Reservoir rock properties of coal measure strata of the Lower Monongahela Group,

Greene County (Southwestern Pennsylvania), from methane control and

production perspectives

C.Özgen Karacan ⁎

CDC/NIOSH Pittsburgh Research Laboratory, Disaster Prevention and Response Branch, 626 Cochrans Mill Road, PO Box 18070, Pittsburgh PA, 15236, United States

⁎ Tel.: +1 412 386 4008; fax: +1 412 386 6595.

E-mail address: cok6@cdc.gov.

abstract

Themethane emission rate into an undergroundmine environment from overburden strata during longwall mining

is impacted by reservoir and geomechanical characteristics of the coal measure rocks in the overlying strata, as well

as the presence of any coal seam. The reservoir characteristics and how they change during mining potentially affect

the performance of gob gas ventholes, which consequently impacts the efficiency of methane control in the mining

environment.

This study presents reservoir and elastic properties of coal measure rocks in the Lower Monongahela Group in

Greene County, southwestern Pennsylvania, of the Northern Appalachian Basin. Since the source of methane in this

region from underground mining is located between the Sewickley coal and the Pittsburgh coal, a specific emphasis

was given to this interval. Core analyses were performed in the laboratory to determine rock porosity and

permeability. Geophysical logging data (gamma, density, sonic) obtained from two exploration boreholes were used

for evaluating formation boundaries, shale contents, log porosities, and geomechanical properties of formations.

Permeability was also calculated using density-log data and empirical equations and compared with laboratory

measurements and slug tests performed in isolated intervals of boreholes. The results presented in this study can be

used as data sources for reservoir studies related to the production and control of methane.

1. Introduction

Methane inflow into mines from overburden strata during longwall

mining and the production potentials of the surface methane degasification systems, mainly gob gas ventholes (GGV), are impacted by reservoir

and geomechanical characteristics of the overlying strata. Core analyses

and geophysical logging techniques are two of the important data sources

for characterizing the geological formations. Determinations of reservoir

and strength properties of the formations are important since they affect

fluid flow and storage in the overburden before and after coal extraction as

the stress and strain states change as a result of longwall operations.

Available coalbed methane (CBM) production literature often provides

more detail on the reservoir and mechanical properties of the coal bed

than on the properties of the adjacent coal measure rocks. For instance,

Vaziri et al. (1997) discuss a back analysis method for strength properties

of the coal seam from field measurements of wellbore cavitations and

methane production. Deisman et al. (2008) give results of some

unconventional geomechanical testing for coal bed reservoir well design

for the Alberta foothills and plains. Beamish and Crosdale (1998) describe

the relationship between coal strength and coal composition and their

effects on outburst potential. Simulation studies for CBM production and

coal seam degasification also are concerned mainly with the properties of

the coal bed (King et al., 1986; Remner et al., 1986; Diamond et al., 1989;

King and Ertekin, 1994).

Despite their lack of attention in the literature, the reservoir and

strength properties of coal measure rocks are as important as the mined

coal seam itself, since their properties determine gas flow paths.

Lunarzewski (1998) and Noack (1998) emphasized that the influence of

the deformation processes on the mechanical properties of the rock mass

occurs in a micro to macro scale. During mining-induced deformations,

existing and mining-induced fractures may open further. The generation

and propagation of the fractures depend on the type and composition of

the rocks overlying the seam. Mining processes can thus create sudden

and unstable gas releases leading to potentially dangerous underground

conditions which must be prevented by using a properly designed

ventilation system or by employing gob gas ventholes effectively. For

instance,Whittles et al. (2006) reported the results of a simulation study to

predict the source and flow path of methane emissions in a UK longwall.

They concluded that the geology of coal measure strata is important to

determine the caving and control of methane. Palchik (2003) conducted a

series of field measurements in gob gas ventholes in Torezko-Snezhnyanskaya (Ukraine) longwall mines to determine the formation of

fractured zones during mining. His study showed that the location of
fractures and gas emissions are closely related to the geology of coal

measure rocks and their distances from mining activity.

In addition to the overall reservoir and strength properties, the types

and thicknesses of coal measure rocks at the roof of a mined coal seam

cause borehole stability problems during mining. Whittles et al. (2007)

described the application of a computational model (FLAC2D) to simulate

the geomechanical disturbances created due to the mining of a longwall

panel at the Thoresby mine, Nottinghamshire, UK. The roof geology was

considered a significant feature because it was known from previous

experience that the amount of roof movement within the roadway in the

region behind the coal face greatly influenced the stability and hence the

gas drainage efficiency of the boreholes. An analysis of the simulation

results provided a method of quantifying the effects of the geological

conditions on determination of the optimum borehole spacing for the

different regions of the panel.

Gas emissions and the design and stability of gob gas ventholes depend

on the reservoir rock properties, the types and thickness of different layers,

and the degree of their deformation dictated by their rock-strength

properties. The knowledge of these rock properties is important for

predicting gas emissions, sudden gas releases and changes in emission

rates, as well as designing surface methane control systems. Thus,

laboratory analyses of available core materials from boreholes and

accurate borehole logs of coal measure rocks are important for any

emission prediction and gob gas venthole design method.

This paper presents analyses on coal measure rocks recovered from the

Lower Monongahela Group from exploration boreholes drilled in Greene

County, Southwestern Pennsylvania (Fig.1). Gamma ray, density, and sonic

log analyses are presented to determine formation boundaries, in-situ

porosities, existing fractures, and geomechanical properties (shear,

Young's, and bulk moduli, and Poisson's ratio). Permeabilities calculated

using log data and empirical relationships are also presented and

compared with laboratory measurements and slug test permeabilities.

The results of this paper are intended to serve as basic properties of coal

measure rocks for site evaluations, gob gas venthole designs, and for

development of numerical models for reservoir or geomechanical

simulations.

Fig. 1. Appalachian Basin and location of study area in Greene County.

2. Southwestern Pennsylvania section of the Northern

A

2.1. Methane sources and production potentials

The Appalachian Basin is one of the most important coal basins in the

U.S. and the world's second largest coal bed methane (CBM) producing

basin (Lyons, 1998). The northern part of this basin, trending in the

northeast–southwest direction and occupying portions of five states

(Pennsylvania, West Virginia, Ohio, Kentucky, and Maryland), is called the

Northern Appalachian Basin (Fig. 1). The basin is bounded by a graben

structure at the southern margins.

The Northern Appalachian Basin in southwestern Pennsylvania is a

very important area for coal mining, for CBM production from coal bed

degasification boreholes, and for mining-related methane (from gob and

from ventilation system) emission and capture. Markowski (1998)

reported that there are 24 coalbed methane pools in Pennsylvania and

11 of these 24 are located in Greene County, Pennsylvania. The main coal

beds in this area are the Pittsburgh, Sewickley, and Waynesburg. Premining degasification wells in this area have penetrated the Washington,

Waynesburg, Uniontown, and Pittsburgh coal beds, as well as others in the

Conemaugh Group (Markowski, 1998). Flows from these wells vary up to

2.8 Mm3

/day, mainly after hydraulic fracture treatment of the Pittsburgh

coal seam interval. Coal mining companies are also becoming interested in

converting GGVs into methane production boreholes, a practice not

previously economical due to air contamination of the gob gas by the

mine's ventilation system. However, with optimum drilling designed for

the overlying strata and using pressure swing adsorption or a molecular

gate system, gob gas can be converted economically to pipeline quality gas.

For a detailed analysis and discussion on coalbed and coal mine

methane resource and production potential of the Northern Appalachian

Basin, please refer to Kelafant et al. (1988), Lyons (1998), and Markowski

(1998).

2.2. Coal measures of the Monongahela Group in Greene County

Greene County, located at the southwest corner of Pennsylvania

(Fig. 2), is remarkable for having many productive underground coal

mines. A great flat-to-dome shape of this county between two major

rivers (Monongahela and Ohio) is underlain by almost perfectly flat coal

seams and coal measure rocks, most of which are located in the

Monongahela Group.

