An overview of the potentials and prospects of coalbed methane exploration and exploitation in the Permo-carboniferous coal measures of Barakar formation, Jharia basin, India

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AN OVERVIEW OF THE POTENTIALS AND PROPECTS OF
COALBED METHANE EXPLORATION AND EXPLOITATION IN
THE PERMO-CARBONIFEROUS COAL MEASURES OF
BARAKAR FORMATION, JHARIA BASIN, INDIA
Saikat Mazumder, Karl-Heinz A. A. Wolf
Delft University of Technology, Department of Applied Earth Sciences, Dietz Laboratory.
Mijnbouwstraat 120, 2628 RX Delft, the Netherlands. E-mail: S.Mazumder@CITG.TUDelft.nl
(13 figures, 2 tables)
ABSTRACT. The Permian Barakar coal formation of the Jharia Basin, India will have a very active
role to play in the future energy scenario of India. However coal seams in general are poorly
understood with respect to their behaviour as gas reservoirs. Gas is predominantly stored in an
adsorbed and a compressed state. For the exploration and assessment of coal bed methane it is
important to understand the mechanism of adsorption, retention and accumulation of methane gas
within the coal seams, during the process of coalification. The gas storage capacity of a saturated
coal seam varies non-linearly as a function of pressure, as described by Langmuir (1916). The
Langmuir constants that define the gas storage as a function of pressure for saturated coals are
measured in the laboratory, generating an adsorption isotherm. A laboratory investigation into the
sorption characteristics of a coal seam from the Jharia basin, led to the generation of an adsorption
isotherm. The Langmuir sorption isotherm defines the relationship between the capacities for coal to
store gas to the external pressure of the gas. At low pressure, the relationship between storage
capacity and pressure is linear as in Henry's Law isotherm. It provides predictive information into
"Gas Storage Capacity" and "Recovery Factor". The approach adopted here for CBM reserve
prediction, uses a modified mass balance and a field example of the coal seams of Barakar
Formation, Jharia Basin, India. As gas storage is well documented and here is a method, which uses
the production history of the reservoir to estimate the ultimate reserve recovery for the next twenty
years. The objective can be achieved with coalbed methane reservoirs, by optimizing completion
design, optimizing well spacing, and optimizing simulation designs. Each of these optimizations
requires accurate prediction of long-term well production. Here in this work two techniques have
been focused upon, to estimate coalbed methane well production. One of the techniques is a
production decline technique and the other is material balance and flow equation calculation. Both
analysis techniques can be useful. It depends on the data available for analysis and the required
accuracy of the production forecast. Decline curve techniques and material balance calculations
generally satisfy for producing wells within established well patterns that have production profiles
with a consistent decline trend. Reservoir simulation is applicable to all stages of the well life;
however, it is most useful in areas where an abundance of core, log, and well test data are available.
Molecular diffusion of methane in a coal matrix has been quantified by determining a sorption time,
t (days), which is related to cleat spacing (ft) and the diffusion coefficient (ft2/day). An effort is
made to use a diffusion coefficient or diffusivity as a tool for seam-to-seam correlation.

KEYWORDS: Jharia, Barakar, Parbatpur, Gondwana, Bokaro, Raniganj, Amlabad, Talchir,
Archean, Recovery factor, Isotherm, Sorption, Pseudo-steady state.
1. Introduction
India, which has the 6th largest coal reserves
in the world, is expected to have a reasonable
potential for coalbed methane. In 1992 it
embarked on evaluating its coal bearing
basins for their coalbed methane potential.
They tested and flowed coalbed methane for
the first time from a well, which was drilled in
the Parbatpur Block of the Jharia basin. Since
then, efforts are being made to exploit this
energy source cost effectively. About 99% of
the coal reserves of India are in the Gondwana
basins while the remaining are in the Tertiary
basins (Fig. 1). The Gondwana basins have
been prioritized for evaluating their coalbed
methane plays. The priority has emerged with
Jharia and East Bokaro Basins on the top
(James Peters9).
Coalbed methane exploration and exploitation
activities are still in the initial stages of
research and development. Geo-scientific,
reservoir and production characteristics are
integrated to evaluate the coalbed methane
play of the Jharia basin. This article is a first
step to solve one of those problems.
Figure 1: Major coalfields of India. Revised after the Atlas of India, 1983
2

