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Running title: The prediction model of coal reservoir pressure
and its implication
The prediction model of coal reservoir pressure and its
implication for the law of coal
reservoir depressurization
Xinlu YAN 1,2,3
, Songhang ZHANG 1,2,3,*
, Shuheng TANG 1,2,3
,Zhongcheng LI4, Kaifeng WANG 1,2,3, Yongxiang YI 1,2,3 ,
Feng
DANG 1,2,3
and Qiuping HU4
1. School of Energy and Resources, China University of
Geoscience, Beijing, 100083, China
2. MOE Key Lab of Marine Reservoir Evolution and Hydrocarbon
Accumulation Mechanism, China University of Geoscience, Beijing,
100083,
China
3. Beijing Key Laboratory of Unconventional Natural Gas
Geological Evaluation and Development Engineering, Beijing, 100083,
China
4. China United Coalbed Methane Corporation Ltd, Beijing,
100011, China Abstract:The main methods of coalbed methane (CBM)
development are drainage and depressurization. Therefore, precise
prediction of coal reservoir pressure is crucial for the evaluation
of the reservoir potentials and the formulation of reasonable
development plans.
In this paper, a new reservoir pressure prediction model was
established basing on the material balance equation (MBE) of coal
reservoir; the model
considers coal reservoir self-regulating effects and dynamic
change of equivalent drainage area (EDA). According to the proposed
model, the
reservoir pressure can be predicted based on the reservoir
condition data and on the actual production data of a single well.
Compared with the
traditional reservoir pressure prediction models, where EDA is
considered as a fixed value, the proposed model shows a more
reasonable prediction
of the reservoir average pressure. Moreover, in the proposed
model, orthogonal experiments were designed to evaluate the
sensitivity of the reservoir
parameters on the reservoir pressure prediction results. The
results showed that the irreducible water saturation is the most
sensitive parameter, which
is followed by the Langmuir volume and the reservoir porosity;
the Langmuir pressure is the least sensitive parameter. In
addition, we found that the
reservoir pressure drop is negatively correlated with the
irreducible water saturation and the Langmuir volume, while it is
positively correlated with
the porosity. By analyzing the reservoir pressure drop
characteristics of the CBM wells in the Shizhuangnan Block, in the
Qinshui Basin, the results
showed that the CBM reservoir depressurization can be divided
into three types, which are the "rapidly drop type", the
"medium-term stability type",
and the "slowly drop type". The drainage features of wells were
reasonably interpreted based on the comprehensive analysis of the
reservoir
depressurization type; the latter was coupled to the
corresponding permeability dynamic change characteristics,
eventually proving the applicability
of the proposed model.
Keywords: coalbed methane, pressure prediction, equivalent
drainage area, influencing factors, pressure drop types
E-mail:[email protected]
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This article has been accepted for publication and undergone
full peer review but has not been
through the copyediting, typesetting, pagination and
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differences between this version and the Version of Record.
Please cite this article as doi:
10.1111/1755-6724.13869.
https://doi.org/10.1111/1755-6724.13869https://doi.org/10.1111/1755-6724.13869https://doi.org/10.1111/1755-6724.13869
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Nomenclature
the equivalent drainage area final reservoir pressure
gas volume coefficient at initial pressure reservoir pressure
variation
gas volume factor the standard pressure
water formation volume coefficien coal density formation water
compressibility coefficient reservoir pressure drop rate
buried depth of coal seam the initial water saturation of the
original fissure Young modulus the irreducible water saturation
the maximum volumetric strain reservoir temperature the surface
volume of cumulative gas production the standard temperature
coal seam thickness the Langmuir volume bulk modulus actual gas
content
permeability poisson’s ratio axial modulus of elasticity the
surface volume of cumulative water production
reservoir pressure the standard deviation factor of gas the
critical reservoir pressure the initial porosity
the initial reservoir pressure porosity
the Langmuir pressure
1 Introduction
The energy demand is increasing worldwide (Chu and Majumdar,
2012). As an unconventional new energy source, coalbed
methane (CBM) increasingly plays an important role in fossil
energy (Kuuskraa, 1989; Clarkson and Salmachi, 2017). The Qinshui
Basin, as the CBM test area in China, has been commercially
developed (Su et al., 2005; Jian et al., 2012). The coal reservoir
in the Qinshui Basin is an undersaturated coal seam (Su et al,
2004), and the production process can be divided into three stages;
the stages are: saturated single-phase water flow, unsaturated
single-phase water flow, and gas/water two-phase flow (Tang et al.,
2015). The main development methods of CBM in the Shizhuangnan
Block are drainage and depressurization (Cervik, 1969; Salmachi and
Yarmohammadtooski, 2015). As unsaturated CBM reservoirs do not
produce commercial quantity gas until the reservoir pressure drops
below the critical desorption pressure, the production wells must
experience a long water drainage and an unstable gas production
stage (Carlson, 2006). Therefore, the full depressurization of the
coal reservoir is the key to CBM production during the development
process.
At present, there are two main methods to calculate the
reservoir pressure. In the first method, the pressure propagation
law is calculated through the seepage equation (Zhao and Zhang,
2012; Liu et al., 2012; Zhang et al., 2017; Sun et al., 2017; Sun
et al., 2018). Using the seepage equations to calculate the
reservoir pressure aims to establish a mathematical model for coal
seam pressure distribution on one hand, and to combine the
reservoir permeability data and the water production date during
the production process on the other. The advantage of this method
is that the dynamic change of the drainage range is considered;
furthermore, the change of the reservoir pressure is calculated in
different regions during the production process. However, the
strong heterogeneity of the coal reservoir, the large inaccuracy in
the permeability parameters, and the underutilization of gas
production date cause inaccuracy in the pressure calculation. In
the second method, the average pressure of coal reservoir is
obtained by using the coal reservoir material balance equation
(MBE) combined with the basic parameters of the reservoir and the
actual production data. King (1993)
first
established the MBE for CBM, which was later improved by
subsequent studies. Penuela et al. (1998) developed a generalized
MBE for CBM reservoirs in which the diffusion process of desorbed
gas into cleat system was considered. Moreover, Ahmed et al. (2006)
proposed a generalized MBE that considered the initial free gas,
water expansion, Langmuir isotherm, and formation compaction to
estimate the original gas in place. Afterward, Hu and Li (2010)
classified the coal seam as a dual-medium of matrix and cracks;
they proposed an improved MBE that involves the self-regulating
effects of coal seams. Then, Zhao et al. (2014) established a new
MBE for undersaturated low rank CBM; on this basis, the dynamic
change of the relative permeability was calculated. Additionally,
Thararoop et al. (2015) developed a new MBE for CBM reservoirs that
considered the water presence in the coal matrix as well as coal
shrinkage and swelling. More recently, Shi et al. (2018) developed
the MBE that considers the effects of various factors, such as the
difference between the initial reservoir pressure and the critical
desorption pressure, pore compressibility, water compressibility,
coal matrix shrinkage, dissolved gas, and free gas. The MBE for CBM
is developed to predict the single well controlled area and the
original gas in place. The advantages of using the MBE method to
calculate the average reservoir pressure is to make full use of the
production data, and the requisite geological parameters of coal
reservoir are more accurate. Unfortunately, previous studies did
not consider the dynamic change of the drainage area when
calculating the average reservoir pressure. That is, the drainage
area is artificially set rather than setting the actual scope of
the development process; this means that the calculated reservoir
pressure might be untrue.
