW = 255 m was the highest. The cumulative CH4
production was 1.25×106 sdt-m3 in 8.4 years after the wells
were opened. In the case of LW = 106 m, the cumulative
CH4 production was 2.7×105 sdt-m3 in 1.4 years. The resultof LW = 78 m had the smallest cumulative CH4 production
and the shortest production period and it was excluded
from present study.
Table 512.0
78 m

106 m 156 m

205 m

255 m

3

10.0
8.0

CO2 injection

6.0
4.0

CH4 production

2.0
0.0

0

Fig. 72

4

6Time, years

8

10

12

CO2 injection and CH4 production for different
well-spacings.

4.0
LW = 78 m
L W = 156 m
L W = 255 m

6

Table 4

Cumulative Inject../ Product., 10 std-m3

model was carried out by simulating the CO2 injection
process into the coal seam model with five different
injector-producer well-spacings; LW = 78, 106, 156,
205 and 255 m. The operating parameters used in thisanalysis are shown in Table 4.

Injection/Production rates, 10 std-m3/day

Numerical Simulation of CO2 Enhanced Coal Bed Methane Recovery for a Vietnamese Coal Seam

3.0

2.0

CO2 injection

1.0

0.0

CH4 production
0

2

4

6
Time, years

8

10

12

Fig. 8 Cumulative CO2 injection and CH4 production
for different well-spacings.
To optimize the well-spacing in present CO2-ECBMR
model, the economic evaluation has been carried out.
The parameters for optimizing well spacing are shownin Table 5. Total profit per unit area was calculated by thefollowing equation:

Parameters for optimization of well spacing
LW = 78 m

LW = 106 m

Well spacing
LW = 156 m

LW = 205 m

LW = 255 m

Drilling cost (D), US$
Production duration (t), year
Maintenance cost per year (m), US$
Maintenance cost (M), US$
Production areas (A), m2

200,000
0.70
20,00014,000200,000
1.40
20,00028,000200,000
3.20
20,00064,000200,000
5.80
20,000116,000

200,000
8.40
20,000168,000

3,025

5,625

12,10021,02532,400

Cum. CH4 production (PCH4), std-m3

250,000

275,000

490,000

850,000

1,250,000

Cum. CO2 injection (PCO2), std-m3

650,000

800,000

1,950,000

3,200,000

4,000,000

Income from CH4 (ICH4), US$

110,000

121,000

215,600

374,000

550,000

Income from CO2 (ICO2), US$

32,50040,00097,500160,000

200,000

Recovery factor for duration, Rf
Benefit (B), US$
Present value/ Unit Area (B/A), US$/m2

0.90-85,750-28.3

0.90-83,100-14.8

0.77-22,913-1.9

0.75
84,5004.0

0.63
104,500
3.2

Economic Parameters

Journal of Novel Carbon Resource Sciences, Vol.2, Sep. 2010

B ( I CH 4 + I CO 2 ) R f − ( D + M )
=
2
A
2 LW

(3)

Present value of Project ; B/A, US$/m2

where B = total benefit (US$); ICH4 = income from CH4(US$); ICO2 = income from CO2 (US$); Rf = capital
recovery factor; D = drilling cost (US$); M = maintenancecost (US$); A = unit area of 5-spot (m2).
In this study, the CH4 gas price was evaluated as
US$0.4 /m3 and CO2 was US$0.05/m3. The results of theeconomic analysis showed that the Mao Khe model had
maximum benefit (B = US$104,500) at well spacing of
255m. Because of the high drilling cost, the well-spacing
LW ≤ 205m was not economically feasible. However, thebenefit per unit area of coal reservoir was highest (B/A =US$4.0/m2) at LW = 205m. This means that LW = 205 m
can be considered as the best selection based on present
sensitivity analysis (Figure 9).
10

156m

106m

-20
L W = 78m

0

50

100
150
Well Spacing,

200m

The operating parameters used in this analysis areshown in Table 6. CO2 injection and CH4 production
rates for kx = ky = 0.5, 1 and 2 mD have been shown in
Figure 11. The results show that both rates increased withreservoir kx =ky, but CH4 production period decreased.
In the case when permeability kx = ky = 2 mD was given,
the CO2 injection rate was approximately 1.7×104 std-m3/
day. And it was almost twice to the case of 1mD and about
4 times larger than that of 0.5 mD (i.e. CO2 injection rateis roughly proportional to permeability).
6

255m

-10

-30

3.4 Permeability sensitivity analysis

Table

205m

0

The sensitivity analysis of well-spacing between
injection and production wells was an useful approachfor deciding the optimized well-spacing and the time toshut down CH4 production and injection of CO2. This
reduces the cost of operation and risks in CO2-ECBMR
projects.