2. Geology and Structure of Jharia Basin
The Jharia basin is a sickle-shaped Gondwana
basin with an areal extent of about 450 km2.
Lower Gondwana sediments are surrounded
on all sides by Pre-Cambrian metamorphics,
(Fig. 2). The Barakar formation is the main
coal bearing stratigraphic unit. Although,
some coal seams are also present in Raniganj
Formation. At places, presence of igneous
intrusive is found, which affected the coal
quality. The southern and northern basin
margins are faulted and the faults, which are
active unto present times, giving, rise to
numerous fault blocks.
High-resolution lineament studies carried out
in Jharia basin indicate the presence of three
lineaments, respectively. NNE-SSW, NE-SW
and NW-SE in their order of dominance.
Field examination of cleat and fracture system
indicates that the cleat systems are open.
Other fractures like joints are also open, but in
the vicinity of faults these fractures are likely
to be obliterated by secondary fillings and
'gouge', as a consequence the Parbatpur block
possibly subdividing into about 24 fault
blocks at the level of seam XV. Apart from
permeabilities ranging from 0.01 to 2.5-3.5
md (pre stimulation), the coal also contains
buff coloured, coarse to medium grained,
feldspathic sandstones, grits, shales, and
carbonaceous shales. The cleat system in the
coal of this area is well developed. The total
coal reserve (for seams IX-XVIII) of this
block is of the order of 800MMT. The major
contributor of the coal is the XV-XVIII coal
seams, with a reserve of 400 MMT.
Figure 2. Regional tectonic settings of the Jharia
basin.
Presently CBM activities are confined within
the unmined Parbatpur block in the SE part of
the basin. This block occupies an area of
approx. 18 km2. There are two prominent E-
W trending doubly plunging synclines,
flanking an anticlinal high (Parbatpur-
Amlabad high). Tectonically it is a half
graben structure with an inlier. The anticlinal
area is dissected by a number of criss-cross
faults indicating a compressed stress pattern.
In the block area, the Barren Measure
Formation (middle Permian) is exposed
underlain by Barakar Formation (lower
Permian) and Talchir Formation (upper
Carboniferous) on Archean Metamorphics or
Table 1: Comparative details of the structural elements of the study area.
BLOCK STRIKE
OF THE
STRATA
AMT./
DIR. OF
DIP
FAULTS FOLDS CLEAT
DIRECTION
Amlabad N-S turns
to E-W
60-100 /
North and
South
Dungri-Petia fault
passes along the eastern
boundary
A domal structure
occurs in NE portion
over the B2 anticline
N250E-S250W to
N650W-S650E
Parbatpur NE-SW
turns to
E-W
100-120 /
West and
South
Large no of multi-
directional fault, great
boundary fault to the
south of the block
Two domal structure
occur in the centre
over the B2 anticline
3

basement. A comparative detail of the
structural elements of the studied area is
presented in Table 1. Around the area, highly
gassy mines of the Jharia coalfield are located,
with gas emission rate more than 14 m3/ton.
The Barakar coal seams are the main
exploration targets.
Table 2. Petrographic details of the coal
Basin Damodar
Formation Barakar
Seam XV
Mine Amlabad
Sample No. M/A/1
Vitrinite 57 %vol.
Inertinite 42.6 %vol.
Liptinite 0.4 %vol
Vitrinite Reflec. 1.08 %
Mineral Matter 14.82 % dry mass
Pure coal 85.18 % dry mass
Moisture as recorded 1.35 % mass
Equivalent moisture 3.49 % mass
Helium density 1.5gm/cc
ASTM Rank Medium to high
volatile bituminous
Temperature 46°C
Depth 375 m
Thickness 2.28 m
3. Gas Storage Capacity and Recovery
factor
A sorption isotherm is a primary coal analysis
that is measured on coal. Isotherm data
usually is interpreted by assuming that they
can be fit to the Langmuir relation (Langmuir,
1916). The Langmuir isotherm including the
parameters for the coal sample is represented
as follows:
(1 ) /
sL
GV fadPP=- +P…...…………(eq. 1)
The above parameters of a typical Langmuir
isotherm of the coal sample, as described in
Table 2, are as follows.
L
V = 586.37Scf/ton
f
ad = 0.196
P
= 525psi
L
P
= 360psi
s
G = 279.66Scf/ton
The isotherm of the coal sample is shown in
Figure 3.
Figure 3. Langmuir sorption curve for coal,
representative for its methane capacity.
In a coal bed methane reservoir, the
volumetric reserve calculation is simply the
product of gas in place (GIP) and the
estimated recovery factor at the economic
limit. The Gas recovery factor ( f
R
) is the
most difficult parameter in the volumetric
equation to estimate accurately.
The recovery factor can be estimated from the
isotherm using; ()/
f
R
Cgi Cga Cgi=- . Here
f
R
is the recovery factor, the initial
sorbed gas concentration and the
abandonment pressure sorbed gas
concentration.
Cgi
Cga
The major drawback of this method is that the
average reservoir pressure at abandonment is
4