To solve the limitations of the CBM material balance equation, a
new reservoir pressure prediction model was established based on
the MBE of coal reservoir in this study. It is worth noting that
the proposed model takes into consideration the coal reservoir
self-regulating effects and dynamic change of the equivalent
drainage area (EDA). Fourteen wells from the Shizhuangnan Block in
the southern Qinshui Basin in China were employed for a case study.
The dynamic average reservoir pressure during the CBM production
was acquired by using production date based on the proposed
reservoir pressure calculation model. Taking the well T1 among
14
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wells as an example, the difference between the traditional
model and the proposed model was analyzed, and the influence of the
geological factors on reservoir pressure was further studied.
2 Regional Geology 2.1 Geological characteristics in the
Shizhuangnan Block
The Shizhuangnan Block is located in the southern region of the
Qinshui Basin, Shanxi Province. The entire field is made from
tectonic rocks that slope westward, and its structure is simple.
The Qinshui Basin is mainly filled with Permo–Carboniferous
sediments (Yao et al., 2008). The strata in the study area include
Cambrian, Ordovician, the Carboniferous Benxi (C2b) and Taiyuan
(C3t) Formations, the Permian Shanxi Formation (P1s), the
Xiashihezi Formation (P1x), the Shangshihezi Formation (P2s), the
Shiqianfeng Formation (P2sh), the Triassic Liujiagou Formation
(T1l), and Quaternary deposits. The C2b unconformably overlies on
the Ordovician Formation (Zhang et al., 2015). The main
coal-bearing strata are the upper Carboniferous Taiyuan Formation
(C3t) and the lower Permian Shanxi Formation (P1s), which contain
the coal seam No.15 and No.3, respectively (Yang et al., 2017). The
total thickness of the two coal seams is 10.7 meters. At present,
the mine-field mainly produces No.3 coal seams which mainly
consists of anthracite; its coal vitrinite reflectance (Romax)
ranges from 2.92% to 3.02%. The No.3 coal seam is stable and the
thickness ranges from 4.45 to 8.75 m, with an average of 6.35 m.
The shallowest and deepest depths of this coal seam are 451 and
1030 m, respectively (Zhu et al., 2017). It is generally deeper in
the northern and the central regions, while it is shallower in the
southern and the eastern regions. The gas contents of the coal
range between 13 and 20 m3/t. The gas contents in the west and in
the north are bigger than the contents in the east and in the south
(Yan et al., 2018).
Fig.1 Location of the sampling and study area. (a) Location of
the study area in China (China basemap after China National Bureau
of Surveying and Mapping Geographical Information); (b) The study
area, showing
CBMBlocks in the southern Qinshui basin; and (c) structure
outline of the study area and the wells where water samples were
collected. SZN, Shizhuangnan CBM Block; MB,
Mabi CBM Block; ZZ, Zhengzhuang CBM Block; FZ, Fanzhuang CBM
Block; PZ, Panzhuang CBM Block).
2.2 Basic parameters for the reservoir pressure calculation
Some production wells were selected as target wells in the
Shizhuangnan Block of the Qinshui Basin; the locations of these
wells are shown in figure 1. These wells are characterized by
continuous gas production; the initial artificial fracture of these
wells is effective from the hydraulic fracturing report, meaning
that there are no external causes to stop production. Peng et al.
(2017) established a prediction model for the CBM content by
matching isothermal adsorption experiments and log interpretation
in the Shizhuangnan Block. Consequently, the gas content of each
production well was calculated by the combination of the log
interpretation data of production wells and previous research
results. The specific parameters of each well are shown in Table 1.
The production time for all the production wells is more than 1500
days, while it is more than 2000 days for 9 of these production
wells (Table 2); this indicates that the production status of the
selected production wells is basically stable. According to the
average gas production rate, the production wells are classified as
high (>1000 m
3/d), medium (500-1000 m
3/d), and low (<500 m3/d) gas-yield
production wells. The 14 production wells can be divided into
three groups; 4, 5, and 5 have high, medium, and low gas-yield
production wells, respectively, with averages of 1680.5 m
3/d, 669 m
3/d, and 251.9 m
3/d, respectively. The daily water production rate
ranges between 0.52 and 2.27 m3/d. The cumulative water yield of
each well is low during the production process, which indicates
that
the CBM wells produce coal seam water and that there is no
influence of inrushing water (Li et al., 2018). Other basic
parameters can be obtained through well logging and well testing;
for a wellbore of 0.1m radius, the water
compressibility of MPa-1, the water formation volume factor of
1m3/m3, the dimensionless maximum Langmuir volumetric strain of
1.25%, the initial water saturation of 0.95, and the Young modulus
of 4300 MPa
-1can be obtained. Shen et al.
(2011) measured the irreducible water saturation of coal seams
to be approximately 0.6 by physical simulation experiments on coal
samples from the southern Qinshui Basin.