250

300

Operating parameters
sensitivity analysis

Operating Parameters
CO2 Injection Pressure (BHP)
Producer-Injector spacing, LW
Production Pressure (BHP)
Reservoir Initial Pressure, Pint
x-direction Permeability, kx
y-direction Permeability, kyz-direction Permeability, kz
Temperature of Coal Seam, T

for

Units
MPa
m
MPa
MPa
mD
mD
mD
ºC

permeability
Value
8
106
0.14
5.5
0.5, 1.0, 2.00.5, 1.0, 2.0
0.05, 0.1, 0.2
45

200

12
CO2, k = 2 mD

0.

0.1
0.2
0.3
Drilling Cost, US Million$/Well

0.4

Fig. 10 Drilling cost for various well-spacings.
Using a similar analysis to this study, the sensitivity
for other well-spacings can be carried out so that an
optimized well spacing can be obtained for the actual
conditions of CO2-ECBMR projects.

10
8

12
CH4, k = 2 mD

9
6

CH4, k = 1 mD

3
0

6

CO2, k = 1 mD

4

CO2, k = 0.5 mD

2

CH4, k =0.5 mD
0

1

2
3
Time, years

4

5

0

3

15

Fig. 11

100

0

18

CH4 Production Rate, 10 std-m3/day

Optimized Well Spacing, m

300

3

Figure 10 showed the relationship between optimized
well spacing and drilling cost. The result showed that
optimized well spacing increase when increasing ofdrilling cost.

CO2 Injection Rate, 10 std-m3/day

Fig. 9 Present value of B / A for various well-spacings.

Injection and production rate of gases for different permeabilities.

3.5 Temperature sensitivity analysis

Injection rate against some coal seam temperatures
were investigated (Figure 12). The numerical parameters
for this sensitivity analysis are shown in Table 7. The
results show that a higher temperature gave a smaller
injection rate. The gas adsorption capacity of coaldepends on temperature (Huy, et al., 2009)6) (Sasaki, etal., 2009)7). The adsorption volume was reduced withincreasing temperature. Therefore, injection rate also be
reduced with increasing temperature.

1.

12

3

10
8

CO2 Injection rate,

10 std-m3/day

Numerical Simulation of CO2 Enhanced Coal Bed Methane Recovery for a Vietnamese Coal Seam

6

40 oC
50 oC
65 oC
Temperature of Coal Seam

2.

and CO2 injection

3.

4
2
0

0

Fig. 12

0.5

1.0
1.5
Time, years

2.0

2.5

CO2 injection rate against different coal seam
and CO2 temperatures.

Table 7 Operating parameters for temperature sensitivity study.
Operating Parameters
CO2 Injection Pressure (BHP)
Producer-Injector Spacing, LW
Production Pressure (BHP)
Reservoir Initial Pressure, Pint
x-direction Permeability, kx
y- direction Permeability, ky
z- direction Permeability, kz
Temperature of Coal Seam, T

4. Conclusions

Units
MPa
m
MPa
MPa
mD
mD
mD
o
C

Value
8
106
0.14
5.5
1.0
1.0
0.1
40 50 65

Coal bed methane production by CO2 injection into
coal seams (CO2-ECBMR) is expected as a cost-effective
CO2 sequestration method, since financial benefit fromgas production can offset some of investment for CO2
capture process. In this study, the sensitivity analysis
with the numerical simulation results was carried out toinvestigate the dominant model factors of CO2-ECBMR
for the Mao Khe coal seam in Vietnam.
The following conclusions are summarized.

Numerical simulation results using five-spot modelat the Mao Khe coal seam have shown that the CH4
production by CO2 injection is increased by 195%
compared with usual CBM.
A sensitivity analysis of CO2 injection pressure gives
a useful information to decide the CH4 production
period and to carry out economic evaluations.
In the Mao Khe model built in this study, the wellspacing of 205 m was found to be optimal because
the CH4 production rate was maximized, giving thehighest present value. Additionally, CO2 was stored
at the maximum injection rate.

Acknowledgements: This study was carried out as apart of a project entitled “Technology Development for
Carbon Dioxide Sequestration in Coal Seams”, NEDO
project on“Innovative Zero-emission Coal Gasification
Power” and G-COE “Novel Carbon Science”, Kyushu
University.
References
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2) P. Q. Huy, K. Sasaki, Y. Sugai, T. Kiga, M. Fujioka, T.
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