usually estimated as abandonment pressure.
The pressure is dependent on future economic
condition in addition to reservoir properties
and production history of the reservoir.
Thereby, the abandonment pressure (Pa) is
defined as, the pressure where the gas rate
becomes too low and the production of CBM
on longer remains cost effective. (Joubert et
al., 1973 and Moffat et al., 1953).
In the previous case the Langmuir pressure is
about 360 psi. Below this pressure the well
will produce. An abandonment pressure of
100 psi is assumed for estimation of the
recovery factor.
Hence the gas content at initial pressure (Cgi)
is 364 Scf/ton, the gas content at abandonment
pressure (Cga) is 114 Scf/ton and based on the
above, the recovery factor (Rf) is estimated to
be 68.7% (Crossdale et al. 1998 and Diamond
et al., 1998).
4. Derivation of the Advanced Mass
Balance Technique
The mass balance technique neglects the
storage of gas in the cleat system. The amount
of cleat related gas is insignificant compared
to the adsorbed gas in the coal matrix. The
technique relates the adsorbed gas content
directly to reservoir pressure without
consideration for the cleat system fluids or
cumulative water production, which is
extracted from the cleats. Hence the
dewatering of the coal in the wet areas will
not affect the linear nature of the modified
pressure function versus the cumulative gas
production data, during the early producing
life of the well. In practical terms, it does not
matter how the pressure declines; the
Langmuir isotherm defines the remaining gas
adsorbed on the coal as a function of pressure.
(See King12 and Jensen et al10).
The initial equation is as follows, where is
the current gas produced, is the original
gas in place (Bcf).
P
G
OGIP
P
GOGIPCGI=-P
d
L
..…………….……(eq. 2)
Connecting the gas in place (GP), to the area
connected to the wells in acres (A), net coal
thickness in feet (h), and coal density (d) in
tons/ (acre-foot) gives:
***GIP V A h d=………….…...…...(eq. 3)
Substituting (eq. 3) in (eq. 2) gives:
*** [/( )]* ***
Pi L L
GVAhdPPP VAh=-+
(eq. 4)
The expression on the right of the (eq. 4) is
obtained by substituting Langmuir’s equation
for current gas content (V). Substituting
Langmuir’s equation for Vi we obtain the final
equation in slope intercept form:
[/( )] 1/( )* [/( )]
LLPii
P
PP VAhd G PPP+=- + +
(eq. 5)
Equation 5 presents a graphical analysis of
pressure behavior that can be used as an
independent ultimate recovery prediction tool
to complement simulation predictions, where;
–1/(VLAhd) is the slope, and,
[Pi/(Pi+PL)] is the y-intercept.
Case Study
One of the Wells, (X) is located at the
expected no-flow boundary between the
surrounding producing wells. This allows the
measured pressures to be indicative of the
reservoir pressure, since it is not subject to
near well pressure draw down effects. The
pressure data used is an average of the
5

