Modeling Methane Emissions and Ventilation Needs by Examination of 

Mining Induced Permeability Changes and Related Damage to Ventilation 

Controls 



Luxbacher, K.D. 

Virginia Tech, Blacksburg, VA, USA 

Erdogan, S.S. 

Middle East Technical University, Ankara, Turkey 

Karacan, C.Ö. 

NIOSH, Pittsburgh, PA, USA 

 



ABSTRACT: Understanding methane emissions in underground coal mines is critical for a safe and productive mine. In addition 

to reasonable estimation of initial coalbed reservoir parameters, it is also crucial that changes in effective stress due to mining and 

pore pressure reduction are taken into account due to their effects on porosity and permeability. Primary parameters for estimation 

of emissions or modeling of the mining environment for this purpose are porosity and permeability which can change dramatically 

as a result of stress redistribution associated with mining and gas desorption from a large coal volume. These parameters affect the 

emission rates and ventilation requirements, as well as water inflow into the working environment. Stopping leakage, on the other 

hand, is a secondary stress dependent factor in estimation of emissions, as convergence of the roof and floor strata, compromising 

the integrity of the stopping, may result in leakage, making prediction of ventilation requirements difficult. 

This paper aims to examine the effects of porosity and permeability changes of the coal seam on methane emissions in an 

underground continuous miner section. The models were developed and executed in a dynamic fashion to simulate an advancing 

section. Through this process, the changes of effective stress in coal, particularly their change paths, on porosity and permeability 

were incorporated into the models and methane emissions, concentrations, air requirements, water inflow and possible leakage 

from the stoppings were investigated using a conventional coalbed methane reservoir model. 

1. INTRODUCTION 

Coalbed methane (CBM) is both a valuable domestic 

energy source in the United States and a safety concern 

in underground coal mines. In 2007, US underground 

coal mine operators reported 73 methane ignitions in 

underground coal mines. In unfortunate situations, these 

ignitions may lead to an explosion and to a major mining 

disaster. Thus, the ability to model methane emissions in 

underground coal mines as realistically as possible 

allows for the optimization of coalbed methane 

degasification systems ahead of mining, appropriate 

design of the mining geometry, and appropriate design 

of the mine and section ventilation systems, providing 

for enhanced safety and productivity. 

There are various parameters involved in coalbed 

methane reservoir modeling that span from depth of 

seam, coal thickness, porosity, permeability, pressure, 

methane content and isotherms. Particularly, the 

influence of in-situ and mining induced stresses on coal 

porosity and permeability during mining cannot be 

underestimated for effective degasification and 

ventilation of coal mines. 

Additionally, mining-induced and the resultant effective 

stress on a coal seam plays an important role in the 

integrity of ventilation controls, such as stoppings, in 

underground mines. Roof and floor convergence will 

usually result in some structural damage to stoppings, 

allowing leakage of air from intake to return and 

reducing the quantity of air at the working face. 

By accounting for the influence of in-situ and mininginduced stress on the reservoir parameters, methane 

emissions in an active continuous mining section can be 

forecasted more accurately. 

2. BACKGROUND 

2.1. Coalbed Methane Emissions and Production 
Methane is formed in coal during the coalification 

process and also as a result of bacterial activity. It is 

stored in coal both as a free gas and an adsorbed gas. 

The free gas and adsorbed gas exist in equilibrium in an 

undisturbed reservoir, but the introduction of a borehole 

or mine entries will disturb this equilibrium and cause 

gas to flow into the open area. Flow occurs both in the 

micropores and in the fracture network or cleat system, 

which comprise of butt (short, discontinuous cleats) and 

face cleats (continuous cleats) [1]. The effects of stress 

on both the micropores and particularly on fracture 

network are important in characterizing the ability of the 

coal to store fluid and to allow gas and water flow. The 

ability of a dual-porosity porous medium storing fluid 

and allowing fluid flow within are directly related to its 

porosity and permeability, respectively, which both are 

dependent on the effective stress level of the coal seam. 