The Monongahela Group is located within the Pennsylvanian age

sediments and includes the interval from the base of the Pittsburgh

coal to the top of the Waynesburg coal. Deposition of the Monongahela Group was primarily in lacustrine and swamp environments.

The Monongahela Group has a maximum thickness of about 122 m

and a minimum thickness of about 76 m along the Ohio River at the

southwestern edge of the basin.

Fig. 3 shows lithological logs obtained from a series of boreholes

(I–VII) located along the X–Y section shown in Fig. 2. This figure also

ppalachian Basin
shows the lithological logs of the two boreholes (EB-1 and 2) studied

in this paper in appropriate places in relation to the X–Y section. The

general coal measures in the Monongahela Group in Greene County

shown in Fig. 3, and their thicknesses from top to bottom of the group,

can be listed as: shale (0 to 3.6 m), Waynesburg main coal bed (1.8 m),

clay (0.9 m), sandstone (6 m), limestone (1.5 m), sandstone and shale

(18.3 m), Uniontown coal bed (0.3 to 0.9 m), Upper Great limestone

(5.4 m), sandstone and shale (18.3 m), Lower Great limestone

(16.8 m), sandy shale (12.2 m), Sewickley coal bed (0.3 to 18.3 m),

sandstone (3 m), the Fishpot limestone (5.4 m), sandstone and shale

(7.62 m), Redstone coal bed (0.3 to 1.2 m), limestone (3 m), Pittsburgh

upper sandstone (12 m), shale (0 to 3 m), and Pittsburgh coal bed (1.5

to 3.7 m) (Penn State University Libraries, 2000).

Fig. 2. Locations of Greene County and Waynesburg. Map also shows the section and locations of lithological logs shown in Fig. 3. EB-1 and EB-2 are approximate locations of the

studied boreholes in this paper.

Fig. 3 also shows that there are three main coal groups in the

Monongahela Group of coal measures: Pittsburgh group of coals,

Sewickley group of coals, and Waynesburg group of coals. The

Pittsburgh group coals consists of the Pittsburgh coal, the Pittsburgh

Rider, which is usually located 0.3–0.9 m above the Pittsburgh main

coal, and the Redstone coal. The Pittsburgh coals are deepest in the

center of the basin, occurring at 366 m. The group is generally

persistent and consistently thick, averaging 1.8–2.4 m thick (Ruppert

et al., 1999). Overlying the Pittsburgh coal by 6.1–15.2 m is the

Redstone coal, which is not as extensive as the Pittsburgh. In general,

the Redstone coal is 0.3–0.9 m thick when present.

The Sewickley group coals include the Sewickley coal itself and any

riders and splits of the main bench when it occurs. The group

underlies 20,700 km2

. Sewickley coals, which are deeper than 122 m,

occupy an area of approximately 10,100 km2

. The deepest Sewickley

coals are found in SW Pennsylvania at a depth of nearly 366 m. The

Sewickley coal is laterally persistent and generally 0.3–0.9 m thick,

although thicknesses of nearly 1.83 m were measured. Overall

thicknesses for the coals show that the depositional center was

located in SW Pennsylvania.

The Waynesburg Group coals are made up of the Waynesburg coal,

the Waynesburg A coal, and the Waynesburg B coal. The Waynesburg

is laterally persistent and is usually multiple bedded. The Waynesburg

has the most limited area with about 18,100 km2

. They reach a

maximum depth of approximately 244 m in the deepest portion of the

basin.

3. Borehole locations, data sources, and evaluation methodology

For a preliminary characterization of reservoir properties of coal

measure rocks, multiple data sources from two exploration boreholes

(EB-1 and EB-2) were used. These two boreholes were drilled in two

different mining areas in Greene County and were approximately

8 km from each other. EB-1 was northwest of Waynesburg and

borehole EB-2 was southeast of the town (Fig. 2).

The boreholes were drilled to characterize the mine roof strata and

the mining coal thickness at these locations. They were drilled from

surface until the bottom of the Pittsburgh coalbed was reached and

exceeded by about 9.1 m. Recovered cores were marked for depths and

lithology identification. The total depths of EB-2 and EB-1 were 245 m

(at the location, the top of the Pittsburgh seam was 252 m from the

surface) and 263 m feet, respectively. After completion of drilling, both

boreholes were logged with gamma and density tools for the entire

length of the borehole, and EB-2 was logged with a full-wave sonic

tool in addition to gamma and density. Table 1 shows the type of data

sources and the samples obtained from each borehole.

4. Evaluation methodology for coal measure strata

4.1. Handling drill cores and laboratory core analysis

Cores from an entire interval within the Sewickley limestone and

Pittsburgh sandstone (204–247 m at EB-1 location) that corresponds

to the Lower Monongahela Group of coal measures were obtained

during exploration borehole drilling. This interval is important for

mining and methane control because it remains in the “fractured

zone” during mining of the longwall panels in the area. This interval is
considered to be the source of strata gas and the location of the highpermeability fracture network for migrating methane (Karacan et al.,

2007). GGVs are drilled and completed with slotted sections in this

interval for capturing methane before it enters the mine environment.

Table 1

Data availability from EB-1 and EB-2 boreholes

Driller's log Drill cores Core plugs Gamma ray Density log Full wave

sonic

EB-1 ☺ ☺☺ ☺ ☺ ☻

EB-2 ☺ na na ☺ ☺☺

☺: Data measured/available; ☻- EB-1 has not been logged by sonic techniques. However

a pseudo-sonic log was created using fractal statistics and radial basis functions

(Karacan, 2008). Derived rock strength parameters using this approach are presented in

this study. na: Cores not available.

Fig. 3. Lithological logs (modified from Kelafant et al. (1988)) of the boreholes drilled in Greene County along X–Y section shown in Fig. 2. Major layers are indicated on the figure.

Lithologic sections of EB-1 and 2 are also shown in appropriate places according to Fig. 2.

Recovered cores were preserved in 7.6-cm diameter plastic sleeves

after photographing and documenting the intervals to prevent

dehydration and fragmentation. Preserved cores from EB-1 were

later cored as plugs in the laboratory and analyzed for primary

porosity and permeability. Core plug locations for sample preparation

and for measurements were selected based on the integrity of the

samples and on the presence of any fracturing that could create paths

for methane flow into the mine environment and to the operating gob

gas ventholes. A total of 23 core plugs (2.54 cm in diameter) were

prepared from the drill cores. Core plugs were taken horizontal to the

bedding planes, thus parallel to the natural flow direction. It was not

possible to recover more plugs due to separation of rocks at fissures

and formation boundaries. In fact, only 15 core plugs remained intact

for further measurements of porosity and permeability.

Core plugs were dried in a low-temperature analytical oven and

dimensions were measured. The grain volumes of plugs were

determined using a helium porosimeter. This method yields effective

matrix and micro-fracture porosity of samples.

After porosity measurements, both the core plugs and the drill

cores were taken to the WV Geological and Economic Survey

laboratories to measure permeabilities using a micro permeability

device. Permeability readings were taken from various locations on

the cores and core plugs. Micro permeability measurements were

taken at eleven locations and some measurements were repeated for

duplication purposes and to verify accuracy.

In order to characterize small-scale heterogeneities within the core

plugs, they were scanned with a medical X-ray CT scanner modified
for petrophysical studies at the DOE-NETL Morgantown facility. Core

plugs were scanned with a 1-mm beam thickness along their entire

lengths. Thus, each core had 30–40 images taken at 120 KeV with

water-phantom calibration. These images were evaluated visually and

by determining the average CT number and its statistics within a

circular region of interest.

4.2. Evaluation of gamma ray (GR) logs for formation boundaries and

shale volume

The GR is a record of a formation's radioactivity. The GR is usually

used to identify boundaries, primarily shale units from other lower

radioactivity formations (limestones, sandstones and dolomites) and

to quantify shale volume. In fractured formations, an increase in the

gamma ray reading without concurrently higher formation shaliness

can be observed. This increase has been explained by deposition of

uranium salts along the discontinuity surfaces of a fracture or within

the crack itself. Also, it is not uncommon to find as much as 0.01%

uranium or thorium in dark bituminous shale units, which increases

the gamma ray reading (Dresser Atlas, 1974).