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Table 1 Basic parameters for the pressure prediction in the
Shizhuangnan Block
Wells D(m) H(m) /(g/cm3) (MPa) (MPa) VL(m3) PL(MPa) (m
3/t) K(mD) T(℃)
T1 776.10 5.00 1.23 3.30 1.87 29.86 2.10 16.13 0.76 0.03 25
0.3
T2 735.80 6.50 1.48 3.34 1.76 32.73 3.40 14.08 0.13 0.01 24.5
0.38
T3 714.00 6.50 1.38 4.20 2.20 26.14 1.62 15.04 0.10 0.05 24.6
0.39
T4 718.0 6.10 1.30 3.61 1.21 36.00 1.70 14.98 0.42 0.04 21.4
0.33
T5 729.40 5.70 1.23 3.68 2.14 34.81 2.19 17.20 0.08 0.03 24.5
0.3
T6 767.00 5.90 1.40 3.42 2.06 33.00 2.25 15.77 0.80 0.05 25.5
0.3
T7 533.60 6.00 1.30 3.10 1.32 36.84 1.70 16.12 0.44 0.04 24
0.32
T8 716.30 5.40 1.51 3.20 1.84 34.00 2.30 15.11 0.28 0.05 23.7
0.27
T9 769.10 6.05 1.39 3.34 2.03 26.42 3.07 10.52 0.11 0.03 25.5
0.28
T10 717.20 5.66 1.35 2.63 1.94 26.71 2.80 10.94 0.38 0.04 22.4
0.31
Z1 607.70 5.80 1.42 3.30 2.07 35.71 1.80 19.07 0.25 0.03 23.3
0.3
Z2 698.50 6.30 1.39 4.37 2.17 36.00 2.38 17.15 0.07 0.04 23.4
0.3
Z3 711.65 6.00 1.32 4.32 1.82 36.26 1.50 19.88 0.12 0.04 24.2
0.33
Z4 717.20 6.30 1.42 3.35 1.50 33.51 2.99 11.19 0.36 0.04 24.3
0.33
Table 2 Production parameters of CBM wells
Wells Time (day) Average daily gas
Production (m3)
Average daily water
production (m3)
T1 2308 545.29 1.54
T2 1553 717.52 1.34
T3 1503 306.86 2.11
T4 1821 553.17 1.21
T5 2044 1081.83 0.52
T6 2341 1064.49 2.27
T7 2285 566.11 0.80
T8 1960 423.97 1.53
T9 2340 198.90 2.02
T10 1531 160.88 1.79
Z1 2622 1279.08 0.93
Z2 2476 2493.09 1.45
Z3 2520 1868.39 0.53
Z4 2240 168.80 1.73
3 Method
The calculation of the average pressure of the coal reservoir is
based on the CBM material balance equation. However, the
traditional model has limitations (specific analysis in Section
4.1). Thus, we considered the dynamic change of the EDA basis on
the previous model in this study; this makes the calculation
results more accurate. There are three steps to improve the
reservoir pressure calculation model; the first is to establish a
gas-phase MBE in the production process based on the principle of
volume conservation; the second is to change the form of the
water-phase MBE so that the EDA increases with the water
production; the last is to substitute the EDA formula into the
gas-phase MBE. Therefore, the reservoir pressure calculation model,
which considers the dynamic change of the EDA, can be deduced.
The CBM in the coal seams is mainly present in the form of
adsorbed, free, and dissolved gas. However, the proportion of
dissolved gas is very small (Dan et al., 1993; Meng et al., 2010);
therefore, the dissolved gas is not taken into consideration when
the gas-phase MBE is deduced. The ground volume of accumulated gas
production is equal to the original geological reserves of the
adsorbed gas in the matrix minus the remaining geological reserves
of the adsorbed gas in the matrix plus the original geological
reserves of the free gas in the fracture minus the remaining
geological reserves of the free gas in the fracture (the gas volume
is the volume under the ground condition.)
(Ahmed et al., 2006):
(1)
Moreover, the formation water in the coal seam mainly exists in
fractures and pores. Due to changes in reservoir pressure, the
water compressibility changes and elastic expansion occurs; this
leads to an increase in the water volume (Zhao et al., 2014).
According to the conservation principle of formation water volume,
the remaining volume of formation water in the reservoir is equal
to the water volume in the fracture in the original condition plus
the water volume increased by elastic expansion minus the
accumulated water production volume (the water volume is the volume
of underground condition):
(2) With the increase of the drainage area, pressure dropping
funnel continues to expand during the development process. When
the
reservoir pressure drops below the critical desorption pressure,
the absorbed gas starts to desorb within the coal reservoir
affected by the pressure dropping funnel. If the pressure dropping
funnel is considered an equivalent cylindrical geometry around the
borehole,
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then the EDA may be used to characterize the pressure drop area,
and the quantity of gas desorption is closely related to the EDA
(Tao et al., 2014).
Formula (2) can be transformed into:
[ ] (3)
By substituting the above EDA equation into the gas balance
equation, the MBE of the coal reservoir can be obtained; this is
considered the dynamic change of the EDA.
[ ( )
( )( )
( )
[ ] (4)
The gas volume factor ( ) varies during production and can be
calculated by:
(5)
Where Z is the deviation factor of gas, which is assumed to be
0.864 due to its slight change during production, and T is the
reservoir temperature. Since each well has a corresponding
reservoir temperature, the gas volume factor is a function of
reservoir pressure.
When the proposed model is applied to calculate the coal
reservoir pressure, the dynamic change of the reservoir porosity
should not be ignored. The dynamic change of the porosity during
the development process is mainly divided into two stages. The
first stage is the saturated single-phase water flow stage; during
this stage, only the formation water discharges, the overlying
stress of the reservoir increases, and the porosity decreases. The
second stage is the gas-water two-phase flow; there is an effective
stress effect at this stage. Simultaneously, the CBM desorbs from
the coal matrix and causes coal matrix shrinkage. When the
effective stress effect is greater than the matrix shrinkage
effect, the porosity decreases, otherwise, it increases (Zhao et
al., 2016).
{
(
) (
)
(6)
(7)
(8)
When we substitute equation (6) into (4), a coal reservoir
pressure calculation model is obtained which involves the
self-regulatory effect and variable EDA. Based on the production
data and the reservoir geological parameters, the new reservoir
pressure calculation model can be used to calculate the average
reservoir pressure during the development process.
4、Results and Discussions 4.1 Reliability of the proposed
model
King (1993) first established the MBE of coal reservoirs. Since
then, the model was used to calculate the average reservoir
pressure:
[ ]
(9)
The traditional reservoir pressure calculation model does not
consider the dynamic change of the drainage area; instead, it
substitutes the fixed value of the area into the calculation model.
First, the fixed value of the area in the traditional model is the
single well controlled range, and it refers to the well spacing.