Effective stress can be defined as the resultant stress due 

to in-situ and mining induced stresses collectively, and 

impacts the porosity and permeability of the cleat system 

more than the microporous matrices. 

2.2.	 Coalbed Methane Reservoir Modeling 

Coalbed methane reservoir modeling is necessary, both 

for the design of appropriate mining geometry and 

ventilation and for the design of degasification systems. 

Reservoir simulators require a large number of 

interrelated parameters for model building. Reasonable 

estimation of these parameters is essential in producing a 

realistic simulation. 

Young gives a summary of the minimum data required 

for coalbed methane reservoir modeling [2]: 

	 Reservoir description (geometry, structure, 

depth, thickness, stratification, water saturation, 

and pressure) 

	 Fluid Pressure-Volume-Temperature (PVT) data 

(gas viscosity and composition) 

	 Time dependent well data (fluid flow rates and 

bottom-hole pressures), in other words recurrent 

data. 

Porosity and permeability are important descriptors in 

the characterization of storage and flow of coalbed 

methane. Coalbed methane reservoirs are unique due to 

their pore structure. Pore structures in coal are divided 

into macropores (>50 nm), mesopores (2-50 nm), and 

micropores (<2 nm) [3]. The majority of methane stored 

in a coal seam is adsorbed on to the walls of these 

micropores, while some gas is present as a free gas in the 

fracture, or cleat, network. This network is comprised of 

nearly orthogonal fractures distributed within the seam; 

it stores almost all of the water and plays a critical role 

in gas production and methane emissions due to its 

permeability and porosity. 

2.3.	 The Effects of Stress on a Coalbed Methane 

Reservoir 

Understanding methane emission rates in underground 

mining is critical for the safety and productivity of a 

mine. Various factors control methane emissions during 

mining development, but the initial reservoir parameters 

and the mining parameters are the most important. Coal 

reservoir parameters that are sensitive to mining induced 

stresses and in-situ stresses include permeability and 

porosity. It is essential to consider stress and associated 

changes in porosity and permeability when modeling 

emissions from a coalbed methane reservoir [4]. 

Generally, a decrease in stress in a coal seam will result 

in desorption of gas followed by an increase in 

permeability due to matrix shrinkage and opening of 

cleats [5, 6]. Stress will generally have a more 

significant effect on macropores and on cleats while 

leaving mesopores and micropores less affected [7]. 

This effect changes the permeability of the coal seam, 

since the cleat structure is mainly responsible for 

permeability and its anisotropy. Therefore, gas may 

flow preferentially in one direction due to this structure, 

usually along the face cleats. The spacing and orientation 

of cleats are generally related to the orientation of the 

present or past principal stresses prevailing in the field. 

It is important to note that the relative importance of 

stress with regard to permeability may differ 

significantly in different coal basins, and that coal seam 

composition and fracture also play a significant role. 

However, in general, the anisotropic permeability tends 

to decrease as effective stress increases, indicating that 

high in-situ stress will cause the cleat system to close 

and lower the permeability and porosity of the seam [8]. 

Therefore, a permeability decrease due to either in-situ 

or induced stresses, and a permeability increase due to 

matrix shrinkage may occur concurrently during mining. 

Mining, when commenced, will have the effect of 

redistributing the in-situ stress. As coal is removed the 

existing stress will be transferred to the adjacent in-place 

coal, creating zones of relatively higher stress, referred 

to as abutment stresses. Considered independently, this 

stress will cause a decrease in porosity and permeability. 

