Geotechnical Assessment of Block-VIII at Thar Coalfield, Pakistan
A.G. Pathan, R.N. Singh and R. Stace
ABSTRACT
Rock and soil mechanics investigations have been carried out in block VIII at Thar coalfield and
it was found that most of the strata was mainly composed of sand with an average content of
67.68 %. Laboratory studies of rock and soil samples from drill hole GT-01 revealed that the
strata in block VIII is very weak with an average UCS value of 3.59 MPa, an average tensile
strength value of 0.68 MPa, an average Young’s modulus value of 0.234 GPa, an average
cohesion as 129.19 KPa and an average friction angle as 55.47 deg. Slope stability analysis,
based on a probabilistic approach, has been carried out using Slide-V software. Monte Carlo
simulation has been applied to investigate the possibility of failure in the slopes of an open pit
lignite mine in block-VIII. From the slope stability investigation, it was found that the probability
of failure is zero percent at the slope angle of 16 deg.
INTRODUCTION
Geotechnical investigation of any prospective mining site is essential to determine the technical
and economic viability of the project. Various physical and strength parameters are required for
the design of slopes, haul roads, outside dump and selection of mining machinery in an open
pit mine. In order to assess the various geotechnical parameters in block VIII at Thar coal field,
a geotechnical bore hole # GT-01 was cored from top to bottom with the core diameter of 65
mm (HQ size). 30 samples of various strata formations, encountered in the drill hole, were
collected for various soil/rock mechanics tests including uni-axial compressive strength (UCS),
Brazilian test, Young's Modulus, direct shear test to determine cohesion and angle of internal
friction, unit weight, particle size analysis and Atterberg limits. Slope stability analysis has been
carried out using probabilistic approach. The use of probabilistic slope analyses provides more
efficient and reliable results of slope stability (El-Ramly, H, et al. 2005). The slope geometry,
stratigraphy and rock/soil properties have been incorporated in the model to determine the
critical slip surfaces. Number of samples used for the simulation is 1000 and analysis type is
overall slope. Three material properties, viz. cohesion, friction angle and unit weight have been
defined as random variables. Normal distribution has been used for the random variables.
THAR LIGNITE FIELD
Thar Coalfield is located about 400 Km east of Karachi city in south-eastern part of Sindh
Province, Pakistan near the Indian border as shown in Figure 1. Total lignite reserves of Thar
Coalfield are estimated at more than 175 billion tonnes which constitutes around 90% of the
total coal reserves of Pakistan. The Thar coalfield covers an area of approximately 9000 Km2,
where lignite/brown coal beds lie at depths of between 130m and 250m. The cumulative seam
thickness varies between 1.45m and 42.6m and the maximum thickness of an individual seam
is 28.6m. The Geological Survey of Pakistan (GSP) and the USGS under the Coal Resources
Exploration & Assessment Program (COALREAP) first discovered this lignite field in 1994.
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The Geological Survey of Pakistan (GSP) and Deep Rock Drilling (DRD) have completed a
detailed assessment of coal resources in nine blocks of Thar coalfield. The area covered by
this exploration program is 730 Km2, containing some 19.344 billion tonnes of reserves. The
nine blocks explored in the Thar coalfield are shown in Figure 2. Analysis of the Thar lignite
indicates a relatively low heating value, between 9.4 and 12.7 million btu per tonne. The most
appropriate large-scale application of the lignite is for power generation, and worldwide more
than 90% of lignite and brown coal is used for this purpose [Ahmad and Farzana, 2001].
Figure 2 Nine exploration blocks in Thar Lignite Field (after DRD, private communication)
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Chemical analysis of some 2000 coal samples has been undertaken, and the rank of coal has
been determined, ranging from lignite-B to sub-bituminous-A. The weighted average
composition of lignite-B at Thar is presented in Table 1.
Table 1: Showing the composition of Thar lignite [after Thomas et al (1994)]
S.No.
Parameter
% composition
1.
Moisture (as received)
46.77 %
2.
