International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
Contents lists available at ScienceDirect
International Journal of
Rock Mechanics & Mining Sciences
journal homepage: www.elsevier.com/locate/ijrmms
Atypical evolution of seismicity patterns resulting from the coupled
natural, human-induced and coseismic stresses in a longwall coal
mining environment
Maria Kozłowska a,n, Beata Orlecka-Sikora a, Łukasz Rudziński a, Szymon Cielesta a,
Grzegorz Mutke b
a
b
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland
Central Mining Institute, Katowice, Poland
art ic l e i nf o
a b s t r a c t
Article history:
Received 23 October 2015
Received in revised form
12 February 2016
Accepted 31 March 2016
A very unusual time-space distribution of seismicity accompanying coal exploitation has been observed
in a Polish mine. The earthquakes did not follow the depth of mining but exhibited changing depths from
far below to close to the mined seam. One of the deep events which occurred at close epicentral distance
to the active mining front was ML3.7 event. This paper presents the study of possible coupling of natural,
human-induced and coseismic stresses in a longwall coal mining environment. The full moment tensor
solution showed that the strong earthquake occurred on an almost vertical plane consistent with approximate strike of local tectonic structure. The signal correlation analysis revealed some highly correlated pairs within both deep and shallow event groups. To evaluate inducing factor of ongoing and past
exploitation, geomechanical modelling of its influence on strain and stress at the target depth has been
performed. The results exhibited a changing vertical stress regime, which might have promoted failure
on preexisting, almost vertical planes of weakness. The earthquakes' rate variation in time showed no
increase in activity right after the occurrence of ML3.7 event. The P-S-wave spectra corner frequency ratio
had an average of 1.0, suggesting slow rupture. However, the Coulomb stress change analysis showed
that the magnitude of stress changes due to coseismic slip of ML3.7 event at the hypocentral depth is of
the same order as the stress changes caused by mining. Thus, the distribution of seismicity at this level
could have been driven by both exploitation and coseismic stresses. Moreover, the seismicity which
occurred within first few weeks after ML3.7 event, followed positive stress changes. All the obtained
results let us prove that the ML3.7 event was a tectonic earthquake triggered by ongoing exploitation and
that the distribution of following seismicity was affected by coupled natural, exploitation-induced and
coseismic stresses.
& 2016 Published by Elsevier Ltd.
Keywords:
Mining induced seismicity
Coulomb stress transfer
Tectonic stress
1. Introduction
Seismicity accompanies different methods of mining and
occurs as failures of the strata, collapses or rock bursts (e.g. Ref. 1,
and the reference therein). The distribution of mining seismicity is
strictly related to the exploitation progress of mining works and,
consequently, to the local stress field (e.g. Ref. 2, and the reference
therein). The longwall mining system changes the stress field
across the panel, ahead of the face, but also along the sides of the
panels within headgate and tailgate.3–7 All these areas are highly
probable for seismic events occurrence. According to many analyses, the maximum number of tremors occurs at a distance of
n
Corresponding author.
E-mail address: mkozlow@igf.edu.pl (M. Kozłowska).
http://dx.doi.org/10.1016/j.ijrmms.2016.03.024
1365-1609/& 2016 Published by Elsevier Ltd.
tens of meters ahead of the face, above and below the panel.7–10
There are also local extremes in a goaf at a longer distance from
the face.11 However, analyzing the seismicity from one of the coal
mines of Upper Silesia Coal Basin (USCB), Poland, we observed
very interesting and unusual time-space behavior of seismicity
pattern – the seismicity typically accompanying exploitation exhibited changing depths from great below to close to mined seam.
What is more, one of the events which occurred at great depth
below, but at close epicentral distance to active mining front, was a
strong event of ML ¼3.7. Such rather unusual seismicity pattern
made this case worth studying in the context of possible natural,
induced and coseismic stresses governing seismicity distribution
in mining environment.
In this paper we present the results of investigation of possible
factors, both natural and induced by mining, causing this strong
seismic event. Using various methods for studying the event, we
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M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
try to find out whether mining exploitation in this region can
activate underlying tectonic structures and trigger earthquakes.
Also, we investigate whether strong events in mining and geological settings of Upper Silesia can influence the number and distribution of following weaker seismicity. This study is the continuation and extension of earlier work done by Marcak and
Mutke,12 where the seismicity of the same mine was analyzed.