3.	 MODELING PROCEDURE 

3.1.	 Reservoir Modeling Approach for Simulating 

Effects of Mining 

The model used for this case study is a three-entry 

continuous miner development section, typically 

practiced by several mines operating in the Northern 

Appalachian basin. The mining geometry is displayed in 

Figure 1. The middle entry was modeled as the track 

entry, intaking air, and the entry to the left of it in the 

advancing direction was designated as the belt entry or a 
 

neutral entry. The third entry was designated as the 

return entry. Mine entries are modeled as boreholes; the 

borehole pressures are adjusted to match ventilation 

pressures found in the entries. Ventilation air input was 

modeled with an injection well, which injected air at a 

constant rate of 37.69 m3

/s (79,861 cfm). This value was 

determined from the pressure loss in the entries and 

allowing the injection pressure to increase to a maximum 

value of 102.4 kPa (14.85 psi). The return and belt 

entries were modeled with production boreholes 

operating at 100.7 kPa (14.60 psi) and 101.0 kPa (14.65 

psi) bottom-hole pressures, respectively. These 

boreholes were used as monitoring points where the 

amount of methane and air in the produced gas stream 

were recorded by the simulator to calculate methane 

inflow. The injected air from the track entry was split 

into two at the face based on the pressure differences in 

the other two entries and the leakage across the 

stoppings, when it occurred. 

 

Mining 

direction 

Fig. 1. A cut-away picture of the model showing entries, 

pillars and mining direction. 

While methane inflow and its percentage in the 

ventilation air are of prime importance, water inflow into 

the mining environment from coal seam may be 

important also. The reservoir model was constructed as a 

two-phase flow model where water is mobilized as a 

result of effective stress reduction in the fractures 

following a relative permeability curve that was chosen 

and used for history matching in earlier studies [9]. 

Similarly, entries were assigned relative permeability 

values which would maximize gas flow while enabling 

water movement towards the monitoring points to 

quantify water inflow. 

Both mining and ventilation are dynamic processes in 

nature, resulting in varying ventilation requirements 

based on changes in operating conditions. As the 

continuous miner advances, a new space must be 

ventilated, and new surfaces that liberate gas into that 

space are created. In terms of modeling, this situation is 

a moving-boundary-value problem. In this study, 

development of a three-entry continuous mining model 

was handled using “restart” model runs. These models 

were run sequentially, each characterizing an advance in 

entry development with a specified development rate, 

during which coal bed properties were replaced with the 

assigned properties of entries in the models. Each restart 

run was performed in such a way that entries would 

progress based on a rate of 15.2 m/day (~50 ft/day) that 

was scheduled in the recurrent data set. As the threeentry system was developed at the designated rates in the 

models by changing coalbed properties, the crosscuts 

were also developed at the same time. The resulting 

pillars were 38.1 m (125 ft) in length, 22.9 m (75.1 ft) in 

width and had the same properties as the coalbed. 

Entries and crosscuts were modeled as 7.62 m (25 ft) 

wide and 1.83 m (6 ft) in height. During development of 

crosscuts, two stoppings (between track-belt and trackreturn) were automatically created in the open crosscut 

of the previous restart run so that during each simulation 

the ventilation flow would always be circulated from the 

last open crosscuts. A relatively low permeability value 

of 98.7 μm2

 (100 darcies) was assigned to the 

undamaged stoppings to represent the minimum leakage, 

where 98,700 μm2 (100,000 darcies) was used to 

simulate stress-related damage to stoppings in the model 

runs. These values were selected based on Bear [10] and 

correspond to lower and upper permeability ends of 

highly fractured rock material [10]. The formulation of 

this model was similar to the earlier work detailed by 

Karacan [9]. The initial properties of the coal seam prior 

to effective-stress-reduction induced changes are given 

in Table 1. 

Table 1. Initial coalbed properties used in simulation of 

development mining. 