Fixed Carbon (AR)
16.66 %
3.
Volatile Matter
23.42 %
4.
Ash (AR)
6.24 %
5.
Sulphur
1.16 %
6.
Heating Value
5,774 btu/lb.
STRATIGRAPHY AND LITHOLOGY OF THAR LIGNITE FIELD
Lignite seams in the Thar area are found in the Bara formation of the Paleocene/Eocene age.
The Bara formation is some 95m thick consisting of siltstone, claystone and a sandstone
formation overlying the basement granite occurring at a depth of 100m to 220m [Singh et al.
2011]. The basement rock is very light grey, weathered, medium compacted-granite containing
fine to coarse quartz grains. The overlying Bara formation consists of layers of carbonaceous
clay stone, sandy claystone and silty claystone. Carbonaceous claystone is medium light grey to
brown in colour containing carboniferous petrified roots, carbonaceous materials and rare sandy
resin globules. The olive grey to dark-grey claystone containing petrified plant roots and pyretic
resin globules overlies this sediment.
GEOTECHNICAL TESTS OF ROCK AND SOIL
Various tests, as mentioned above, were conducted on 30 samples of rock and soil at Mehran
University of Engineering and Technology, Pakistan and the University of Nottingham, UK.
Compression Tests
Sixteen rock and soil samples were tested in compression. ISRM procedures were used for
specimen preparation and testing. Servo-Hydraulic Stiff Testing Machine (Model: WAW-1000C )
was used for all compression tests. UCS results of all the rock/soil types range from 0.576 to
8.60 MPa with an average value of 3.59 MPa and standard deviation of 2.34 MPa. Looking at
the results obtained from 16 compression tests, it is revealed that 11 samples have the UCS
values in the range of 1 to 5 MPa which is classified as very low strength. Where as, the UCS
results of 3 rock samples fall in the range rock of 5- 25 MPa which is classified as low strength
rock. Average values of three formations are calculated as follows:
3
Formation
Average UCS (MPa)
Recent
Sub recent
Bara
1.752
4.252
3.723
It is clear from the above results that recent formation (i.e dune sand) is the weakest formation
and sub-recent formation which is mostly composed of siltstone is the strongest formation.
Young's modulus of 14 samples were determined from compression tests and the results are
shown in Table 2. These results are in the range of 0.126 to 0.365 GPa with the average value
of 0.234 GPa and standard deviation of 0.07 GPa. Young's modulus values indicate the plastic
behaviour of various rocks/soil. Young's modulus results have linear correlation with uniaxial
compressive strength results as shown in Figure 3. The empirical relationship of the best fit
linear regression line through the data points is determined as follows:
UCS = 24.336 x E – 1.6006
UCS (MPa)
Correlation of UCS with E
10
9
8
7
6
5
4
3
2
1
0
y = 24.336x - 1.6006
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Young's Modulus, E (GPa)
Figure 3:- Correlation of UCS with Young's Modulus (E)
BRAZILIAN TEST
Sixteen rock/soil samples, obtained from drill hole GT-01, were tested for the determination of
tensile strength using the disc type specimen under diametral loading. The results are
presented in Table 2. These results ranges from 0.237 MPa to 2.924 MPa with the average
value of σav = 0.677 MPa and standard deviation of 0.65 MPa. Average values of tensile
strength for three formations are calculated as follows:
4
Rock Formation
Recent
Sub-recent
Bara
Average Tensile Strength (MPa)
0.31
0.58
0.975
Above results indicate that the tensile strength of recent (i.e dune sand) formation has got the
lowest value, where as Bara formation has the highest value of tensile strength. Tensile strength
has the linear correlation with UCS as shown in Figure 3. Following empirical equation has been
determined from the correlation graph:
Y =1.8609X + 1.9952
UCS (MPa)
Correlation between UCS and tensile strength
10
9
8
7
6
5
4
3
2
1
0
y = 1.8609x + 1.9952
0
0.5
1
1.5
2
2.5
3
3.5
Tensile Strength, (MPa)
Figure 4: Showing the linear correlation between UCS and tensile strength
DIRECT SHEAR TEST
Direct shear tests were conducted on 9 samples of rock, 8 samples of soil and 7 samples of
coal obtained from geotechnical drill hole, GT-01 in block VIII. From the shear tests, cohesion
and angle of internal friction were determined. Cohesion of different layers varies between 0.51
KPa and 1275 KPa with standard deviation of 304.68 KPa and angle of internal friction ranges
between 9.48 deg and 86.87 deg with standard deviation of 27.40 deg.