Furthermore, the well spacing is not the pressure drop range;
meaning that the pressure drop range can’t be replaced by the well
spacing. Second, the production system of the production well is
the drainage and depressurization, and the drainage area
continuously changes with the progress of production. If the fixed
value of the area is substituted into the model instead of the
dynamic drainage area when the reservoir pressure is calculated,
the result will be irrational.
Taking the well T1 as an example, two models were used to
calculate the reservoir pressure. The geological parameters of well
T1 are shown in Table 1. The actual drainage curve of well T1 is
shown in figure.2. When the traditional prediction model was used
to calculate the reservoir pressure, the well-controlled radius was
set to 100, 150, and 200 m. The calculation results of the average
reservoir pressure for the two models are shown in figure.3.
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Fig.2 Actual production curve of the T1 well.
Fig.3 Calculation of reservoir pressure by substituting
different drainage area.
Fig.4 Sketch of pressure calculation range for two models.
When the dynamic EDA is not taken into account, the reservoir
pressure calculation results by substituting the different drainage
areas are quite different (Fig.3); the greater the drainage area,
the slower the drop in the reservoir pressure. At about 750 days,
the EDA reached 100 m. At that time, when the constant drainage
radius was set to 100 m, the calculation result of the proposed
model was the same as the traditional model. This indicates that if
the fixed value of the area is smaller than the actual drainage
range, the calculated reservoir pressure will greatly drop.
Conversely, if the fixed value of the area is larger than the
actual drainage range, the calculation result of reservoir pressure
is the average pressure within the actual drainage range and the
undeveloped range, and the pressure drop rate is slow. If the
setting drainage area increases, the range of the reservoir that
has not been depressurized increases, resulting in a larger
pressure calculation result (Fig.4). However, when the proposed
model was used to calculate the coal reservoir pressure, the
drainage area changed with the actual water production, and the
water production data was used more efficiently. Therefore, the
results which were calculated by the proposed model are more
realistic.
When the proposed model was used to calculate the average
reservoir pressure in the well T1, the pressure drop curve showed a
good correspondence with the actual production curve, as seen by
the curve in figure.2. From the start of production until 300 days,
the reservoir pressure rapidly dropped. Afterward, the reservoir
pressure was relatively stable from 300 days to 1200 days. Finally,
the reservoir pressure rapidly dropped. The analysis of this
pressure curve shows that due to drainage and depressurization, the
pressure around the wellbore rapidly dropped in the initial stage,
and the drainage range extended from the wellbore to a distant
place. In the middle stage, the water and gas production was
stable, and the drainage range gradually extended to a distant
place. At this time, because the reservoir pressure was constantly
replenished from the far well, the average reservoir pressure was
maintained at a stable level. In the later period, the EDA was
stable, the reservoir pressure rapidly dropped in this area, and
the massive desorption of CBM resulted in the rapid increase of gas
production.
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4.2 Reservoir pressure sensitivity analysis
Coal reservoir pressure is controlled by various factors such as
geology, drainage, and engineering (Song et al., 2017; Zhang et
al., 2018; Kang et al., 2018). Moreover, engineering factors are
uncertain and contingent, and their impact on the reservoir
pressure is difficult to assess in a quantitative way (Gu et al.,
2017; Wei et al., 2017). The influence of the geological parameters
on the reservoir pressure is discussed in this section. Firstly, a
typical well was selected as the research object, and its
productivity characteristics are actual production curves.
Secondly, the four-factor and the three-level orthogonal
experiments were designed by selecting the reservoir porosity,
irreducible water saturation, Langmuir volume, and Langmuir
pressure as the target parameters. Finally, the intuitionistic
analysis method was used to analyze the influence of the geological
factors on the coal reservoir pressure during the development
process.
4.2.1 Orthogonal experimental design
The orthogonal design is one of the most effective and
time-saving methods for the studies involving multiple variables to
find out which factors (or variables) mostly influence the
properties of the target product (Ross, 1988). It is designed by
selecting a partial representative combination in all combinations
of the experimental factors. Through the analysis of a part of the
experimental results, the situation of the comprehensive experiment
was studied, and the optimal level combination was realized. The
basic feature of the orthogonal experimental design is to replace
the comprehensive experiments with some characteristic experiments
on one hand, and to study the situation of the comprehensive
experiments by analyzing some experimental results on the other
(Li, 2005).
In this study, the well T1 is considered as the typical well,
and the production characteristic is the production curve of the
well T1. The target geological parameters are initial porosity,
irreducible water saturation, Langmuir volume, and Langmuir
pressure. The initial porosity and the irreducible water saturation
control the water content of the coal reservoir, while the Langmuir
volume and the Langmuir pressure control the gas content of the
coal reservoir. The parameters are independent of each other, and
the joint collocation between the parameters has little effect on
the experimental results; so, the interaction between the
parameters was ignored. Moreover, the ratio of the horizontal
component of each parameter is 1:1.5:2 (Table 3) and the orthogonal
experiment is designed according to the standard orthogonal array
L9 (3
4). The experimental design and experimental results are shown
in the follow (Table 4;
Fig.5): Table 3 Experimental factors and horizontal
parameters
component (m3) (MPa)
1 20 1 2% 0.4
2 30 1.5 3% 0.6
3 40 2 4% 0.8
Table4 Orthogonal experimental design and experimental
results
Test (m3) (MPa)
1 20 1 0.02 0.4 53.75%
2 20 1.5 0.03 0.6 48.52%
3 20 2 0.04 0.8 31.13%
4 30 1 0.03 0.8 21.48%
5 30 1.5 0.04 0.4 59.49%
6 30 2 0.02 0.6 25.53%
7 40 1 0.04 0.6 40.58%
8 40 1.5 0.02 0.8 10.08%
9 40 2 0.03 0.4 39.80%
K1 133.40% 115.81% 89.37% 153.04%
K2 106.50% 118.10% 109.80% 114.63%
K3 90.46% 96.45% 131.20% 62.68%
k1 44.47% 38.60% 29.79% 51.01%
k2 35.50% 39.37% 36.60% 38.21%
k3 30.15% 32.15% 43.73% 20.89%
R 14.32% 7.22% 13.94% 30.12%
(Ki represents the sum of the calculation results of the same
horizontal component of the corresponding parameter; ki is the
average value of Ki. R indicates the range of the
corresponding parameters which is used to judge the order of the
factors affecting the results. Greater range indicates that the
factor has a greater influence on the experimental
results. The calculation method of the range is
R=max(ki)-min(ki))
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Fig.5 Orthogonal experimental calculation results.