Parameter Values 

Coalbed thickness 1.83 m (6 ft) 

Coalbed pressure 2758 kPa (400 psi) 

Sorption time 50 days 

Permeability anisotropy (Kx/Ky) 4 

Face cleat permeability (Kx ) 0.00987 μm2

 (10 md) 

Butt cleat permeability (Ky) 0.00247 μm2

 (2.5 md) 

Langmuir volume 13.6 m3

/ton (490 scf/ton) 

Langmuir pressure 2248 kPa (326 psi) 

Initial water saturation (Swi) 60% 

Effective porosity 5% 

Irreducible water saturation (Swir) 10% 

Relative permeability to gas (Krg) 

at Sg= 1-Swirr 

0.35 

3.2. Implementation of Stress Induced Changes 

Various factors control the methane emission rates 

during mining; the most important are the mining 

parameters and coalbed parameters [9]. As mining 
proceeds, the coal seam and the overlying strata are 

exposed to mining induced stress. These stresses may 

cause some deformation in the pillars and the ribs of the 

coal seam, as well as convergence of the roof and floor. 

The stresses in the ribs and pillars of the roadways result 

in deviations in the original permeability and porosity of 

the coal seam. These deviations eventually result in 

changes in methane and water inflow into the roadways 

that must be controlled with proper ventilation and 

pumping. Additionally, roof and floor convergence may 

result in damage to stoppings, causing intake ventilation 

air to leak to the return entries, reducing the volume of 

fresh air that can be utilized at the face. In this study, 

convergence was neglected due to the model limitations; 

however, its effect on stoppings was represented by 

increasing the stopping permeability three orders of 

magnitude from an original permeability of 98.7 μm2 

(100 darcies) to 98,700 μm2 (100,000 darcies). These 

numbers are consistent with permeability values of 0.1 

μm2

 to 100 μm2 for undamaged cinderblocks in the 

literature [11] and those of highly fractured rock masses 

given in [10]. 

Griffith’s crack theory was utilized to model changes in 

permeability at the entry boundaries due to mininginduced stress [12]. This theory describes an elliptical 

crack, which represents the mine opening in this case, 

and the stresses at its edges, which may represent the 

stresses occurring in pillars and in the ribs extending into 

the coal seam [13]. According to this theory, the vertical 

stress distribution along the edge of the opening is given 

by: 

 yy  P coth(e) (1)

where e  cosh1

x c (2)

 yy : The vertical stress in the rib 

P : Stress at infinity perpendicular to the crack, 

generally related to the overburden stress 

x : Distance into the rib 

c : Half the crack width, half the entry width in this 

case. 

It has been postulated previously by Hoch et al. [14] that 

the  xx curve had the same shape as the  yy ; however, 

it was a fraction less in magnitude. This fraction amount 

could be approximated by the expression: 

 xx   yy (3)

Where: 

 xx : horizontal stress 

 yy : vertical stress 

 : Poisson’s ratio, approximately 0.25 for coal. 

A simple elastic behavior concept was used to 

implement the stress level during extension of the 

opening. In addition, desorption of gas, and drainage of 

gas and water from coal cleats into the entries result in 

changes in pore pressure, which couple with mechanical 

stresses and cause compaction of coal, thus changes in 

fluid flow related properties, in relation to the porepressure stress path. For these cases, four different stress 

paths (SP), or elastic response curves of the coal 

material to a given pressure, were defined to change 

permeability and porosity of the coal seam in accordance 

with changes in the pressure for pillars and the ribs 

around the openings. Figure 2 illustrates the four cases 

and the resulting changes in porosity and permeability, 

as calculated in comparison with the initial values after 

mining induced stresses are incurred. 

 

0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

0 50 100 150 200 250 300 350 400 450 

Pressure (psi) 

Permeability (k/ko) 

0.7 

0.8 

0.9 

1 

Porosity (Ø/Øo) 

SP1-Perm 

SP2-Perm 

SP3-Perm 

SP4-Perm 

SP1-Por 

SP2-Por 

SP3-Por 

SP4-Por 

Fig. 2. Permeability and porosity change curves for different 

stress paths during entry development. 

 In these cases, 

SP1 was considered the base stress path, where a 

stopping permeability value of 98,700 μm2 (100,000 

darcies) is also used, in addition to 98.7 μm2 (100 

darcies) for comparison of a damaged stopping with 

undamaged one. Damage to the stoppings was reflected 

in their permeability values, which was not a function of 

pressure; therefore all the damaged stoppings had 

permeability values of 98,700 μm2 (100,000 darcies) in 

the model. 