SOIL CLASSIFICATION
Unified Soil Classification System and ASTM soil classification techniques have been used for
the classification of soil encountered in the drill hole GT-01. Particle size analysis and Atterberg
limits tests were conducted for soil classification:
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Particle Size Analysis
Seven soil samples, from drill hole # GT-01 were collected for particle size analysis, using
various sizes of sieves and particle size analyzer (Model: HORIBA). Particle size of soil, passing
through 500 μm sieve, was determined by laser based particle size analyzer which is a latest
technique and gives more accurate results than hydrometer analysis. Grain size distribution
curves for all samples were developed. Constituents of soil were determined on the basis of
particle size as per ASTM classification.
Three soil parameters, viz. Effective size, Uniformity Coefficient, and Coefficient of Gradation,
have been evaluated from grain size distribution graphs and shown below in Table 2:
Table 2: Effective size, uniformity coefficient and coefficient of gradation
Sample #
Effective size (d10)
GT-01-01
GT-01-02
GT-01-09
GT-01-10
GT-01-13
GT-01-14
GT-01-20
0.011 mm
0.079 mm
0.004 mm
0.004 mm
0.003 mm
0.013 mm
0.114 mm
Uniformity coefficient
(Cu)
14.36
3.34
12.0
30.25
45.0
37.23
2.53
Coefficient of gradation (Cz)
5.3
0.73
0.88
8.46
0.42
6.23
0.97
Atterberg Limits
Seven soil samples from drill holes GT-01 were tested in the laboratory and their liquid limits and
plasticity indexes were determined. From these results, plasticity chart has been developed as shown in
Figure 5.
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Figure 61: Plasticity Chart of Drill Holes, GT-01 & GT-2B
50
Plasticity Index
40
Li
U-
30
ne
A-Line
ine
A-L
U-Line
Projection-30
20
Projection-50
P-Index
10
0
0
10
20
30
40
50
60
70
Liquid Limit (%)
Figure 5: Plasticity chart of soil samples from drill hole GT-01 of block-VIII
SLOPE STABILITY ANALYSIS USING PROBABILISTIC APPROACH
A probabilistic slope stability analysis based on Monte Carlo simulation has been applied to
investigate the possibility of failure in the slopes of open pit lignite mine in block-VIII of Thar
coalfield. Slide-V software has been used for probabilistic analysis. The slope geometry,
stratigraphy and rock/soil properties have been incorporated in the model to determine the
critical slip surfaces. Number of samples used for the simulation is 1000 and analysis type is
overall slope. Three material properties, viz. cohesion, friction angle and unit weight have been
defined as random variables. Normal distribution has been used for the random variables.