Fig. 4-I shows the GR log received from the EB-2 borehole, as an

example, that was used to calculate shale volume.

The following equation can be used to quantify the shale volume

by using GR log (Schlumberger, 1991):

GR Vsh = l−GRclean rock : GRshale−GRclean rock

ð1Þ

Fig. 4. Example gamma (I), density (II), and full waveform sonic (III) data obtained from EB-2 borehole. In III, “P” indicates the arrival of the compression wave to the near

detector. M–N profile is the depth where the waveform shown in Fig. 5, from the near detector, was recorded.

In this equation, GRl is the gamma ray reading (cps—count per

second) from the log. The other two terms are the GR readings of the

clean formations (clean sandstone and limestone) and the pure shale.

For calculating shale volume, the types of the formations and their

thicknesses were first identified from the GR logs of boreholes EB-1
and EB-2. The clean-formation readings of the tool were determined

by locating the clean sandstone and limestone units in the log.

Pittsburgh sandstone and limestone intervals were deemed suitable

for this purpose. For the shale reading, the average reading of the shale

intervals was determined and used in the calculation (Table 2).

In shale volume calculations, each interval was calculated

separately using the respective clean-formation reading. The aim

was to minimize errors from using a single formation GR value for the

entire interval.

4.3. Evaluation of density log (DL) for porosity calculation

High-energy gamma rays from a natural radioactive material are

directed at the formation to interact with the rock material to measure

bulk density of the formation (Schlumberger, 1991). Fig. 4-II shows the

density log along with resistivity log for the EB-2 borehole that was

used to calculate bulk density. Once the bulk density (ρb) is

determined, one can calculate the porosity. However, before porosity

can be determined, the lithology of the formation, the matrix density,

and the fluid density filling the pore space must be known. For a clean

formation of known matrix density, ρma, with a fluid of average

density, ρf, the linear sum of the contributions can be used to calculate

porosity (φ):

ρb = ρf + 1ð Þ −ρma: ð2Þ

There are a variety of factors affecting bulk density measurements.

One of the most important ones is the shaliness of the formation. This

affects the measurement by the amount of its contribution to the total

signal. A correction should be made to density by the volume of shale

(Vshale) to obtain a shale-corrected density measurement, as follows:

ρb = ρbsh:free ð Þ 1−Vshale + ρshaleVshale: ð3Þ

In Eqs. (2) and (3), and throughout the calculation of porosity, the

density values listed in Table 3 were used for individual strata

intervals to minimize the errors that may arise from using a single

density value for the entire interval. Shale volume is determined from

the GR log.

4.4. Calculation of Young's, shear, and bulk moduli, Poisson's ratio,

porosity from sonic log (SL)

Borehole EB-2 was also logged with the full wave sonic tool. The

full wave sonic signature of this borehole received by the near detector

within 201–241 m (660–790 ft) depth is shown in Fig. 4-III. In sonic

logging, ultrasonic frequencies that create particle motions in

different directions in and around the borehole are employed.

A full wave sonic tool generates three types of waves in the

formation and in the borehole. In the case of a compressional wave,

the acoustic wave alternately compresses the surrounding medium on

a forward movement and rarifies it on a backward movement. The

shear wave is a transverse wave in which the direction of propagation

is perpendicular to the direction of particle displacement. Solids have

a tendency to oppose shearing forces which cause particles to slide

relative to each other. Shear waves cannot travel through them. On the

other hand, the Stoneley wave is a type of large-amplitude surface

wave generated by a sonic tool in a borehole. Stoneley waves can

propagate along the walls of a fluid-filled borehole. When the

borehole crosses permeable zones or fractures, some fluid movement

occurs between these locations and the borehole. This results in some

energy loss of the wave (Endo, 2006). Thus, analysis of Stoneley waves

can define the locations of fractures and estimate the permeability of

the formation.

Fig. 4-III displays the full waveform, transit time, and amplitude

received at the near detector for EB-2 within 201–241 m. In the

receiver, the P waves arrive first, the shear wave arrives next, and the

tube wave traveling up the borehole water column arrives third. Shear

wave and tube wave (Stoneley wave) transit times can be determined

by analyzing each of the individual wave forms for second and third

arrivals. Long transit times for the first break, compressional wave (P

wave) arrivals, indicate slow formations, while small transit times

indicate fast formations. Only the arrival of the compression wave

shows up in the full waveform clearly (P in Fig. 4-III). The shear and

tube wave arrivals are read from the individual wave forms, 10 of

which were collected for each 30.5 cm of the borehole. Thus, for the

201–241 m interval, 1300 wave forms were analyzed. The full wave

form in Fig. 4-III is a plot of the individual wave forms stacked side by

side, with the peaks as white and the troughs as black. A sample

individual waveform from the near (along the M–N profile in Fig. 4-III)

and the far detectors is given in Fig. 5. In this figure, the intervals show

where compression, shear, and tube waves arrive at a particular depth.

Acoustic travel time measurements of subsurface formations can

be interpreted in terms of formation porosity. A unit volume of rock

through which the acoustic wave travels is influenced by the total

make-up of that rock. The measurement recorded on the log is the

sum of the effects of the solid part of the rock and the fluid-filled pore

space.

In this study, the following relationships were used to calculate

porosity of the formations with shale correction:

Δt−Δt = matrix Δt −V sh−Δtmatrix

Δtfluid−Δt sh 4 matrix Δtfluid−Δtmatrix

ð Þ

where Δt is the interval travel time of the compressional wave, which

was determined from the full wave sonic record (Figs. 4-III and 5)

based on the first arrival wave, and Vsh is the shale volume obtained

from GR-log analysis (Eq. (1)). Since the compressional wave travels

almost twice the velocity of other waves, its arrival is undistorted by

later arriving waves.

Before using this equation for calculating porosity, it is necessary to

have values for the rock matrix (Δtmatrix) and the formation fluid (Δtfluid).

In this case, the formation fluid was assumed to be water. The interval

transit time in the rock matrix will vary considerably depending on the

formation type. To be more specific, Δtmatrix changes with variations in

the chemical composition of the rock and also its compaction (Castagna

et al.,1985; Bemer et al., 2004). The selection of proper matrix velocity to

be used in the porosity calculation requires knowledge of the lithology of

the sections being investigated. This information was gathered from the

driller's log and the lithological log of EB-2. In Eq. (4), the velocity values

for different strata given in Table 4 were used along with the interval

transit times to calculate sonic porosity.

Besides porosity, velocities obtained from full wave sonic logs

(Fig. 4-III) can be used as the fundamental information for rock

classification and geotechnical evaluation. Acoustic travel time of any

type of ultrasonic disturbance is explicitly tied to the density and the

elasticity of the medium. In this work, shear modulus and Young's

modulus were calculated using the velocities of compressional and

shear waves determined from the sonic log.

Table 3

Bulk density readings for individual minerals

Mixed clay Limestone and

dolomite

Sandstone Coal Water

2.5 2.8 2.65 1.35 1.0

Units are in g/cc.

Table 2

GR readings for isolated formations

Carb. Shale Shale Limestone Sandstone Coal

150 100 5 40 20

Units are in cps.
Compressional waves are characterized by first arrival times.

Although slower than compressional waves (0.5–0.7 times), shear

waves are usually stronger and can be identified in the total wave

train. Both of these waves and the calculated velocities were used in

the following equations for calculation of Young's and shear moduli

(Takahashi et al., 2006).

G = ρV2

s ð5Þ

where ρ is the density, G is shear modulus, and Vs is the shear wave

velocity.

Dynamic Young's modulus was calculated using both compressional and shear waves and a determination of dynamic Poisson's ratio

(σ):

( )   V 2

σ = p −2 V = V 2 p

s

( )  2

−2 Vsð6Þ

where Vp and Vs are the compressional and the shear wave velocities.