pressure profiles of all the five producing coal
seams, as shown in Figure 4. The cumulative
production data, associated with each
pressure, is the sum of the five producing coal
seams. Figure. 5 illustrate the application of
Well X production data set where the
cumulative gas produced is plotted on the X-
axis and the modified pressure term (P/P+PL)
on the Y-axis. The X-intercept of the data
extrapolation yields the original gas in place
in the drainage area. An average Langmuir
pressure (PL) value of 360 psi was used, as
derived from eq.1. An anticipated
abandonment pressure of 100psi is assumed.
New, extrapolation of the pressure and
cumulative production data back to the Y-axis
yields a calculation of the initial pressure.
Analysis of the slope of the extrapolated line
is useful for determining information about
reservoir properties like Langmuir volume,
drainage area, thickness of producing zone
and the density of the coal. It provides a
qualitative check of the whole reservoir.
Collectively a practical method for coal gas
reserve estimation, using reservoir pressures,
has been presented. The advanced mass
balance technique provides an accurate
estimate of the ultimate recovery from a coal
bed, to compare the decline curve, reservoir
simulation and volumetrics to increase
confidence in an estimate.
Figure 5. Estimated gas reserves as a function of
pressure and the cumulative gas production.
5. Role of the Permeability in Techno-
Economics
Worldwide experience of the CBM production
establishes the fact that producibility varies
widely within a basin. Variation in the
permeability of the producing coal seams is
the main reason. It is the principal controlling
factor for efficiency of de-watering process,
upon which the decline in reservoir pressure
and by that de-sorption and production of
CBM, largely depends. A fall in producibility
with decreasing permeability has led CBM
industry of the world to formulate a rule of
thumb for defining one millidarcy as the
lowest limit of permeability for economic
exploitation. Below this value, de-watering
process becomes inefficient, thereby
drastically affecting the producibility.
Contrary to conventional reservoirs, the
permeability of a coal seam is the most
important criteria, followed by the gas content
and the seam thickness. As permeability in
coals is highly stress dependent, its reduction
with depth is also well known. Shallow depths
favour faster de-sorption of the gas during
pressure decline. (See Bodden et al. 1998).
Figure 4: Pressure profile of various seams and
average pressure drop, during production.
6

The Barakar formation in Jharia basin has
been subdivided into the Lower Barakar,
Middle Barakar and Upper Barakar as shown
in Figure 6.
Lower Recovery factors for the Lower
Barakar sequence is primarily due to the
following reasons:
a) A lower permeability in the range of 0.1 to
0.01 md.
b) A reasonably high cleat porosity resulting
in an initial high quantum of water within the
drainage area of a well.
c) Low permeabilities related to water phase,
which make dewatering, de-pressurization and
gas desorption a slow process. High,
irreducible water saturation (45-50%) also
affecting efficiency of dewatering process.
In spite of their huge thickness deeper, low
permeability coal seams tend to yield very low
recoveries. Thickness can only add to the
reserves in place. They certainly play no role
in the improvement of the flow characteristics
and consequently no role in improving the
efficiency of de-watering. Dewatering is the
very basis of CBM production and is likely to
affect the techno-economics.
6. Production Decline Analysis
Figure 6. Barakar coal seams, net thickness versus permeabilities.
Production decline trends of producing CBM
wells can be analysed to accurately estimate
future production for coalbed wells. Decline
curve analysis is useful, as it is widely
accepted and is practiced in the conventional
oil and gas industry with ease and it requires
only the well producing history. Using decline
curve analysis technique for CBM well is
complicated by the fact that it may take
several months to years for a well to show a
“declining” production trend. Well spacing,
permeability, producing conditions, and the
diffusion characteristics of coal all affect the
shape of the production profile. (See Choote
et al., 1986 and Hanby, 1991). Analysis of
pressure transients in simulated cases show
that the decline trend is established when the
outer flow boundary effects dominate the flow
characteristics (pseudo-steady state flow). So
declining production trends tend to be best
developed in wells that are part of a pattern of
producing wells, in which each well is
interfering with other producing wells.
The criteria for declining curve techniques
are:
7

· Decreasing gas and water rates.
· Consistent slope in gas rates for at least
six months.
· The production life more than 22 months
including a six months decline period.
· The wells are showing interference
behaviour.
Usually not all the parameters are met for
each well. However when most of the criteria
are met, there is a high degree of confidence
in the production forecast based, on the
decline analysis. Figures 7 and 8 illustrate the
use of both the exponential decline technique
and the hyperbolic decline technique for
estimating the future production of our
example well (Well X) with a commingled
production.
Exponential decline curve equations are used
most often for analysing oil and gas wells.
This type of decline is a constant percentage
decline, which is characterized by straight line
on a graph of production against time. Here
the log of the production rate is plotted against
the production time. The set of exponential
decline equations are:
a) …………………….(eq. 6)
0
at
t
qqe
-
=
, where ( ) is the production rate, using the
initial production rate ( q) and cumulative
producing time ( t).
t
q
0
b) 0
ln ln t
q
at
-
=
q
……….……..(eq. 7)
The equation calculates the decline rate ( )
from a fit of measured production data.
a
c) 0
ln( / )
t
qq
ta
-
=……….………(eq. 8)
, as the time-rate (t) equation.
d) 0
0
1at
t
qq
L
R
q
-
-
==-
e…………(eq. 9)
, as the loss ratio, (
L
R).
The equations 6 to 9 are used to calculate
cumulative production ( G):
P
Figure 7. Production forecast, using production rate, time and an exponential
decline technique.
8