For porosity-dependent permeability changes, the 

following relation was used [15]: 

k   

3 

   (4)   k o o 

In Figure 2, all starting and end point values for different 

SPs in porosity and permeability were set to the same 

values. Thus, the effect of end points was eliminated and 

just the effect of SP change in elastic region was 

considered. 
4. RESULTS AND DISCUSSION 

Figure 3 displays samples from model runs. These 

pictures represent the last 137 m (449.5 ft) of 

development.

 

Fig 3. Reservoir pressure contours (A) and porosity contours 

(B) for the last 137 m (450 ft) of development. Mining is 

advancing towards right side of the figures. Color legends are 

and the values are in pressure units, psia. 

 A total of 518 m (1,700 ft) of development 

was modeled in this work. Figure 3A shows the pressure 

contours while 3B shows the effective porosity contours 

at the corresponding time step. In both figures, the 

arrows show the direction and magnitude of water 

velocity scaled by the logarithm in order to be able to 

show low and high values in the same figures. These 

figures illustrate that the velocity of water is highest at 

the headings where there are sudden drops in pore 

pressure and it declines around the entries and in the 

pillars. Conversely, porosity and the related permeability 

parameter reach the lowest values in the pillars and in 

the ribs. There is a high porosity and permeability zone 

ahead of the entries that result from the transient increase 

in pore pressure in this zone. 

The results of the simulations for different stress paths 

(SP) were evaluated for their effects on methane and 

water inflow into the entries. Figure 4 shows the daily 

methane inflow rates into the belt and return entries (A) 

and the daily cumulative emissions from these two 

entries (B) while a constant air injection rate of 37.69 

m3

/s (79,861 cfm) has been provided from the middle 

(track) entry.

150.00 

200.00 

250.00 

300.00 

350.00 

400.00 

450.00 

500.00 

550.00 

0 200 400 600 800 1000 1200 1400 1600 1800 

Linear Entry Advance (ft) 

Methane Inflow Rate (Mscf/day) 

SP1-Belt SP1-Return 

SP2-Belt SP2-Return 

SP3-Belt SP3-Return 

SP4-Belt SP4-Return 

400.00 

450.00 

500.00 

550.00 

600.00 

650.00 

700.00 

750.00 

800.00 

850.00 

0 500 1000 1500 2000 

Linear Entry Advance (ft) 

Total Methane Inflow Rate (Mscf/day) 

SP1 

SP2 

SP3 

SP4 

Fig. 4. Daily methane inflow rates into the belt and return 

entries (A) and the daily cumulative emission from these two 

entries (B) as a function of development distance and stress 

path results during mining. 

A 

B 

 Figure 4A shows that the highest methane 

emissions were obtained from the return entries when 

SPs of 4, 1, 3 and 2 were followed, respectively. The 

emission level from the belt entry followed the same SP 

trends. This was due to the fact that when SP4 was being 

followed the porosity and permeability of coal in pillars 

and in ribs around the entries followed a gradually 

compacting trend with decreasing pressure, as opposed 

to a sudden compaction and decrease in directional 

permeability that was experienced in SP2. Therefore, 

during mining of the entries, a more gradual compaction 

resulted in a higher gas inflow rate due to a slower 

decrease in absolute and effective permeabilities. On the 

other hand, methane inflow rates were about two times 

higher in the return as compared to the belt entry 

because the pressure was 0.34 kPa (0.05 psia) lower in 

the return entry. The cumulative methane emission rates 

from these two entries were calculated to reach values of 

about 15.7 m3

/min (557 cfm) at the end of 518 m (1,700 

ft) development, when SP4 was followed during mining 

(Figure 4B) 
Figure 5 shows the methane percentages in the 

cumulative ventilation air as measured at the monitoring 

points at return and belt entries as a function of linear 

entry distance and the stress paths given in Figure 2. 