Young's modulus (E) can thus be calculated using

E = 2Gð Þ 1 + σ : ð7Þ

Using Eqs. (6) and (7), the bulk modulus (K) can be calculated using

Eq. (8):

E K = : 3 1ð Þ −2σ ð8Þ

Fig. 5. Example sonic waveforms recorded at the near and far detectors during logging of EB-2 at 204 m depth (M–N profile in 4-III). Figure also marks the arrivals of three different

waves to these detectors.

5. Results and discussion

5.1. Borehole cores, porosity, and permeability from laboratory measurements

The core pictures at various depths of EB-1 show the heterogeneity of

the strata in terms of layering and coal measure rock types (Fig. 6a–t).

Green and gray shales are abundant in large intervals and occasionally

mixed with sandstones, probably decreasing their strength and

reservoir quality in these intervals. Shale layers are extensively fractured

(some of them due to drilling and coring) and usually separated at the

interfaces from stronger units. When present, limestone appears to be

relatively free of shale and forms a consistent and strong layer. There are

no apparent pores or macro-scale primary porosity systems in the

interval. However, cores show frequent fractures, most of which are

parallel to the bedding and occur at formation boundaries.

Table 5 shows the results of porosity measurements by helium

porosimeter. The measurements show that some of the core plugs had

minimal porosities between 1 and 2%. A couple of cores taken at

233.8–234.1-m drill depths in the borehole had higher porosities of

~6% and ~11%.

Permeability readings were taken from various locations on the

cores and core plugs. Micro permeability measurements were taken at

eleven locations and some measurements were repeated for duplication purposes and to verify accuracy. The measurements were

performed by forcing the measurement probe to the rock surface

under unconfined conditions. The measurements were conducted at

laboratory temperature conditions (~25 °C). The results are given in

Table 6 and show that for the core intervals, the measurements

indicated generally low permeabilities, except at 217.3 m and 224.6 m.

These comparably higher values of permeability are attributed to the

hair-like fissures observed on the samples. Since the fissures and

fractures were not included in the samples, it should be mentioned

that the porosity and permeability measurements would represent

Table 4

Formation velocities used in Eq. (4)

Mixed clay Limestone Sandstone Coal Water

328.1 157.5 173.9 295.3 715.2

Units are in μsec/m (Dresser Atlas, 1974).

Fig. 6. Cores recovered from EB-1 during drilling and their recovery depths (in meters). a - limestone with shale, b - green shale, c - limestone with dark shale, d - limestone with

green shale, e - limestone with dark shale, f - limy shale, g - sandstone with gray shale, h - black carbonaceous shale, i - Sewickley coal, j - gray shale with sandstone streaks, k - shale

with sandstone, l - limestone with shale, m - limestone with gray-black shale, n - limestone, o - limestone with shale layer, p - limestone with limy shale, q - sandstone with gray shale, rgreen limy shale, s - limestone, green limy shale, t - green sandy shale, u - sandy shale, v - black shale and sandstone.

rock-matrix values, excluding the effects of fractures on storage and

flow properties of the formations.

After laboratory testing of porosity and permeability, core plugs

were scanned using an X-ray CT scanner. X-ray CT is a non-destructive

technique which detects the attenuation of X-rays passing through an

object, which is dependent on bulk density and effective atomic

number. X-ray attenuation is mapped in Hounsfield units, or in CT

numbers, in each voxel of a CT image of the object. The CT numbers

can be converted to density using a calibration function. If a water

phantom is used, as in this study, the CT number is 0 for water (1 gr/cc)

and −1000 for air (negligible density). The principles of X-ray

attenuation are given in Ketcham and Carlson (2001) and in Karacan

and Mitchell (2003).

In this study, the average and the maximum CT numbers

determined in a circular region of interest were plotted for all the

images taken for each core (Fig. 7). Example images from four

different core plugs in the borehole are also shown in this figure. The

scatter plot shows the heterogeneity in the cores. If the maximum (or

minimum) and the average CT numbers accumulate within a small

range of values, then the rock at that scan location is homogeneous

(e.g., 226.4 and 234.1 m). However, if the values are widely scattered,

then it indicates the existence of heterogeneities within the cores (e.g.,

243.8 m). The plot and the images show that the core plugs have

small-scale heterogeneities (243.8 m, 247.2 m, 248.1 m) that may not

be discernible from visual inspection of borehole cores or from the

analysis of well logs. However, these heterogeneities may affect flow

characteristics within the formation and flow and strength tests

conducted in the laboratory.

5.2. Geophysical log evaluations

Gamma ray and density logs are two of those techniques that are

most frequently used in the field for conventional and unconventional

reservoir evaluation studies. Full wave sonic logs, are more expensive

to run, data-intensive, and more complicated in terms of operation

procedures. However, they provide more detailed information about

the condition of the borehole and surrounding strata, such as

geomechanical parameters and formation permeability (Qobi et al.,

2001; Takahashi et al., 2006; Yan, 2002; Milkereit and Ji, 2005;

Castagna et al., 1985). In this section, gamma ray (GR), density (DL),

and sonic logs from EB-1 and EB-2 were evaluated to determine

porosity, shale volume, and geomechanical properties of the coal

measure rocks.

5.2.1. Strata thickness, lithology and GR and DL readings

DL and GR were used to identify formation boundaries, to calculate

porosities, bulk densities, and shale volumes, and to create lithological

logs of the formations in EB-1 and EB-2. Calculations were based on

the methods described in Sections 4.2 and 4.3 using the raw data

shown in Fig. 4-I and -II. In order to create lithological logs, ALT's

WellCAD v4.2 (Advanced Logic Technologies, 2008, Luxemburg) was

used. In addition, strata thicknesses recorded during drilling were

plotted based on the recovered cores.

Fig. 8 shows the lithological log, thicknesses of major layers

defined from the driller's log, and the values of gamma and density

readings from EB-2. At this location, the top of Pittsburgh coal bed was

at a depth of 252 m. The general sequence between 204 m and 241 m,

which was to remain in the fractured zone during mining above the

Pittsburgh seam layer, was divided into four horizons (dotted lines in

Fig. 8). These zones are mainly alternating sequences of limestone and

shale and sandstones, as concluded from GR and DL. In each of these

zones, thin shale layers (A, C–F) are sandwiched between stronger

limestone or sandstone formations. In this log, the Sewickley coalbed

is located at “B” (low gamma ray, low density) and overlain by

carbonaceous shale (A), which records a high gamma ray reading

accompanied by a decreased density.

GR and DL, as well as lithological logs and strata thicknesses for EB-1,

are shown in Fig. 9. At this location, the Pittsburgh coal bed is found at a

depth of 254 m. A similar sequence of layers, as in EB-2, is also observed

at this location. Limestone layers are separated by shale layers as

annotated on gamma and density logs (A–G). Some of the low density

readings (A⁎ and B⁎) are associated with carbonaceous and limy shales

and with highly porous shale units. At this borehole site, the Sewickley

coal seam is thicker than it is at the EB-2 location. This might influence

the amount of methane that will be experienced once this location is

undermined. Also, this location is missing the thick Pittsburgh

sandstone that overlays the Pittsburgh coal seam. The absence of this

layer may affect the fracturing and the amount of methane associated

with this layer.

5.2.2. Shale content and porosity of formations at EB-1 and EB-2 using

GR and DL

In order to calculate shale volume and porosity using GR and DL,

the types of the formations and their thicknesses were first identified

(Figs. 8 and 9). The clean-formation readings for each rock type were

determined by locating the clean sandstone and limestone units in the

logging data. Pittsburgh sandstone and limestone intervals were

suitable for this purpose, since they were mostly free from shales. The

GR reading for coal was determined based on the average GR reading

along the Sewickley layer. For the shale GR reading, the average

reading of the shale intervals was determined and used in the

calculations (Eq. (1)) given in Section 4. Porosities were calculated

based on a similar procedure given for GR by using DL (bulk density)

with shale corrections given by Eqs. (2) and (3).