e) 0t
p
qq
Ga
-
=………………...(eq. 10)
In this study, the coalbed methane production
data partly follow the exponential decline
equation. The time zero of the production data
has to be reset to the point, where the
production data starts with an exponential
decline. This adjustment reduces the time
span. To estimate the initial production rate,
the rate data are extrapolated. To apply these
equations, the units for decline rate and
production rates must be consistent (i.e.,
decline rate expressed as “percent per day”
and production rate as “Sm3 per day”).
Figure 7 shows the semi log graph of daily
production rate plotted against time for
Coalbed Methane well with a backpressure of
2.5 Kgf/cm2. For this analysis the last six
months of production data have been
analysed. A least squares fit of the production
data gave a decline rate as shown on
individual plots. This line was extrapolated
and used to estimate the ultimate recovery at
some economic limit.
The same set of production data is also used to
fit into the hyperbolic decline equations. A
hyperbolic decline is characterized by a
constant change of decline rates with respect
to time (i.e. the derivative of the exponential
decline equation). The set of hyperbolic
decline equations are:
a) …………(eq. 11)
1/
00
(1 ) n
t
qq nat
-
=+
This equation is used to calculate production
rate ( ) using initial production rate ( ) and
cumulative producing time ( t), as function
where is the hyperbolic decline constant and
varying decline rate.
t
q
n
0
q
0
a
b) ……………..(eq. 12)
00
(/)
n
tt
aaqq=
Figure 8. Production forecast, using production rate, time and an
hyperbolical decline technique.
9

This equation calculates the decline rate ( )
from a fit of measured production data.
t
a
c) 0
(/) 1/
n
t
tqq na
-
=-
0
t
……….(eq. 13)
Time rate (t) equation.
d) ……….(eq. 14)
1/
1(1 ) n
t
LR na -
=- +
Loss ratio ( t
L
R).
Equations 11 to 14 are used to calculate the
cumulative production ( G):
P
e) 0
11
00
(1 ) ( )
n
Pn
t
q
Gna q q
--
=
--
n
…..(eq. 15)
Figure 8. is the semi log graph of daily
production rate plotted against time with a
hyperbolic fit.
6.1. Analysing the Suitability of the
Procedure
To compare the exponential decline method
with the hyperbolic decline method, it is
stated that an exponential decline method is
more suited for oil and gas production
prediction rather than coalbed methane
production forecasting. Going by the typical
production profile of a coalbed methane well,
this profile differs significantly from the
typical decline of a conventional gas well as
shown in Figure 9. In Figure 9, the Phase III
of a production profile begins when reservoir
flow conditions have stabilized, the well has
reached its peak gas rate, and the gas
production is characterized by a more typical
decline trend. This well is dewatered at the
beginning of Phase III. During this phase
water production is low and/or negligible, and
the relative permeabilities for gas and water
change very little. The pseudo-steady state
flow persists for the rest of Phase III and the
producing rates of gas and water are
controlled by the physical properties of coal,
as well as the boundary conditions. Classic
pressure transient behaviour of a dual porosity
reservoir is based on mathematical models,
which are developed by Warren and Root
(1997). The classic behaviour does not occur
in coalbed methane reservoirs. In an idealized
dual porosity reservoir the pressure derivative
profile is divided into an initial well bore
storage period followed by an infinite acting
period. The unit slope of the profile is 45°
during the well bore storage period. At the end
of the well bore storage period most of the
fluid production originates from the reservoir.
The infinite acting period in the classic dual
porosity reservoir is characterized by three
sub-periods, a fracture system dominated sub-
period, a system transition sub-period and a
matrix system dominated sub-period. During
the fracture system dominated sub-period, the
production originates from the secondary
porosity. As time continues, the fracture
system dominated sub-period ends as fluid
starts to flow from the matrix system. In
between a system dominated sub-period a
production fall and a corresponding rise in the
pressure derivative is observed. This classic
pressure behaviour does not occur in coal gas
Figure 9. Production phases of a well
during production.
10