4.2.2 Analysis of the results
From the orthogonal experimental results, the influence of the
geological factors was analyzed on the coal reservoir
depressurization by using the intuitionistic analysis. The
intuitionistic analysis solves the problem by comparing the R of
each factor. The main factors affecting the experimental results
are identified by their R. The results showed that the irreducible
water saturation has the greatest influence on the reservoir
depressurization, followed by the Langmuir volume, the initial
porosity, and finally by the Langmuir pressure. From the
corresponding trend of the R, the irreducible water saturation and
the Langmuir volume showed negative correlations with the reservoir
pressure drop, while the effect of porosity on the reservoir
pressure drop showed a positive correlation (Table 4).
Irreducible water saturation and porosity are the key factors
that predominate the water content of the coal reservoir as well as
the amount of the water production (Li et al., 2018). Larger
irreducible water saturation and smaller porosity, suggest weaker
water content in the coal reservoir. In the calculation process,
the gas and water production curves are actual curves, when the
water content of the coal reservoir is relatively weak, the
equivalent drainage radius (EDR) is relatively large; i.e. the EDA
is also relatively large. Although the reservoir pressure variation
was small in the relatively large EDA, the increase of the latter
indicates that it has a high production potential. Previous studies
have shown that Chinese and American coals are different; indeed,
the Chinese coals exhibit relatively higher irreducible water
saturation. This could be one of the reasons why there are many CBM
wells drilled in the study area of the Qinshui Basin, and the
tested CBM wells had relatively high gas contents, yet low gas
yield in comparison with those in selected basins of the United
States (Fu and Qin, 2003). In this circumstance, the CBM wells in
the study area usually feature the early-coming peak of gas
production and a short gas production life.
The Langmuir volume is a key factor that controls the gas
content of the coal reservoir. Large the Langmuir volume indicates
that the adsorption capacity of the coal reservoir is strong.
Moreover, when the single well controlled range and the gas
production rate are constant, the Langmuir volume is larger and the
reservoir pressure drops in a slower rate, indicating that the
reservoir has a good production potential. On the contrary, faster
drop in the reservoir pressure indicates poorer production
potential of coal reservoir. 4.3 Analysis and classification of
reservoir depressurization
Based on the above results, and since the proposed reservoir
pressure calculation model is more accurate in calculating the
average reservoir pressure, some target wells were selected in the
Shizhuangnan Block for further calculation; consequently, the wells
were classified according to the reservoir depressurization
characteristics. However, the reservoir pressure is a key factor in
calculating the dynamic changes of the reservoir permeability
during development; the calculation results were inputted into the
permeability dynamic change model in different wells to study the
influence of reservoir pressure on the dynamic changes of coal seam
permeability (Chen et al., 2015). The calculation results of the 14
wells in the study area are shown in Table 5. Interestingly, the
depressurization of target wells is significantly different (Table
5). The maximum pressure drop can reach 94.22% (well Z3), while the
minimum pressure drop is only 17.06% (well T10). The pressure drop
curves of the different wells are different in terms of shape and
can be specifically divided into "rapidly drop type", "medium-term
stability type", and "slowly drop type", which correspond to the
"rising type", "rebound type", and "drop type" of the dynamic
permeability curve, respectively.
Table 5 Reservoir pressure calculation results
Wells Time (day) (MPa) (MPa) (MPa) (Kpa/100d) Depressurization
type
T1 2308 3.30 2.21 33.03% 47.23 medium-term stability type
T2 1553 3.34 1.74 47.90% 103.03 medium-term stability type
T3 1503 4.20 2.81 33.10% 94.24 slowly drop type
T4 1821 3.61 2.11 41.55% 82.73 medium-term stability type
T5 2044 3.68 0.64 82.60% 148.65 rapidly drop type
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T6 2341 3.42 1.66 51.45% 75.14 medium-term stability type
T7 2285 3.10 1.52 50.97% 69.15 medium-term stability type
T8 1960 3.20 2.14 33.20 % 54.47 slowly drop type
T9 2340 3.34 2.62 21.62% 30.89 slowly drop type
T10 1531 2.63 2.18 17.06% 29.28 slowly drop type
Z1 2622 3.30 0.46 86.06% 108.26 rapidly drop type
Z2 2476 4.37 0.89 79.62% 140.39 rapidly drop type
Z3 2520 4.32 0.25 94.22% 161.58 rapidly drop type
Z4 2240 3.35 2.47 26.30% 39.36 slowly drop type
4.3.1 The rapidly drop type
By calculating the reservoir pressure and by analyzing the
pressure drop characteristic curve, the production wells having
"rapidly drop type" reservoir pressure are T5, Z1, Z2, and Z3. The
pressure variation of these wells ranged between 77.7% and 94.2%,
and the pressure drop rate ranged between 108.3 and 161.6 KPa/100d.
By analyzing the production data, all those wells are classified as
high gas-yield production wells, and the average daily water
production was relatively low and ranged from 0.5 to 1.5 m
3/d. From the
drainage curve, the gas production characteristics of this type
are a short time for the start gas production, which achieves high
gas yields, and stable high yields in the later period. The
characteristics of water production begin with an initial initial
large water production, then rapidly drop in the middle period, and
eventually end with basically no water production.
The analysis diagram of the typical well with “rapidly drop
type” is shown in figure.6. It clearly reflects the dynamic changes
of the reservoir pressure, reservoir permeability, and drainage
radius. The reservoir pressure of the typical well tends to drop
rapidly during the production process, while the permeability of
the reservoir rapidly increases upon a decrease in the reservoir
pressure. From the EDR curve, the EDR rapidly increases in the
early stage, while the increase rate slows down or even remains
constant in the later period. The EDR of the reservoir can be
calculated through water production. Such wells have high-water
production in the early stage and then rapidly decline, so that the
EDR can quickly reach the single well controlled boundary, and
pressure interference can be quickly achieved between production
wells. Subsequently, the coal reservoir rapidly depressurizes
within the EDA and the CBM desorbs in large quantities; hence the
production well can quickly and steadily reach high production in
the later period. Because of low-water production, high and stable
gas production in the later period, the effective stress has little
effect on the coal reservoir; in addition, the effect of the matrix
shrinkage and gas slippage is far greater than the effective
stress, so the reservoir permeability has a "rising type" during
the production process.
Fig.6 "The rapidly drop type" typical well production curve.