Fig. 10 shows the shale contents and porosity values for EB-1. The

calculations show that the lowest shale percentage is found in

limestone-bearing units at depths of 225.5 m, and 230.1–234.7 m,

with an average shale content of 5–10%. Within this interval, there are

layers of weak shale formations at around 229.9 m and 233.5 m. These

and similar layers are potentially weak interfaces to be affected by

stresses during mining and by resulting bedding plane separations.

Table 5

Laboratory porosity measurements on core plugs obtained from EB-1

Number Sample

depth (m)

Length,

cm.

Diameter,

cm.

Bulk

volume,

(cm3

)

Grain

volume,

(cm3

)

Porosity,

fraction

1 226.5 3.8 2.5 18.3 18.0 0.019

2 227.4 3.8 2.5 18.3 18.1 0.011

3 233.5 4.2 2.5 20.2 19.6 0.027

4 233.8 3.5 2.5 16.8 15.9 0.056

5 234.1 3.4 2.5 16.6 14.8 0.111

6 241.7 3.6 2.5 17.5 17.4 0.006

7 241.9 4.0 2.5 19.5 19.4 0.002

8 242.0 3.7 2.5 18.2 18.2 0.001

9 243.8 3.5 2.5 17.0 16.8 0.012

10 247.2 3.8 2.5 18.3 17.9 0.019

11 247.8 3.9 2.5 18.8 18.6 0.013

12 248.1 3.9 2.5 18.9 18.4 0.026
Outside of limestone intervals, the average shale content in the strata

varies from 40 to 50%.

Fig. 7. Sample CT images from core plugs and a plot of average versus maximum CT number determined from the core images. Large symbols are the averages of “average CT

numbers” and “maximum CT number” for each core.

Fig. 10 also shows the porosity values calculated in the EB-1

borehole using the density log. This plot shows that porosity values

are generally low (0–0.1), except for some intervals where values

exceeding 0.5 are observed. These locations are at 210.3 m (A), 217.9 m

(B), 224.0–225.5 m (C–D), 233.1 m (E), 237.8 m (F) and 243.8 m (G), of

which 224 m corresponds to the Sewickley coal bed. These intervals

are generally associated with fractures, laminated layers, and shales

interlayered between limestone units. These high porosities can result

in weak spots in the strata that may fracture and separate, as well as

promote methane flow towards any borehole or the mine environment. These areas may potentially be the reservoirs of free methane

that will flow into a pressure sink once the fracture connection is

established during mining.

Similar observations can be made for EB-2 based on clay content

and density porosity (Fig. 11). In this borehole, average shale content

in sandy-shale layers is around 40%. Higher shale-content areas are

interbedded with a more competent limestone sequence and

Pittsburgh sandstone between 217.9 and 228.6 m and below

236.2 m, respectively. The layer that is almost exclusively shale at

211.8 m is closely associated with thin carbonaceous shale and is

either a clay-filled fracture or a fracture surface that is carrying a high

amount of radioactive ions.

The calculated porosities for EB-2, based on the density log (DL),

indicate that most porosity values are 0.1 or less (Fig. 11). However,

there are higher porosity sections based on the strata. The highest

values are marked from A to H on the figure. They are generally

associated with shale layers, especially where the clay content is high

and possibly where some natural fractures within the strata or along

the bedding interfaces are present. In these sections, porosities were

as high as 0.4–0.5 and, in some instances, even more. These highporosity areas constitute weak spots for strata fracturing that create

high permeability pathways and pockets for free methane.

5.2.3. Porosity evaluation using sonic log (SL)

In order to separate possible natural fractures in the interval of

interest from its primary porosity, the sonic log (SL) of EB-2 was used.

Porosity calculations using sonic log data are discussed in Section 4

and given as Eq. (4). The difference between these two methods for

calculating porosity is due to the nature of the response measured in

the formations: the DL is responsive to all pores of all sizes, including

Table 6

Laboratory permeability measurements on core plugs obtained from EB-1

Number Sample Depth m. Measurement No. Permeability md.

1 212.1 1 0.499

1 212.1 2 0.503

2 217.3 1 2.484

2 217.3 2 2.463

3 220.4 1 0.207

3 220.4 2 0.204

4 224.6 1 6.616

4 224.6 2 6.557

4 224.6 3 6.210

4 224.6 4 6.171

5 226.5 1 0.093

6 227.7 1 0.153

7 233.8 1 0.122

8 234.1 1 0.153

9 234.5 1 0.132

10 247.8 1 0.380

10 247.8 2 0.333

11 248.1 1 0.606

11 248.1 2 0.530

11 248.1 3 0.291
fractures. However, field observations over many years have shown

that the SL is a measure of primary porosity but largely insensitive to

secondary porosity as fractures or vugs. This discrepancy arises from

the sonic tool measuring the transit time by recording the first arrival

waveform which often corresponds to a route in the borehole wall free

of fractures and vugs. Thus, comparing SL porosity to DL porosity or

calculating secondary porosity index (SPI= (φ)DL−(φ)SL) may differentiate primary and secondary porosity (Schlumberger, 1991). In the

SPI equation, (φ)DL and (φ)SL are density log and sonic log porosities,

respectively.

Fig. 8. Lithological log, thicknesses of major layers defined from driller's log, and GR and

DL readings from EB-2.

Fig. 9. GR and DL, as well as lithological log and strata thicknesses for EB-1.

Fig. 12 shows SL porosity and SPI calculated for EB-2. As can be seen

from the SL porosity plot, there is a clear decrease in porosity

compared to DL porosity shown in Fig. 11. The average value of SL

porosity along the entire logged interval is 5.5%, with some lower and

higher local deviations from this average. Particularly, points A–D are

of interest due to higher primary porosities. These points correspond

mainly to strata interfaces and may result from rock gouges in the

fractures since they are picked up by sonic log. On the other hand, the

average of DL porosity (Fig. 11) for the same interval is 0.152. The

difference in average DL and SL porosity is the average of SPI, which

indicates that the interval had approximately 0.1 average secondary

porosity due to major fractures and vugs that the sonic log ignored.

The large deviations from this average (E–J) correspond to limestoneshale and sandstone-shale or -shaly sand interfaces and are most

likely due to open fractures at the interfaces. There are also some

peaks above the average values within layers, which may be due to

fracture networks in those layers.

The existence of these fracture signatures is important due to their

potential role as a source of free methane under reservoir pressure and

also as potential pathways for methane flow within the formation as

the longwall face approaches. They are also important for drilling and

cementing of gob gas ventholes in the area due to their potential for

creating drilling fluid or cement mixture losses into the formation.

5.2.4. Evaluation of sonic logs for geomechanical properties of rock

formations

Young's, shear, and bulk moduli, and Poisson's ratio for EB-2 were

calculated based on the method detailed in Section 4.3. Moduli and

Poisson's ratio properties of borehole strata are shown in Fig. 13. In

order to make geomechanical properties of different strata intervals

more distinctive from each other, the arithmetic averages of the values

within different lithology intervals shown in Fig. 8 were calculated.

Young's modulus is a measure of the stiffness of a material for

deformation. It describes the rock's response to linear strain. Shear
modulus, or modulus of rigidity, describes the deformation of a rock

when it experiences a force parallel to one of its surfaces while its

opposite face experiences an opposing force, i.e. rock's response to

shearing strains.

Fig. 10. Shale content and density porosity log calculated from GR and DL of EB-1.

Fig. 11. Shale content and density porosity calculated from GR and DL of EB-2.

Fig. 13 shows that the highest Young's and shear moduli are

associated with limestone and competent sandstone layers. The values

in these layers are as high as 4 and 9 GPa for shear and Young's moduli,

respectively. When there is a shale layer, sandy or limy shale, or coal,

values decrease abruptly to values as low as 1–2 GPa, indicating weaker

rock units that will be deformed easily when subjected to high stress

and strain conditions that can prevail during mining. These weak layers

and their interfaces with stronger rocks are candidates for easy

fracturing and bedding plane separations that form increased permeability pathways for methane migration, as discussed by Palchik

(2005). It should also be noticed that shear and Young's moduli are also

related to density and gamma ray readings shown in Fig. 8.