Simplified lithology of drill hole GT-01 and design parameters used for slope stability analysis
are given below in Table 3:
Table 3: Simplified Lithology of Drill Hole GT-01 of Block-VIII and Design Parameters for Slope
Stability
Lithology
Formation Thickness Cav/ Cst
CRmin/CRmax
Dune Sand Recent
40.73
Siltstone-1
Sub-Recent
39.02
Siltstone-2
Sub-Recent
58.23
Sand
Sub-Recent
26.02
23.27/23.78
16.82/16.81
21.8/9.49
8.97/8.28
55.33/15.52
16.11/17.82
35.28/46.26
30.11/53.26
Φav/ ϕst
ϕRmin/ϕRmax
γav/ γst
γRmin/γRmax
34.12/12.52
8.85/8.85
21.29/13.12
11.81/16.74
80.65/2.64
2.61/3.5
32.55/13.38
14.97/20.71
16.35/2.46
2.69/2.24
14.31/6.72
5.41/7.53
10.26/3.88
3.14/5.53
17.77/0.24
0.19/0.27
7
Lignite
Bara
43.17
Claystone
Bara
12
23.61/17.57
20.88/32.71
824.67/482.15
509/450.5
67.19/24.29
54.05/15.66
80.41/5.6
3.43/6.46
37.86/5.58
7.03/6.01
20.13/1.26
1.22/1.77
Six slope angles from 16 deg. to 25 deg. have been investigated to determine the stability using
probabilistic approach. Mean safety factor (FS), probability of failure (PF) and reliability index
(RI) based on normal & lognormal distribution have been determined. The analysis is carried out
for overall slope. Probabilistic analysis of slope with inclination of 16 deg is shown in Figure 6.
Figure 6: Probabilistic analysis of a slope with inclination of 16 deg.
The probabilistic analysis results shown in Figure 6 are based on overall slope reliability. A
summary of the results are displayed in the legend which includes mean safety factor (FS),
probability of failure (PF in %) and reliability index (RI normal and RI lognormal). These results
correspond to the slip surfaces displayed on the model. These slip surfaces are all of the
different global minimum slip surfaces, located by the overall slope probabilistic analysis.
Probability of failure (PF) is simply equal to the number of analyses with safety factor less than
1, divided by the total number of samples, and it is calculated as follows:
𝑛𝑢𝑚𝑓𝑎𝑖𝑙𝑒𝑑
𝑃𝐹 = 𝑛𝑢𝑚𝑠𝑎𝑚𝑝𝑙𝑒𝑠 𝑥100%
Reliability Index (RI) is an indication of the number of standard deviations which separate the
mean safety factor from the critical safety factor (=1). RI can be calculated assuming either a
normal or log-normal distribution of safety factor results.
From the overall slope results of probabilistic analysis, the effect of slope angle on PF, FS and
RI (normal) is plotted in Figure 7. It is clear from the figure that the probability of failure
decreases from 21 % at 25 deg. slope angle to 0.1 % at 16 deg. which means 16 deg. slope
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angle is safe and can be considered as optimum slope angle. It is also clear from the graph that
the mean safety factor and reliability index increases by decreasing the slope angle. Optimum
values of FS(mean) and RI are achieved as 1.922 and 1.839 respectively at the slope angle of
16 deg.
Effect of Slope Angle on PF, FS and RI
25
PF(%)
FS(mean)
RI(normal)
20
15
PF(%)
10
FS(mean)
RI(normal)
5
0
25
23
21
19
17
15
Slope Angle (deg)
Figure 7: The effect of slope angle on PF, FS and RI (normal)
Cumulative probability is plotted against safety factor for slope angles 16 deg. and 25 deg. as
shown in Figure 8. It is clear from this graph that cumulative probabilities of failure at safety
factor 1 are 0 % and 21.3 % for slope angles 16 deg and 25 deg. respectively.
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Cumulative (FS - Bishop simplified)
1
Cumulative Probability
0.9
0.8
0.7
0.6
0.5
16 deg
0.4
25 deg
0.3
0.2
0.1
0
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
3.4
Factor of Safety - Bishop simplified
Figure 8: Cumulative plot of safety factor for the slope angles – 16 and 25 deg.
Convergence plots showing the probability of failure vs number of samples are presented in
Figures 9 and 10. Convergence plot for slope angle 25 deg. as shown in Figure 9 indicates that
the final results of the probabilistic analysis are converging to stable after 250 samples.
Probability of failure for slope angle 16 deg. is zero as shown in Figure 10, that is why the
convergence plot is a straight line .
Figure 9: Convergence plot showing the probability of failure for slope angle 25 deg.
10
Figure 10: Convergence plot showing the probability of failure for slope angle 16 deg.