4.3.2The medium-term stability type
By analyzing the production curve and by calculating the
characteristic curve of depressurization, the production wells
having "medium-term stability type" reservoir pressure are T1, T2,
T4, T6, and T7. The pressure variation of these wells ranged from
33.03% to 51.45%, and the pressure drop rate ranged from 47.23 to
103.03 KPa/100d. According to the production data, most of these
wells are classified as medium gas-yield production wells. The
average daily gas production and water production ranged from
545.29 to 1064.49 m
3/d and from 1.2 to 2.3 m
3/d, respectively. From the production curve, the gas production
characteristics of such wells are
stable low gas-yield after starting gas production in the
initial period, and the daily gas production gradually reaches high
yield in the later period. The characteristics of water production
in such wells are as follow: the water production is high in the
early period; it then decreases in the middle period, however, the
drop rate is small and basically no water is produced in the later
period.
Figure 7 represents an analysis diagram of a typical well with
“medium-term stability type”. It can be seen that the average
reservoir pressure of the typical well rapidly drops in the early
stage, then remains stable for a period, and finally continues to
rapidly drop in the later stage. The reservoir permeability rapidly
decreases in the early stage, remains stable in the medium stage,
and then rapidly increases in the later stage. From the EDR curve,
it can be seen that the EDR rapidly increases in the early stage,
which is followed by a slower growth rates, nonetheless, it is
still increasing. The reason for these results is due to the
hydraulic fracture in the near-well zone, the permeability of the
reservoir near the production well is high, so the rapid drop of
the bottom hole flowing pressure and the large amount of drainage
in the early production stage cause the rapid drop of the reservoir
pressure in the near-well zone. However,
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the drainage area is continuously expanding during the
production process on one hand, and the pressure of the outer edge
of the reservoir propagates to the drainage area on the other.
Consequently, the average pressure of the reservoir is stable for a
certain period, which results in low gas production. In the later
stage, because of the decrease in the water production, the EDR
reaches the well-controlled boundary, the propagation capacity of
the reservoir’s outside pressure decreases, and the gas production
increases and sustains high gas yields; this makes the reservoir
pressure showing a rapid drop. In the early stage, the influence of
the effective stress on the reservoir permeability is greater than
that of the matrix shrinkage and gas slippage; additionally, the
permeability of the reservoir was rapidly reduced as seen by the
dynamic change curve of the reservoir permeability. Indeed, this is
due to the high -water production and low gas production. During
the middle period, and since the water production decreases, the
effect of the effective stress reduces damage to the reservoir
permeability and renders it stable. Furthermore, and during the
later period, the recovery effect of the matrix shrinkage and the
gas slippage on the reservoir permeability is greater than the
damage effect of the effective stress, result in the gradual
increase of the reservoir permeability. This is explained by the
increase of the gas production and the decrease of the water
production. Therefore, the reservoir permeability is of "rebound
type" during the entire production process.
Fig.7 "Medium-term stability type" typical well production
curve.
4.3.3 The slowly drop type
The production wells having "slowly drop type" reservoir
pressure are T3, T8, T9, T10, and Z4. The pressure variation of
these wells ranged from 17% to 33%, and the pressure drop rate
ranged from 29 to 94 KPa/100d. By analyzing the production data,
all of these wells are classified as low gas-yield production
wells. The average daily gas production is less than 500 m
3/d, and the water
production is relatively high. The average daily water
production ranged between 1.53 and 2.11 m3/d. From the production
curve, it
can be seen that the gas production of such wells is low.
However, the daily water production is high and characterized by
multiple peaks.
Figure 8 shows an analysis diagram of a typical "slowly drop
type" well. It can be seen that the reservoir pressure tends to
slowly drop during the production process, while the reservoir
permeability rapidly decreases upon the change of the reservoir
pressure. Due to the multi-peak shape of the water production in
such wells, the EDR rapidly increases during the production
process. Therefore, the pressure of the outer edge of the reservoir
continuously propagates to the drainage area, and the average
reservoir pressure slowly drops, which ultimately leads to low gas
production. Because of the production characteristics of
“high-water-yield production” and “low-gas-yield production”, the
influence of the effective stress of the coal reservoir is greater
than that of the matrix shrinkage and the gas slippage; so, the
reservoir permeability has a “drop type”.
Fig.8 "Slowly drop type" typical well production curve
5 Conclusions
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(1) To accurately calculate the average pressure of the coal
reservoir during the development process, we mainly considered the
dynamic change of the equivalent drainage area and the
self-regulatory effect based on the classic material balance of
coalbed methane. The difference between the two models was analyzed
by comparing the calculation results between the proposed and the
traditional models. The conclusions show that the results
calculated by the traditional model are greatly affected by human
factors; that is, larger fixed values of the area which is inputted
into the formula results in smaller pressure drops in the
reservoir. Therefore, the calculated results are untrue.
Additionally, when the dynamic change of the EDA isn’t ignored, the
EDA in the reservoir pressure prediction model changes with the
actual production; indicating a relatively accurate calculated
average pressure of the coal reservoir.
(2) The irreducible water saturation, reservoir porosity,
Langmuir volume and Langmuir pressure are selected as the target
parameters. Additionally, the orthogonal experiment was designed to
analyze the influence of the target parameters on the reservoir
pressure during the development process. Based on the
intuitionistic analysis method, the irreducible water saturation
showed the greatest influence on the reservoir pressure, followed
by the Langmuir volume, porosity, and finally the Langmuir pressure
as seen by the experimental results. The irreducible water
saturation and the Langmuir volume are negatively correlated with
the reservoir pressure, while the effect of porosity is positively
correlated with the reservoir pressure.
(3) Some typical wells were selected to analyze their pressure
characteristic curves. The average reservoir pressure that was
calculated by the proposed model is inputted into the reservoir
permeability prediction model; consequently, the dynamic change of
reservoir permeability, during the development process of these
wells, was calculated. The pressure drop curves of the different
wells were different in shape, and can be specifically divided into
"rapidly drop type", "medium-term stability type", and "slowly drop
type", which correspond to "rising type", "rebound type", and "drop
type" of the dynamic permeability curve, respectively. The
reservoir pressure of the “rapidly drop type” production wells
greatly drops during the development process, and the reservoir
permeability gradually increases. The reservoir pressure of the
“slowly drop type” production wells drops to a small extent, and
the reservoir permeability gradually decreases. Moreover, the
reservoir pressure of the “medium-term stability type” production
wells continuously drop in the early and the late stages of the
production process, while the reservoir pressure remains stable in
the medium-term, correspondingly, the reservoir permeability
decreases in the early stage, increases in the later stage, and
stabilizes in the medium stage.