reservoirs that produce both gas and water.
The single-phase flow tends to occur during
the fracture system dominated sub-period and
the multiphase flow tends to occur during the
matrix system dominated sub-period. The
change from single to multiphase flow
changes the fluid flow rate through the
reservoir and the resulting derivative
behaviour is as shown in Figure 10. So the
resulting derivative profile removes the
possibility of an exponential decline with a
constant decline rate. It favours a model with
an initially high decline rate followed by a
less decline rate. The profile tends to stabilize
corresponding to the derivative stabilization
with a hyperbolic decline fit in a period of 4 to
4.5 years, in each case as shown in Figure 8.
(Holditch, 1990, Sawyer, 1987 and Schwerer,
1984).
In the production well of this example with a
commingled production of five seams with
varying permeabilities and varying t values,
the system is considered in a t versus
permeability plot (Fig. 11). A lower t value
signifies smaller cleat spacing, i.e. higher cleat
intensity and a higher diffusion coefficient.
When regarded in terms of production, a
higher permeable seam will desorbs faster,
attain its peak early and allow the infinite
acting period to be dominated by a prolonged
matrix dominated sub-period. This is different
in case of a less permeable seam, because of
its higher t value. The peak production is
delayed and the well bore storage is more
pronounced. Accordingly when such five
seams with different relative permeabilities
are allowed to produce together, a case of
constant production decline rate is never
expected. The interference of a declining
production of a high permeable reservoir with
peak production of a less permeable reservoir,
results in a stable production for a time span
of 4 to 4.5 years. (Ettinger et al. 1966).
Figure 11. Tau values and permeabilities
of the seams in Well X.
Figure 10. Pressure stages in a well during its
p
roduction life.
6.2. Analysis using the Mass Balance
Technique
As presented by King (1993), this technique
incorporates the effects of gas desorption from
the coal matrix as well as dynamic changes in
gas and water permeability in the coal
fractures. To use this technique a " Material
balance simulator" was programmed. It is not
widely used for production analysis and
forecasting of coalbed methane wells. This
technique is theoretically sound within the
boundary, of the assumptions used to generate
the solutions. The technique is useful for
11

validating recovery calculations, generated by
reservoir simulators, and for estimating well
performances of mature producing fields in
which sufficient reservoir data is available.
The assumptions inherent in the material
balance technique presented by King are as
follows:
a) It assumes equilibrium between the free gas
and adsorbed gas in the reservoir (saturation
conditions with respect to the isotherm).
b) It requires accurate estimate of key
reservoir data such as pressures, desorption
isotherm, permeability characteristics etc.
c) It assumes pseudo-steady state desorption
characteristics.
d) It models well bore damage or stimulation
using, skin factors (not applicable for
hydraulically fractured wells).
In the present technique, developed by Seidle
(1991) and Yee et al. (1993), a coalbed
methane reservoir has to reach the dewatered
phase, which is defined by:
1. A declining gas production rate trend
(outer boundary dominated, pseudo-steady
state flow), and
2. Changes in the relative permeabilities of
gas and water in the reservoir.
Figure 12. Tau values and cummulative gas production against time.
This technique combines a coalbed methane
material balance equation with a gas
deliverability equation, to forecast gas
production rates. The technique is used on the
production data of an example well (Well Y).
Equation 16 is used to calculate the gas flow
rate (
g
q).
[( .) ( )]
1, 422 [ln / 3 / 4 ]
g
g
D
Khmavgp mpwf
qTrerw sDnqg
-
=
-++
(eq.16) ,
where:
g
K
is the effective permeability to gas (md),
the thickness, ma the real gas
pseudo-pressure, which corresponds to he
average reservoir pressure (psi
h
re
(.vgp)
2/cp),
the real gas pseudo-pressure, which
corresponds to the bottom hole pressure
(psi
()mpwf
2/cp). is the reservoir temperature (R),
the drainage radius (ft), rw the well bore
T
12