 

0.40 

0.60 

0.80 

0 200 400 600 800 1000 1200 1400 1600 1800 

Linear Entry Advance (ft) 

Methane in the Ventilation Air (%) 

SP1 

SP2 

SP3 

SP4 

Fig. 5. Methane percentages in the cumulative ventilation air 

as measured at the monitoring points in return and belt entries 

as a function of linear entry distance and the stress paths given 

in Figure 2. 

This figure shows that the methane percentage increased 

in the ventilation air in accordance with the methane 

inflow rates as developed distance increased. In all SP 

conditions the ultimate methane percentage at 518 m 

(1,700 ft) is <1%, which is the statuatory limit. 

However, as discussed before, the methane content in 

the air increased more when the compaction of the coal 

did not occur abruptly as a result of decrease in coal 

seam pressure as mining continued. From these data, it 

appears that for longer linear developments the 

percentage of methane in ventilation air may exceed the 

1% limit, especially in the SP4 case. 

From Figure 5 it is also evident that a sudden 

compaction of the coal with small decreases in pressure 

during mining, the case in SP2, may be desirable since 

this will result in less methane inflow. 

The reservoir model was developed with two-phase flow 

formulation; water was also flowing in the coalbed due 

to changes in stress variations and effective permeability 

to water during mining. In some situations, water inflow 

into the mine may be high enough to require pumping. 

In this study, the results of water inflow into entries 

associated with changes in SP during mining were 

determined and the data are displayed in Figure 6. 

 

40.00 

50.00 

60.00 

70.00 

80.00 

0 200 400 600 800 1000 1200 1400 1600 1800 

Linear Entry Advance (ft) 

Water Inflow Rate (bbl/day) 

SP1-Belt SP1-Return 

SP2-Belt SP2-Return 

SP3-Belt SP3-Return 

SP4-Belt SP4-Return 

120.00 

125.00 

130.00 

135.00 

140.00 

0 200 400 600 800 1000 1200 1400 1600 1800 

Linear Entry Advance (ft) 

Total Water Inflow Rate (bblday)

SP1 

SP2 

SP3 

SP4 

Fig. 6. Daily water inflow rates into the belt and return entries 

(A) and the daily cumulative water production from these two 

entries (B) as a function of development distance and stress 

path results during mining (bbl: barrels). 

A 

B 

Figure 

6-A shows the difference in water inflow into return and 

belt entries, as well as the effect of SP. More water was 

measured in the return entry, about 11.9 m3

/day (75 

bbl/day). The rate in the belt entry was approximately 

8.74 m3

/day (55 bbl/day). The values did exhibit an 

increasing trend with advance distance, similar to 

observations for methane in Figures 4 and 5. As 

expected, water control in longer developments is less of 

an issue than methane control. However, more 

importantly, the water inflow trend is opposite of the 

methane inflow trend with respect to SPs. This is due to 

two mechanisms that occur simultaneously in this 

model. Normally, in a coal seam reservoir free of any 

major compaction due to mechanical effects, or similar 

sorptive tight gas reservoirs, most gas resides in 

micropores, and most water resides in cleats or fractures. 

In these reservoirs, gas is released from the microporous 

matrix as water removal causing the pore pressure to 

drop. Thus, the faster the pressure drops, the more gas 

desorbs from coal and diffuses into the cleats, where 

eventually the relative permeability to gas increases and 

the gas rate increases at the expense of water rate, which 

initially was higher. In this model, since fractures 

deform continuously as well with the stress changes, 

water residing in fractures has been forced out of the 

pillars and ribs. So, as a result of the combined effect of 

compaction of fractures and coal matrix, water rate 

increased when compaction occurred abrubtly, opposite 

of what was observed in the methane inflow case. The 

cumulative water flow rate from return and belt entries 

was approximately 21.5 m3

/day (135 bbl/day) when the 

development distance was 518 m (1,700 ft). 
The discussion thus far has included examination of how 

changes in SP with mining affect methane and water 

inflow. In these cases, all stoppings were given 

permeability values of 98.7 μm2

 (100 darcies). In other 

words, all stoppings were considered undamaged. A 

model case was created to compare the effect of 

permeability of stoppings by using the stress path SP1. 