Acknowledgements
We would like to thank China United Coalbed Methane Corporation
for providing the production well date. This study was
financially supported by the National Science and Technology
Major Project of China (Grant No. 2017ZX05064003) and the National
Natural Science Foundation of China (Grant No. 41772159/D0208,
No.41872178).
Reference Chu, S., and Majumdar, A., 2012. Opportunities and
challenges for a sustainable energy future. Nature, 488 (7411):
294. Kuuskraa, V. A., 1989. Coalbed methane sparks a new energy
industry. Oil and Gas Journal, 9: 3-8. Clarkson, C.R., and
Salmachi, A., 2017. Rate-transient analysis of an undersaturated
CBM reservoir in Australia: accounting for effective
permeability changes above and below desorption pressure.
Journal of Natural Gas Science and Engineering, 40: 51-60. Su,
X.B., Lin, X.Y., Liu, S.B., Zhao, M.J., and Song, Y., 2005. Geology
of coalbed methane reservoirs in the southeast Qinshui basin of
China. International Journal of Coal Geology, 62 (4): 197-210.
Yun, J., Xu, F.Y., Liu, L., Zhong, N.N, and Wu X.B, 2012. New
progress and future prospects of cbm exploration and development in
china.
International Journal of Mining Science and Technology, 22 (3):
363-369. Su, X.B., Lin, X.Y., Song, Y., and Zhao M.J., 2004. The
Classification and Model of Coalbed Methane Reservoir. Acta
Geologica Sinica (English
Edition), 78 (3): 662-666. Tang D.Z., Zhao, J.L., Xu, H., Li,
Z.P., Tao, S., and Li, S., 2015. Material and energy dynamic
balance mechanism in middle-high rank coalbed
methane (CBM) systems. Journal of China Coal Society, 40 (1):
40-48 (in Chinese with English abstract). Cervik, J., 1967.
Behavior of coal-gas reservoirs. Journal of Petroleum Technology.
Salmachi, A., and Yarmohammadtooski, Z., 2015. Production data
analysis of coalbed methane wells to estimate the time required to
reach to peak
of gas production. International Journal of Coal Geology,
141-142 (1): 33-41. Carlson, F., 2006. Technical and economic
evaluation of undersaturated coalbed methane reservoirs. In: the
SPE Europe/EAGE Annual Conference
and Exhibition, Vienna, Austria, 6: 12-15. Zhao, J., and Zhang.
S.A., 2012. Study on Pressure Drop Transmission Law of Coal Bed
Methane Drainage Reservoir Stratum. Coal Science and
Technology, 40 (10): 65-68 (in Chinese with English abstract).
Liu, S.Q., S, S.X., Li, M.X., Liu, H.H., Wang, L.L., 2012. Control
factors of coalbed methane well depressurization cone under
drainage network in
southern Qinshui basin. Journal of China University of Mining
and Technology, 41 (6): 943-950 (in Chinese with English abstract).
Zhang, F.N., Qi, Y.G., Li, M.Z., Chen, B., and Meng, S.Z., 2017.
Analysis on gas drainage area affected to gas production potential
of single coalbed
methane well. Coal Science and Technology, 45 (3): 94-100 (in
Chinese with English abstract). Sun, Z., Li, X.F, Shi, J.T., Yu,
P.L., Huang, L., Xia, J., Sun, F.R., Zhang, T., and Feng, D., 2017.
A semi-analytical model for drainage and
desorption area expansion during coal-bed methane production.
Fuel, 204: 214-226. Sun, Z., Li, X.F., Shi, J.T., Zhang, T., Feng,
D., Sun, F.R., Chen, Y., Deng, J.C., and Li, L.J., 2018. A
semi-analytical model for the relationship
between pressure and saturation in the CBM reservoir. Journal of
Natural Gas Science and Engineering, 49: 365-375. King, G.R., 1993.
Material balance techniques for coal seam and Devonian shale gas
reservoir with limited water influx. SPE Reservoir Engineering,
2: 67-72. Hu, S.M., and Li, X.F., 2010. Material balance
equation of coalbed methane reservoir with consideration of
self-adjust effect of coal. Nature gas
Exploration and Development, 33 (1): 38-41 (in Chinese).
This article is protected by copyright. All rights reserved.
-
Penuela, G., Ordonez, A., and Bejarano, A., 1998. A generalized
material balance equation for coal seam gas reservoirs. In:
Presented at the SPE Annual Technical Conference and Exhibition,
New Orleans, 27-30 September. SPE-49225-MS.
Ahmed, T. H., Centilmen, A., and Roux, B. P., 2006. A
Generalized Material Balance Equation for Coalbed Methane
Reservoirs. In: Presented at the SPE Annual Technical Conference
and Exhibition, San Antonio, 24-27 September. SPE-102638-MS
Zhao, J.L., Tang, D.Z., Xu, H., Meng, Y., Lv, Y.M., and Tao, S.,
2014. A dynamic prediction model for gas-water effective
permeability in unsaturated coalbed methane reservoir based on
production data. Journal of Natural Gas Science and Engineering,
21: 496-506.
Thararoop, P., Karpyn, Z.T., and Ertekin, T. 2015. Development
of a material balance equation for coalbed methane reservoirs
accounting for the presence of water in the coal matrix and coal
shrinkage and swelling. Journal of Unconventional Oil and Gas
Resources, 9: 153-162.
Shi, J.T., Chang, Y.C., Wu, S.G., Xiong, X.Y., Liu, C., and
Feng, K., 2018. Development of material balance equations for
coalbed methane reservoirs considering dewatering process, gas
solubility, pore compressibility and matrix shrinkage.
International Journal of Coal Geology, 195: 200-216.
Yao, Y.B., Liu, D.M., Tang, D.Z., Huang, W.H., Tang, S.H., and
Yao, C. (2008). A comprehensive model for evaluating coalbed
methane reservoirs in china. Acta Geologica Sinica(English
Edition), 82(6), 1253-1270.
Zhang, S.H., Tang, S.H., Li, Z.C., Guo, Q.L., and Pan, Z.J.,
2015. Stable isotope characteristics of CBM co-produced water and
implications for cbm development: the example of the Shizhuangnan
Block in the southern Qinshui basin, China. Journal of Natural Gas
Science and Engineering, 27 (3): 1400-1411.