The bulk modulus of a substance measures the resistance to

uniform compression under hydrostatic pressure. The reciprocal of

the bulk modulus is the compressibility of the substance. If a rock

material is incompressible or has very little compressibility under

hydrostatic pressure, its bulk modulus will be large and thus

compressibility will be small. Fig. 13 shows that the bulk moduli of

limestone intervals in Fig. 8 have the highest values, indicating their

low compressibility compared to shale and sandy shale layers which

appear to be more compressible under uniform pressure.

Poisson's ratio is the ratio of expansion in one direction of a rock

caused by a contraction at right angles. The Poisson's ratio of most

materials is between 0.0 and 0.5. If the material is showing almost no

Poisson contraction as a response to extension, then the Poisson's

ratio is 0. On the other hand, a perfectly incompressible material

deformed elastically at small strains would have a Poisson's ratio of

0.5. Rocks are subject to Poisson's effect under stress and strain. For

instance, excessive erosion or sedimentation in the overburden can

either create or remove large vertical stresses on a particular rock

layer, under which it will deform in the horizontal direction as a result

of Poisson's effect. This change in strain in the horizontal direction can

affect formation of joints or local stresses in the rock. Fig. 13 shows

that the Poisson's ratio is between 0.1 and 0.3 for the rock layers of

interest. Limestone layers are close to a value of 0.3, whereas

sandstone is 0.25, and sandy shale and shale layers are between 0.15

and 0.2. These data indicate that none of the layers are perfectly

incompressible and will tend to show Poisson effects as a result of

changes in stress in one direction. However, this change will tend to

occur more in shale and sandy shale layers. Since there will be a

discontinuity in this effect in the rock layer interfaces, the likelihood of

developing bedding plane separations and fractures will be higher in

those regions.

A similar analysis was performed for EB-1. However, a sonic log

was not run in this borehole. In order to provide operators, who do not
run sonic log on a regular basis (at least for coal mining purposes) due

to its cost and data-intensive nature, with a simpler way of generating

geomechanical properties, a new methodology was developed using

gamma and density logs (Karacan, 2008). This methodology relied on

the indirect effects of density and shale content of rocks on their

geomechanical properties. The methodology processed gamma and

density logs using Fourier transforms and fractal techniques such as

fractional Gaussian noise (fGn) and fractional Brownian motion (fBm).

These methods determined the similarities in data ordering while

eliminating noise and then used radial basis function (RBF) networks

to calculate the Young's and shear moduli of the formations. Details of

this technique are given in Karacan (2008). The data presented in

Fig. 14 were generated using this technique on the EB-1 borehole's

gamma and density logs and its lithology log shown in Fig. 9.

Fig. 12. Comparison of SL porosity and SPI, and with the lithologic log for the EB-2 site.

Fig. 14 shows that the highest Young's and shear moduli are

associated with limestone layers, as in EB-2. The values in these layers

are as high as 2.5 and 6 GPa for shear and Young's moduli, respectively.

The difference in these values compared to those of EB-2 may be due

to the generally higher shale content and DL porosity observed in this

borehole (Fig. 10) compared to EB-2 (Fig. 11). Shale, sandy shale, limy

shale, carbonaceous shale, or coal have lower Young's and shear

moduli as observed in EB-2, indicating weaker rock units compared to

the intervals abundant in limestones. These weak layers and their

interfaces with hard rocks will be deformed and separated easily at

this location during longwall mining.

Fig. 14 also shows that the bulk moduli have the highest values of

4 GPa in limestone intervals and the lowest values in carbonaceous

shale and coal intervals. Also, these layers, except the Sewickley coal

layer, have a lower Poisson's ratio (0.1–0.15) compared to limestone

layers (0.25). The higher Poisson's ratio calculated for the coal at this

location may be due to lower amounts of shale calculated for this

interval and possibly drilling-induced fractures observed in the coal

layer (Fig. 6-i). Silitonga and Siahaan (2005) reported, based on

experimental and theoretical results, that additional fracturing of a

fluid-filled formation will increase the Poisson's ratio deduced using

the sonic log. This is due to a slight decrease in compressional wave

velocities in additional fractures compared to a significant reduction

in shear wave velocities (Schlumberger, 1991).

5.3. Permeability of coal measure formations

Permeability is a critical parameter for any formation, both for

economically and effectively producing fluids (production of gas, oil,

or water) and for controlling the flow of those fluids to any restricted

environments, such as the underground mining environment. There

are various permeability models in the literature relating log or core

porosity, water saturation, particle size, and log resistivity to

permeability. Some of these models are reviewed in Balan et al.

(1995). Sonic velocities, particularly the dispersion and attenuation of

Stoneley waves, are also used to calculate the permeability of

formations, especially in fractured zones (Qobi et al., 2001; Endo,

2006). This method requires obtaining high-fidelity monopole waveforms at low frequency over a sufficiently wide frequency range

(Norris, 1989; Endo, 2006), necessitating a detailed procedure.

In coal measure formations that may also contain strata methane,

the abundance of shales, clays, and their mixtures with sandstones

and limestones make them different from formations in oil and gas

reservoirs, which contain clean sandstones or fractured limestones. In

coal measure rocks, the lack of primary porosity and abundance of

shales/clays affect both the permeability in these formations and the

sealing of thin fractures upon swelling after hydration (Hatherly et al.,

2005). Each of these is important for methane control during mining.

Core pictures shown in Fig. 6 and laboratory measurements of

porosity and permeability on these cores (Tables 5 and 6) prove that

this is not the case in almost all layers examined within the entire coal

measure interval at the EB-2 location. These pictures and tests show

that the matrix is fine-grained, with very low porosity and permeability values. Thus, possible flow paths can be the existing fractures in

the formation that are observable from the pictures (some of which

may be related to drilling). The possible fractures and intervals that are

amenable for bedding separation and fracturing were evaluated using

log data in the previous sections.

In this study, permeability of the coal measure interval between

the Sewickley and Pittsburgh coal seams was evaluated by two

approaches. The first approach performed slug tests in isolated

intervals in three underground monitoring boreholes drilled at

different depths. These boreholes were 15.2 from each other and

thus virtually drilled in the same formations with similar thicknesses.

The second approach used empirical relationships to determine

permeability for shaly formations (Yan, 2002) and sandstones

(Timur, 1968). Fig. 15 shows a picture from the monitoring site and

the boreholes tested using slug-test approach.

5.3.1. Slug tests in boreholes for calculating permeability

These tests were conducted in three different boreholes drilled at

the EB-2 location shown in Fig. 2. The first borehole was drilled to a

depth of 220 ft and completed with a 9-m slotted casing at the bottom.

The second borehole was drilled to a depth of 230 m and completed

with a 6-m slotted casing. The third and the deepest borehole was the

“EB-2” borehole that is reported in this study. This borehole was

drilled to 245 m. It was logged first and then completed with a 4-m

slotted casing and a 2-m open section at the bottom. The first borehole

tested the Sewickley coal (close to the top of the completion) and its

immediate strata below including sandy shale and part of the
limestone. The second borehole tested a majority of the thick

limestone layer, and EB-2 tested the Pittsburgh sandstone and

overlying sandy shale unit (Fig. 8).

Fig. 13. Young's, shear, and bulk moduli and Poisson's ratio calculated using SL data for EB-2.

After completing the boreholes by casing and cementing, the

boreholes were instrumented with downhole transducers located

close to the top of slotted sections to protect them from any sludge that

might have been at the bottom of the boreholes. The transducer used in

this test was a self-contained data logger and pressure transducer with

a 2.041 MPa (300 psia) rating. The data stored in the transducer could

be uploaded to a computer at the surface through this cable using the

accompanying software. After installing and starting the transducers,

the boreholes were filled with water as quickly as possible to start the

slug tests. The data were recorded and initially downloaded in 15-

second intervals, followed by 30-minute intervals later in the tests. The

tests took approximately 1 week in each borehole.