In this case, the stoppings were assigned a permeability 

of 98,700 μm2

 (100,000 darcies), which was considered 

a damaged stopping for comparison purposes. The main 

effect of this change was expected to be a increase in 

leakage across the stoppings and a increase in the 

ventilation air in return entries, and a consequent 

decrease in belt air rate, which will either be insufficient 

to maintain statutory methane levels as mining continues 

at the face with constant ventilation air capacity, or will 

increase the ventilation costs significantly in order to 

provide desired amount ventilation air at the face for 

effective dilution. The result is displayed in Figures 7 

and 8. 

30000.00 

40000.00 

50000.00 

60000.00 

70000.00 

80000.00 

0 200 400 600 800 1000 1200 1400 1600 1800 

Linear Entry Advance (ft) 

Ventilation Air Rate (Mscf/day) 

SP1-Belt-Without Leakage 

SP1-Return-Without Leakage 

SP1-Belt-With Leakage 

SP1-Return-With Leakage 

Fig. 7. Comparison of two different stopping permeabilities on 

the ventilation air quantity in return and intake entries. 

Fig. 8. Comparison of leakage paths for undamaged (A) and 

damaged (B) stopping permeabilities. Velocity vectors are 

shown in black, mining is from left to right. Denser cross 

entry vectors in B indicate more leakage due to stopping 

damage. 

In Figure 7, the air rates measured in return and belt 

entries as a function of development distance are shown. 

It can be observed that the change in stopping 

permeability resulted in an increase in air quantity in the 

return, and a decrease in air quantity in the intake, as air 

leaked from intake to return. 

CONCLUSIONS 

The results indicate that a gradual change in reservoir 

permeability and porosity (SP4) as a result of mining 

induced stress produces the highest quantity of methane 

emissions, while water production is actually higher with 

a sudden decrease in permeability and porosity (SP2) as 

a result of mining induced stress. This phenomenon is 

most likely due to two mechanisms that occur 

concurrently. Gradual compaction will cause water to 

flow out of fractures, lowering the pore pressure and 

causing gas to desorb from the coal and diffuse into the 

fracture network, eventually increasing the relative 

permeability of the reservoir to gas. However, a sudden 

compaction will force water out too quickly and also 

cause the fracture network to compress, effectively 

lowering the permeability of the reservoir to gas. 

Stopping damage due to mining induced stress was 

modeled by increasing the permeability of the stopping 

to simulate air leakage, and determine the effects of this 

leakage on methane presence in the ventilation air. This 

increase in permeability affected the ventilation air 
quantity, increasing air in the return and decreasing it in 

the belt entry, as expected. Also, stopping leakage 

becomes more significant as a section advances. A 

damaged stopping with a permeability of 98,700 μm2 

(100,000 darcies) was set and applied all the way along 

the section because convergence could not be integrated 

into the reservoir simulator and applied to the stoppings. 

A more realistic approach might be to apply a high 

permeability at the most outby stoppings (farthest from 

the mining face) and gradually reduce stopping 

permeability as they move closer to the face. 

Although a sudden compaction will produce less 

methane to the ventilation air it may also cause further 

damage to stoppings, which will either reduce the 

ventilation air quantity that is available to dilute the 

methane or require higher fan costs to effectively dilute 

the methane. It is evident from these results that the 

effects of mining induced stress on both the reservoir 

properties and the ventilation controls should be 

considered when designing mining geometry (layout?) 

and ventilation in a gassy mine. 

Future research will involve improving the simulation of 

leakage across damaged stoppings as detailed above. 

Additionally, more advanced modeling of mining 

induced stress would also improve the model, most 

likely with software such as FLAC [16]. 

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