Yang, G.Q., Tang, S.H., Zhang, S.H., Hu, W.H., Xi, Z.D., and Li,
L., 2017. Impacts of vertical variation of different coal texture
types on coalbed methane production in Zaoyuan area of the
Shizhuangnan Block, southern Qinshui basin, north China. Energy
Sources Part A Recovery Utilization and Environmental Effects, 39
(15): 1617-1624.
Zhu, X.S., Liang, J.S., Liu, Y.H., Wang, C.W., Liao, X., Guo,
G.S., and Lv, Y.M., 2017. Influence factor and type of water
production of CBM wells: Case study of Shizhuangnan block of
Qinshui Basin. Nature Science Geoscience, 25 (5): 755-760 (in
Chinese with English abstract).
Yan, X.L., Tang, S.H., Zhang, S.H., Yang, G.Q., and Wang, K.F.,
2018. Study on reconstruction of inefficient well of coalbed
methane in southern Shizhuang Block of Qinshui Basin. Coal Science
and Technology, 46 (6):119-125 (in Chinese with English
abstract).
Peng, C., Zou, C.C., Zhou, T.N., Li, K., Yang, Y.Q., Zhang,
G.H., and Wang, W.W., 2017. Factors affecting coalbed methane (CBM)
well productivity in the Shizhuangnan Block of southern Qinshui
basin, North China: investigation by geophysical log, experiment
and production data. Fuel, 191: 427-441.
Li, C., S, J., Zhao, J.C., and Yang, C.L., 2018. Control
mechanisms of water production and gas production divergences of
CBM Wells in southern Qinshui basin. China Mining magazine, 27
(2):117-124 (in Chinese with English abstract).
Shen, J., Qin, Y., Wang, G., Fu, X.H., Wei, C.T., and Lei, B.,
2011. Relative permeabilities of gas and water for different rank
coals. International Journal of Coal Geology, 86 (2): 266-275.
Dan, Y., Seidle, J.P., and Hanson, W.B. 1993. Gas Sorption on
Coal and Measurement of Gas Content. El discurso civilizador en
Derecho Internacional: Cinco estudios y tres comentarios. Instituto
Fernando el Católico. IFC.
M, Z.P., Tian, Y.D., and Li G.F., 2010. Theory and method of
coalbed methane development geology. Beijing: Science Press (in
Chinese). Ahmed, T. H., Centilmen, A., and Roux, B. P., 2006. A
Generalized Material Balance Equation for Coalbed Methane
Reservoirs. Society of
Petroleum Engineers. Tao, S., Tang, D.Z., Xu, H., Gao, L.J., and
Fang, Y., 2014. Factors controlling high-yield coalbed methane
vertical wells in the fanzhuang Block,
southern qinshui basin. International Journal of Coal Geology,
134-135: 38-45. Zhao, J.L., Tang, D.Z., Gao, L.J., Xu, H., Meng,
Y.J., and Lv, Y.M., 2016. Porosity model and variation law of coal
reservoir in coalbed methane
production process. Coal Science and Technology. 44 (7): 180-185
(in Chinese with English abstract). Kang, Y.S., Jiang, S.Y., Wang,
J., Zhang, B., and Guo, M.Q., 2018. Original Hydrodynamic Patterns
and Their Influence on Coalbed Methane
Drainage in Qinshui Basin. Geological Review, 64(4): 927-936 (in
Chinese with English abstract). Song, Y., Liu, S.B., Ma, X.Z.,
Jiang, L., and Hong, F., 2017. Favorable Depth Distribution of
Coalbed Methane Enrichment and High Yield Zone in
Slope Areas. Acta Geologica Sinica (English Edition),
91(1):371-372. Zhang, Z., Qin, Y., Zhuang, X.G., Li, G.Q., and Liu,
D.H., 2018. Geological Controls on the CBM Productivity of No.15
Coal Seam of
Carboniferous-Permian Taiyuan Formation in Southern Qinshui
Basin and Prediction for CBM High-yield Potential Regions. Acta
Geologica Sinica (English Edition), 92(6):2310-2332.
Gu, J., Wang, S., Ma, C., Gan, P., and Tang, N.Q., 2017.
Influence of Drilling Fluid Components on Shear Strength at
Cement-aquifuge Interface in Coalbed Methane Wells. Acta Geologica
Sinica (English Edition), 91(4):1511-1512.
Wei, Y.C., Li, C., Cai, D.Y., Zhang, A.X., Wang, A.M., and
Xiang, X.X., 2018. New Progress on the Coal Fines Affecting the
Development of Coalbed Methane. Acta Geologica Sinica (English
Edition), 92(5): 2060-2062.
Ross, P. J., 1988. Taguchi techniques for quality engineering:
loss function, orthogonal experiments, parameter and tolerance
design. McGraw-Hill. Li, S., 2005. Applied statistics. Beijing:
Tsinghua University Press (in Chinese). Li, X.W., Liu, D.M., Cai,
Y.D., Yao, Y.B., Zhang, B.R., and Zhang, X.Y., 2018. Moisture
content characteristics of high rank coal reservoir and its
influence on adsorption capacity. Earth Science Frontiers, 25
(4): 237-244 (in Chinese with English abstract). Fu, X.H., and Qin,
Y., 2003. Theories and Techniques of Permeability Prediction of
Multiphase Medium Coalbed Methane Reservoir. Xuzhou: China
University of Mining and Technology Press (in Chinese). Chen,
Y.X., Liu, D.M., Yao, Y.B., Cai, Y.D., and Chen, L.W., 2015.
Dynamic permeability change during coalbed methane production and
its
controlling factors. Journal of Natural Gas Science and
Engineering, 25, 335-346.
About the first author
YAN Xinlu, male, born in 1993 in Jinzhong City, Shanxi Province;
is a Ph. D; he is studying at China University of Geoscience,
Beijing; he is mainly
engaged in petroleum and natural gas engineering; currently
focuses on the development of coalbed methane.. Email:
[email protected].
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About the corresponding author
ZHANG Songhang, male, born in 1982 in Nanyang City, Henan
Province; Ph. D; graduated from China University of Geoscience,
Beijing; associate
professor of China University of Geoscience, Beijing. He is now
interested in the study on coalbed methane geology and development.
Email: [email protected].
This article is protected by copyright. All rights reserved.
mailto:[email protected]