radius (ft),
s
the well bore skin factor and
D
D
n
()
mp
non-Darcy flow coefficient (D/MScf).
/
p
The real gas pseudo-pressure in to above
equation, changes with the average reservoir
pressure at every point of time.
2
p
pb
gzdpm=ò…………………(eq. 17)
Where
p
is the pressure (psi), pb is an
arbitrary base pressure,
g
mis the gas viscosity
(cp) and
z
is the compressibility factor.
The following example illustrates the use of
Seidle's analytic technique for long-term gas
production of the barefoot seam of Well Y
(1019.2 to 1049.40 mts.). Figures 12 & 13
show graphically the result of the forecast
calculations.
Other than the above two expressions
(Eqations.16 &17) the simulator developed
takes into account:
1. Gas initially held in the coal cleats.
2. Initial absorbed gas in the coal matrix.
3. Water influx into and production from the
coal fracture system.
4. Gas remaining in the coal cleats.
5. Gas remaining in the coal matrix.
A combined expression accounts for the
cumulative produced gas volume:
3
6
3
6
[7.758*10 (1 )1/ ]
[1.306*10 ( /1 )]
[0.001( / ) / . ]
[7.758*10 (1 )1/ ]
[1.360*10 ( . /1 . )]
Pfwi
B
ew p g
fwig
mB
GAhSB
Vm Ah bpi bpi
WB W avgB
Ah S B
V Ah bavg p bavg p
f
r
f
r
-
-
-
-
=-
++
+-
--
-+
gi
(eq. 18)
7. Conclusion
Coal reservoirs are systems of storage and
transport mechanisms that can be
characterized using mathematical models.
Simulation studies have shown that well to
well interference effects can greatly improve
the economic recovery of gas from water
saturated coal seams. To accurately evaluate
coalbed methane reservoirs, we must acquire
and integrate the proper reservoir data.
Material balance calculations for estimating
gas-in-place for coalbed methane reservoirs
have been derived from conventional material
balance equations by adding terms to account
for desorption mechanisms. Material balance
methods also can be coupled with flow
equations to predict future production rates.
Optimizing recovery from coalbed methane
reservoirs requires accurately predicting long
term well production. Techniques for
forecasting production for coalbed methane
wells under pressure depletion include
volumetric calculations, production decline
analysis, material balance and flow equation
calculations, and reservoir simulation. Decline
curve techniques and material balance
calculations generally agree with the profiles
for producing wells within established well
patterns that have a consistent production
Figure 13. Average reservoir pressure and
production rate over time.
13

decline trend. Reservoir simulation is
applicable to all stages of the well life;
however, it is most useful in areas where an
abundance of reservoir data have been
generated and well test data are available. In
the course of the study it was observed that
Tau values can be used as a fingerprint of
each coal seam and thus can be used as a tool
for seam to seam correlation. To use material
balance technique, a simulator was developed
using Seidle’s Mass Balance equations.
All the above mentioned case studies contain
the final analysis of the data using
corresponding techniques, but original
reservoir, reserve and production data have
purposefully been omitted because they stand
as confidential.
8. References
BODDEN,W. R. III, EHRLICH, R., 1998.
Permeability of coals and Characteristics of
Desorption Tests: Implications for Coalbed
Methane Production. International Journal of
Coal Geology, 35: 333-347.
CHOOTE, R., MACCORD, J.P.,
RIGHTMIRE, R.T., 1986. Assesment of
Natural Gas From Coalbeds by Geological
Characterization and Production Evaluation.
Geology, 21: 223-245.
CROSSDALE, P. J.; BEAMISH, B.B.,
VALIX, M., 1998. Coalbed Methane Sorption
Related To Coal Composition. International
Journal of Coal Geology, 38: 147-158.
DIAMOND, P. W., SCHATZEL, S.J., 1998.
Measuring the Gas Content of Coal: A
Review. International Journal of Coal
Geology, 35: 311-331.
ETTINGER, I.; EREMIN, I.; ZIMAKOV, B.,
YANAVSKAYA, M., 1966. Natural Factors
Influencing Coal Sorption Properties. I.
Petrography and Sorption Properties of Coals.
Fuel, 45: 267-275.
HANBY, K.P, 1991. The Use of Production
Profiles for Coalbed Methane Valuation.
Paper 9117, Gas Technology Symposium, The
University of Alabama, Tuscaloosa (May 13-
17, 1991): 443-452.
HOLDITCH, S.A., 1990. Coal Seam
Simulation Manual. Gas Research Institute
Tropical Report No. GRI-90/0141, Chicago,
Illinois.
PETERS, J., 2001. Evaluation of Coalbed
Methane Potential of Jharia Basin, India, SPE
Asia Pacific Oil and Gas Conference and
Exhibition, Brisbane, Australia (October 16-
18, 2000).
JENSEN, D., SMITH, L.K., 1997. A Practical
Approach to Coalbed Methane Reserve
Prediction Using a Modified Material balance
Technique. International Symposium on
Coalbed Methane, The University of
Alabama, Tuscaloosa (May 13-17, 1997):
105-113.
JOUBERT, J.I.; GREIN, C.T., BIENSTOCK,
D., 1973. Sorption of Methane on Moist Coal.
Fuel, 52: 181-185.
KING, G.R., 1993. Material-Balance
Techniques for Coal-Seam and Devonian
Shale Gas Reservoirs With Limited Water
Influx. SPE Reservoir Engineering Journal,
(February, 1993): 67-72.
LANGMUIR, I., 1916. The Constitution and
Fundamental Properties of Solids and Liquids.
Journal of the American Chemical Society,
38: 2221-2295.
MOFFAT, D.H., WEALE, K.E., 1953.
Sorption by Coal of Methane at High
Pressures. Fuel, 32: 325-330.
14