The data obtained from the slug tests were analyzed using the

Bauwer and Rice (1976) method that is also summarized in Dawson

and Istok (1991). The average permeabilities calculated for the tested

intervals were 2.8 md, 0.11 md, and 0.14 md for the first, second, and

third test borehole (EB-2), respectively. These values are actually close

to the permeabilities obtained from the laboratory tests (Table 6). This

suggests that the slug tests measured permeabilities mainly in the

fracture-free sections of the formations and thus close to the matrix

permeability values.

5.3.2. Permeability calculations using empirical models with well log data

Two models were used to calculate the permeability of different

rock layers using log data. These models were those of Timur (1968)

and the empirical equation proposed by Yan (2002) for a shaly sand

reservoir in the North Sea.

Shale content and porosity are believed to control permeability in

clay-sand formations (Yan, 2002). According to core analysis of

permeability, porosity, and shale content determination in the

laboratory and calibrating these data with log responses, Yan

proposed the following empirical equation for permeability of shalysand formations:

b k = a×104 log

Vc

sh

ð9Þ

where a, b, and c are coefficients which were determined by nonlinear regression (Yan, 2002) and their values are 8.71, 5.78 and 1.37,

respectively. In this equation, Φ is the porosity calculated from density

or neutron logs, Vsh is the shale content, which can be calculated from

the gamma ray log, and k is permeability. Since shale content is

included in this equation, porosity can be used without correcting it

for shale volume effects.

The Timur model is based on the work of Wyllie and Rose (1950).

This model is given in Balan et al. (1995) for permeability calculation:

4 :4

k = 0:136 log : S2

wi

ð10Þ

In this equation, Swi is irreducible water saturation. In our

calculation, we have assumed that Swi=Sw and that the formations
around the boreholes were 100% saturated with water. Considering

the fact that the boreholes were drilled with water and logging was

performed as soon as drilling was completed, this assumption is

reasonable.

Fig. 14. Young's, shear, and bulk moduli and Poisson's ratio calculated for EB-1 using fractal techniques and radial basis functions on gamma and density logs (Karacan, 2008).

Fig. 15. Test site where slug tests were performed in the boreholes (A) and the downhole transducer used to collect data during tests.

Fig. 16-A and B shows permeability values calculated with Eqs. (9)

and (10), respectively, for the entire interval of the EB-2 borehole.

These values show that the permeabilities are generally low except for

some particular intervals. These intervals correspond to the “weak”

intervals at the strata interfaces or “suspected fractures” within the

formations discussed in the previous sections. The high values in those

layers are on the order of 1100–9000 md at 212 m and 90 md at 229 m

in the Fig. 16-A log that was generated using Yan's (2002) formula. The
same locations have 180 md and 9 md in Fig. 16-B, calculated using

Timur's (1968) formula. The other intervals have low permeabilities

on the order of 0–3 md, with an average of 1.16 md, in Fig. 16-A and 0–

0.3 md, with an average of 0.18 md, as shown in Fig. 16-B. As seen from

the calculated permeabilities, the difference between these two

methods is almost one order of magnitude and may result from the

different parameters used in these equations. However, it is not

unusual for empirical models to give somewhat different values

(Balan et al., 1995). Except for two high-permeability intervals, all

permeabilities are very low and the predictions from both models can

be considered close to each other for the ranges reported. They also

can be considered in good agreement with laboratory and with slug

test measurements given in previous sections.

Fig. 16. Permeability logs for EB-2 borehole generated using Yan (2002) equation (A), and Timur (1968) equation (B).

Fig. 17-A and B shows permeability values calculated for the EB-1

borehole for the entire interval using its logs and Eqs. (9) and (10).

Similarly to EB-2, there are also high-permeabilitylayers at this location at

depths of 210 m (40 md), 218 m (680 md) and 244 m (35 md) in Fig.17-A.

The rest of the rock layers have lower permeabilities between 0 and 2 md.

The average of low-permeability layers is 0.6 md. For permeability logs

calculated using the Timur equation (Fig. 17-B), one interval at 224 m has

the highest permeability layer of 22 md. Other higher-permeability

intervals are 7.5 and 14 md at depths of 210 and 218 meters, respectively.

Low permeability intervals have an average permeability value of 0.4 md.

These values are in good agreement with each other and with the results

of laboratory and slug testing.

6. Summary and concluding remarks

The methane emission rate into an underground mine environment

from overburden strata during longwall mining is impacted by reservoir

and geomechanical characteristics of the coal measure rocks in the

overlying strata, as well as the presence of any coal seam. The reservoir

characteristics and how they change during mining potentially affect

the performance of gob gas ventholes, which consequently impacts the

efficiency of methane control in the mining environment.

This paper presents a preliminary reservoir and mechanical characterization of coal measure formations in the Lower Monongahela Group from

exploration boreholes drilled in Greene County, Southwestern Pennsylvania, using laboratory analyses and gamma ray, density, and sonic logs.

Core porosities and permeabilities were determined and log

analyses of formation boundaries, in-situ porosities, existing fractures,

and geomechanical properties (shear, Young's, and bulk moduli and

Poisson's ratio) were reported. Permeabilities were determined using

slug tests in the boreholes and were compared with the permeabilities

calculated using two empirical equations. The results of this paper can

serve as a source of basic properties for coal measure rocks and can be

used for gob gas venthole designs and for constructing models for

reservoir and geomechanical simulations.

Specific observations and conclusions can be stated as:

1. In the Lower Monongahela Group of coal measure formations, most of

the strata are composed of shale-rich sequences with occasional thick

limestone and sandstone layers. Cores recovered from a borehole

showed that layers are mostly fine-grained sediments, without much

primary porosity and permeability. However, there are natural

fractures within the interval, especially in the bedding plane interfaces,

which may help drain pockets of gas and water before mining occurs.

2. Laboratory analyses of core plugs drilled from cores showed that

primary porosities are within 1–2% in most rock types, except with

some higher numbers between 5 and 10% depending on the rock
type and the existence of micro cracks in the matrices. Measured

matrix permeabilities are generally less than 1 md. However, values

increasing to 2–6 md were measured depending on the existence of

fissures in the matrices.

3. Wellbore logs that are commonly used in the petroleum and natural

gas industry can be used in the mining industry for purposes other

than determining the thicknesses of the coal and the immediate

roof material. Well logs can be used more effectively in the coal

mining industry for characterizing the reservoir and mechanical

properties of the entire coal measure strata that will stay in the

fractured interval during mining. These logs can be used to

determine shale content, porosity, elastic moduli of rocks, Poisson's

ratio, fractured intervals or intervals amenable for fracturing, and

permeability. This information can help optimize the location and

design of GGVs to capture methane more effectively.

4. Gamma ray and density logs were used to determine shale contents

and porosities of the Monongahela Group. These logs showed that

there are possible fracturing and separation zones between hardand soft-rock interfaces. The existence of fractures within the single

rock units was also observed. The porosities without shale

correction were calculated at 5–10%. However, considering the

shaliness of formations and their effects on density log readings, a

correction was applied on the porosity data. Shale content for most

intervals was around 40%, except for lower values in thick

limestone intervals. Corrected porosity values were 10–15%.

5. Sonic log data was used to calculate the secondary porosity index

which defined the fractured intervals and their porosities.

6. Full wave sonic log and wave velocities were used to calculate

Young's, shear and bulk moduli of the entire interval. Young's and

bulk moduli varied from 4 to 8 GPa, depending on the rock type.

Shear moduli showed lower values. The strongest formation was

determined to be the limestone interval with the coal and pure

shales being the weakest. Poisson's ratio values were 0.15–0.25 for

the entire interval.

7. Permeabilities of coal measure rocks were calculated using log data

and empirical equations. The values calculated with two different

equations were close and they were also in close agreement with

the laboratory-measured permeabilities and with data from the

slug tests. Higher permeability values were calculated for “possible” fractures, which could not be tested at the laboratory and were

also missed in slug-tested intervals. Thus, log data can be used to

estimate the permeability of fractures in the formation.

Fig. 17. Permeability logs for EB-1 borehole generated using Yan (2002), equation (A), and Timur (1968), equation (B).