From the above discussions, following conclusions can be made:
1. UCS results of all the rock/soil types range from 0.576 to 8.60 MPa with average value
of 3.59 MPa and standard deviation of 2.34 MPa. Looking at the results obtained from
16 compression tests, it is revealed that 11 samples have the UCS values in the range
of 1 to 5 MPa which is classified as very low strength. Where as, the UCS results of 3
rock samples fall in the range rock of 5 MPa to 25 MPa which is classified as low
strength rock. Average values of three formations are calculated as follows:
Formation
Average UCS (MPa)
Recent
Sub recent
Bara
1.752
4.252
3.723
It is clear from the above results that recent formation (i.e dune sand) is the weakest
formation and sub-recent formation which is mostly composed of siltstone is the
strongest formation.
2. Young’s modulus results are in the range of 0.126 to 0.365 GPa with the average value
of 0.234 GPa and standard deviation of 0.07 GPa. Young's modulus values indicate the
plastic behaviour of various rocks/soil. Young's modulus results have linear correlation
with uniaxial compressive strength results as shown in Figure 3. The empirical
relationship of the best fit linear regression line through the data points is determined as
follows:
UCS = 24.336 x E – 1.6006
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3. Brazilian test results indicate that tensile strength of rocks and soils is in the range of
0.237 MPa to 2.924 MPa with the average value of σav = 0.677 MPa and standard
deviation of 0.65 MPa. Average values of tensile strength for three formations are
calculated as follows:
Rock Formation
Recent
Sub-recent
Bara
Average Tensile Strength
(MPa)
0.31
0.58
0.975
Above results indicate that the tensile strength of recent (i.e dune sand) formation has
got the lowest value, where as Bara formation has the highest value of tensile strength.
Tensile strength has the linear correlation with UCS as shown in Figure 3. Following
empirical equation has been determined from the correlation graph:
Y =1.8609X + 1.9952
4. Direct shear test results indicate that the cohesion of different layers in drill hole GT-01
varies between 0.51 KPa and 1275 KPa with standard deviation of 304.68 KPa and
angle of internal friction ranges between 9.48deg and 86.87deg with standard deviation
of 27.40 deg.
5. Soil classification study indicates that most of the soil is block VIII is mainly composed of
sand with average content of sand as 67.68 %.
6. Following conclusions are made for the slope stability analysis, based on probabilistic
approach:
 The effect of slope angle on probability of failure (PF), safety factor (FS) and reliability
index (RI, normal) has been investigated and it is found that the probability of failure
decreases from 21.3% at 25 deg. slope angle to 0 % at 16 deg. which means 16 deg.
slope angle is safe and can be considered as optimum slope angle. It is also found from
the investigation that the mean safety factor and reliability index increases by decreasing
the slope angle. Optimum values of FS(mean) and RI are achieved as 1.922 and 1.839
respectively at the slope angle of 16 deg.
 Convergence plot for slope angle 25 deg. as shown in Figure 9 indicates that the final
results of the probabilistic analysis are converging to stable after 250 samples.
Probability of failure for slope angle 16 deg. is zero as shown in Figure 10, that is why
the convergence plot is a straight line .
REFRENCES

El-Ramly, H., Morgenstern, N.R. & Cruden, D.M. (2005). Probabilistic Assessment of
Stability of a Cut Slope in Residual Soil. Geotechnique, 55 No. 1, 77-84.
12

Thomas, R.E., Shah, A.A., Khan, S. A. and Tgar, M. A. and Others (1994),’ Analytical
results on coal samples collected from drilling activities in the Thar Desert, Sindh,
Pakistan, U.S. Geological Survey Open File Report 94-557, 440 p

Singh, Raghu N.; Pathan, Abdul Ghani; Reddish, David J.; and Atkins, Anthony
S.,(2011). “Geotechnical Appraisal of the Thar Open Cut Mining Project”. Underground
Coal Operators’ Conference. 10-11 February 2011. pp. 105-114. Australia.


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