SAWYER, W.K., 1987. Using Reservoir
Simulation and Field Data to Define
Mechanisms Controlling Coalbed Methane
Production. International Coalbed Methane
Symposium, Tuscaloosa (November 16-19,
1987) Paper 8763: 295-307.
SCHWERER, F.C., 1984. Development of
Coal-Gas Production Simulators and
Mathematical Models for Well-Test
Strategies. Gas Research Institute Final
Report No. GRI-84/0060, Chicago, Illinois.
SEIDLE, J.P, 1991. Long-Term Gas
Deliverability of a Dewatered Coalbed. SPE
Paper 21488, Gas Technology Symposium,
Houston Texas (January 23-25, 1991): 63-70.
WARREN, J.E. AND P.J. ROOT, 1963. The
Behavior of Naturally Fractured Reservoirs.
SPE Journal , September, 1963: 245-255.
YEE, D. ; SEIDLE, J.P. & HANSON, W.B.,
1993. Gas Sorption on Coal and Measurement
of Gas Content. Am. Assoc. Petr. Geol.: 159-
184.
Nomenclature
a Constant/varying decline rate
A Area, acres
avg. p Average reservoir pressure, psi.
b Langmuir isotherm constant, psi-1
Bgi Gas formation volume factor at pi,
rcf/Scf.
Bavg.
g
Average gas formation volume factor,
reservoir volume / surface volume.
Bw Water formation volume factor,
bbl/STB
CGIP Current gas in place, Bcf
d Density of coal, tons/acre-foot
DnD Non-Darcy flow coefficient, D/Mscf
fad Correction for ash, moisture content,
dimensionless
GS Gas storage capacity, Bscf
GP Current or cummulative gas
produced, Bscf
h Height of producing interval or coal
thickness, feet
Kg Effective permeability to gas, md.
LR Loss ratio (" effective" decline)
m(avg
.p)
Real gas pseudo-pressure
corresponding to the average
reservoir pressure (avg.p), psi2 /cp.
m(pwf
)
Real gas pseudo-pressure
corresponding to flowing bottom hole
pressure (pwf), psi2 /cp
m(p) Real gas pseudo pressure
n Hyperbolic decline constant
OGIP Original gas in place, Bcf
p Pressure, psi
pb Arbitrary base pressure, psi
pi Initial reservoir pressure, psia
P Reservoir pressure, psi
PL Langmuir Pressure; pressure where
the coal storage capacity is half the
Langmuir volume
q Surface gas flow rate, Mscf/day
q0 Gas rate at time t=0, Mscf/day
qt Gas rate at time t, Mscf/day
re Drainage radius, ft
rw Well bore radius, ft
s well bore skin factor, dimensionless
Swi Initial water saturation, fraction
t Time period between q0 and qt, hrs,
days
T Reservoir temperature,
°R
V Gas content at pressure P, Scf/ton
Vi Initial gas content at pressure Pi,
Scf/ton
VL Langmuir Volume, the maximum gas
storage capacity of the ash free coal,
Scf/ton
Vm = Matrix volume, ft3
we Water influx, Mbbl
wp Cumulative water produced. MSTB
Z Real gas compressibility factor,
dimensionless
ff Interconnected fracture (effective
porosity), fraction.
15

mg Gas viscosity, cp
rB Bulk density, g/cm3
16