Acknowledgements

Drs. Ilkin Bilgesu of West Virginia University and Ronald McDowell

of the West Virginia Geological and Economic Survey are acknowledged for their help in laboratory analysis of cores. Drs. Robert

McLendon and Duane Smith of DOE-NETL in Morgantown are

acknowledged for making X-ray CT available for this study. The

operating mine in Greene County is also acknowledged for giving

permission to have the borehole cores analyzed.

References

Advanced Logic Technologies, 2008. WellCAD v. 4.2. Luxenbourg.

Balan, B., Mohaghegh, S., Ameri, S., 1995. State-of-the-Art in permeability determination

from well log data: part 1 — a comparative study, model development. SPE Paper

no: 30978, Proceedings of SPE Eastern Regional Meeting, Morgantown, WV.
Bauwer, H., Rice, R.C., 1976. A slug test for determining hydraulic conductivity of

unconfined aquifers with completely or partially penetrating wells. Water

Resources Research 12, 423–428.

Beamish, B.B., Crosdale, P.J., 1998. Instantaneous outbursts in underground coal mines:

an overview and association with coal type. International Journal of Coal Geology

35, 27–55.

Bemer, E., Vincke, O., Longuemare, P., 2004. Geomechanical log deduced from porosity

and mineralogical content. Oil and Gas Science and Technology 59, 405–426 – Rev.

IFP.

Castagna, J.P., Batzle, M.L., Eastwood, R.L., 1985. Relationships between compressionalwave and shear-wave velocities in clastic silicate rocks. Geophysics 4, 571–581.

Dawson, K.J., Istok, J.D., 1991. Aquifer testing: design and analysis of pumping and slug

tests. Lewis Publishers, MI.

Deisman, N., Gentzis, T., Chalaturnyk, R.J., 2008. Unconventional geomechanical testing

on coal for coalbed reservoir well design: the Alberta Foothills and Plains.

International Journal of Coal Geology 75, 15–26.

Diamond, W.P., Bodden, W.R., Zuber, M.D., Schraufnagel, R.A., 1989. Measuring the

extent of coalbed gas drainage after 10 years of production at the Oak Grove Pattern,

Alabama. Paper 8961, Proc. Coalbed Methane Symposium, Tuscaloosa, AL.

Dresser Atlas. 1974. Log Review I. Dresser Atlas Division, Dresser Industries.

Endo, T., 2006. Evaluation of formation permeability from borehole Stoneley waves.

Journal of Geography 115, 883–899.

Hatherly, P., Medhurst, T., Sliwa, R., Turner, R., 2005. A rock mass assessment procedure

based on quantitative geophysical log analysis of coal measure sequences.

Exploration Geophysics 36, 112–117.

Karacan, C.Ö. 2008. Elastic and shear moduli of coal measure rocks derived from basic

well logs using fractal statistics (fGn/fBm) and radial basis function (RBF) networks.

Submitted to International Journal Rock Mechanics and Mining Sciences.

Karacan, C.Ö., Mitchell, G.D., 2003. Behavior and effect of coal microlithotypes during

gas transport for carbon dioxide sequestration into coal seams. International

Journal of Coal Geology 53, 201–217.

Karacan, C.Ö., Esterhuizen, G.S., Schatzel, S.J., Diamond, W.P., 2007. Reservoir

simulation-based modeling for characterizing longwall methane emissions and

gob gas venthole production. International Journal of Coal Geology 71, 225–245.

Kelafant, J.R., Wicks, D.E., Kuuskraa, V.A., 1988. A geologic assessment of natural gas

from coal seams of the Northern Appalachian basin. Topical Report GRI 88/0039,

Gas Research Institute, Chicago, IL. 86 pp.

Ketcham, R.A., Carlson, W.D., 2001. Acquisition, optimization and interpretation of X-ray

computed tomographic imagery: applications to the geosciences. Computers and

Geosciences 27, 381–400.

King, G.R., Ertekin, T., 1994. A survey of mathematical models related to methane

production from coal seam: III. Recent developments (1989–1993). The International Coalbed Methane Extraction Conference, London, UK.

King, G.R., Ertekin, T., Schwerer, F.C., 1986. Numerical simulation of the transient

behavior of coal-seam degasification wells. Society of Petroleum Engineers (SPE)

Formation Evaluation, pp. 165–183. April.

Lunarzewski, W.L., 1998. Gas emission prediction and recovery in underground coal

mines. International Journal of Coal Geology 35, 117–145.

Lyons, A., 1998. The central and northern Appalachian Bain — a frontier region for

coalbed methane development. International Journal of Coal Geology 38, 61–87.

Markowski, A., 1998. Coalbed methane resource potential and current prospect in

Pennsylvania. International Journal of Coal Geology 38, 137–159.

Milkereit, B., Ji, J., 2005. Extraction of Stoneley waves from full wave sonic data.

Proceedings of EAGE 67th Conference and Exhibition, Madrid, Spain.

Noack, K., 1998. Control of gas emissions in underground coal mines. International

Journal of Coal Geology, 35, 57–82.

Norris, A., 1989. Stoneley-wave attenuation and dispersion in permeable formations.

Geophysics 54, 330–341.

Palchik, V., 2003. Formation of fractured zones in overburden due to longwall mining.

Environmental Geology 44, 28–38.

Palchik, V., 2005. Localization of mining-induced horizontal fractures along rock layer

interfaces in overburden: field measurements and prediction. Environmental

Geology 48, 68–80.

Penn State University Libraries, 2000. Description of the geology of Greene County

Pennsylvania. URL: http://www.libraries.psu.edu/emsl/guides/X/greene.htm.

Qobi, A., Kuijper, A., Ting, X.M., Strauss, J., 2001. Permeability determination from

Stoneley waves in the Ara Group carbonates, Oman. GeoArabia 6, 649–666.

Remner, D.J., Ertekin, T., Sung, W., King, G.R., 1986. A parametric study of the effects of

coal seam properties on gas drainage efficiency. SPE Reservoir Engineering

633–645 November.

Ruppert, L.F., Tewalt, S.J., Bragg, L.J., Wallack, R.N., 1999. A digital resource model of the

Upper Pennsylvanian Pittsburgh coal bed, Monongahela Group, northern Appalachian Basin coal region, USA. International Journal of Coal Geology 41, 3–24.

Schlumberger, 1991. Log Interpretation Principles/Applications. Schlumberger Wireline

and Testing, Sugarland, TX.

Silitonga, T.H., Siahaan, E.E., 2005. A Poisson's ratio distribution from Wadati diagram as

indicator of fracturing of Lahendong geothermal field, North Sulawesi, Indonesia.

Proceedings of World Geothermal Congress, Antalya, Turkey.

Takahashi, T., Takeuchi, T., Sassa, K., 2006. ISRM suggested methods for borehole

geophysics in rock engineering. International Journal of Rock Mechanics and

Mining Sciences 43, 337–368.

Timur, A., 1968. An investigation of permeability, porosity and residual water saturation

relationships for sandstone reservoirs. The Log Analyst 9, 30–48.

Vaziri, H.H., Wang, X., Palmer, I.D., Khodaverdian, M., McLennan, J., 1997. International

Journal of Rock Mechanics and Mining Sciences 34, 963–978.

Whittles, D.N., Lowndes, I.S., Kingman, S.W., Yates, C., Jobling, S., 2006. Influence of

geotechnical factors on gas flow experienced in a UK longwall coal mine panel.

International Journal of Rock Mechanics and Mining Sciences 43, 369–387.

Whittles, D.N., Lowndes, I.S., Kingman, S.W., Yates, C., Jobling, S., 2007. The stability of

methane capture boreholes around a longwall coal panel. International Journal of

Coal Geology 71, 313–328.

Wyllie, M.R.J., Rose, W.D., 1950. Some theoretical considerations related to the

quantitative evaluation of the physical characteristics of reservoir rock from

electric log data. Trans AIME 189, 105.

Yan, J., 2002. Reservoir parameters estimation from well log and core data: a case study

from the North Sea. Petroleum Geoscience 8, 63–69.