Authors were investigating the tectonic activation of rock masses
as a result of mining.
We start our analysis from relocation of strong events to verify
results obtained by the mine's routine. In the second step, we
perform signal correlation to investigate whether deep and more
shallow events have significantly different recorded signals. In
order to carefully investigate the ML3.7 event, we determined its
moment tensor and source parameters. To evaluate inducing factor
of ongoing and past exploitation we performed geomechanical
modelling of its influence on strain and stress in the rock mass at
the target depth. The last part of the analysis is focused on investigating the effect of the coseismic stress changes due to strong
event on following seismicity. Static stress transfer phenomenon
has been studied in natural earthquakes and was proven to influence the distribution of aftershocks.13 Recently, few studies
have analyzed the influence of static stress transfer on mining
seismicity,14–16 showing that strong mining events are capable of
producing stress changes big enough to influence the spatial and
temporal distribution of following seismicity. In our study, we
want to investigate whether similar effect was observed after ML
3.7 event.
2. Seismogenesis conditions of USCB
The USCB in southern Poland is the place of intense coal exploitation carried out since 18th century. Coal seams deposited
within Carboniferous sandstones, conglomerates and mudstones
are now being exploited in more than thirty mines using the
longwall method. Mining induced seismicity in the area has been
monitored since 1929 when the first mining-dedicated seismological station was opened in Racibórz city in southern USCB. Since
then, with only three years break after World War II, seismic
monitoring was constantly improved leading to the present day
Upper Silesian Regional Seismological Network (GRSS) conducted
by Central Mining Institute (CMI) and a number of local networks
conducted by mines themselves. Locations of most seismic mining
areas correlate with tectonically complicated parts of the USCB, i.e.
the Kłodnicki fault, Main anticline and Bytom syncline regions
(Fig. 1). Seismicity in these regions' mines is not only the most
intense in the area but also characterized by the highest
magnitudes.17,18 The strongest events recorded in the USCB in the
last twenty years had local magnitudes ranging from 3.8 to 4.0 and
occurred in mines in mentioned areas.
In numerous studies of mining seismicity authors have distinguished several mechanisms of seismic events which correspond to diverse stress state around mining face and exploited
voids.3,19,20,21 Bimodal frequency-magnitude distribution indicates
two main types of events and has been observed in several mines:
e.g. Polish coal mines,22 Polish copper ore mines23 and South
African gold mines.24 Mentioned studies suggest that smaller
earthquakes - named type A after Richardson and Jordan,24 are
directly connected with mining operations whereas bigger earthquakes, type B, are associated with local and regional tectonic
structures which create weak zones and promote shear failure. The
type A seismicity occurs as a result of interaction between mining
induced and local tectonic stresses and cluster mainly in close
vicinity to mining stope. Such events are characterized by low and
medium magnitudes and can have significant non double-couple
18˚24'
18˚48'
50˚24'
19˚12'
50˚24'
A
50˚00'
50˚00'
18˚24'
18˚48'
19˚12'
Paralic Series
Mudstone Series
Upper Silesian
Sandstone Series
Krakow Sandstones
Fig. 1. Map of USCB with seismicity recorded by GRSS in 2014, only ML 4 2.5-black
points. Note the location of Bobrek mine. Main seismotectonic units mentioned in
the paper are marked with letters: A-Bytom syncline, B-Kłodnicki fault, C-Main
anticline.
component associated with volume change caused by stope
closure.19,20,25 Mining tremors associated with local and regional
tectonic structures, type B, have usually larger magnitudes, their
mechanisms are coupled to pre-existing faults or other zones of
weakness and thus are rather of double-couple type. Such events
can also occur at greater distances from an active mining
front.3,18,26 Such events in USCB are usually associated with wellknown geological units intersecting the area mostly in its north
part, including well mapped Kłodnicki fault and Main anticline17
(Fig. 1). Many of these big events have also been assigned to Bytom
syncline intersecting numerous mines and striking WNW-ESE,12
however, no significant faults have been mapped there. One of the
mines currently inducing intense seismicity and passing Bytom
syncline axis is Bobrek Coal Mine in Bytom city (Fig. 1). In December 2009 strong seismic event of ML ¼3.7 occurred during
exploitation of longwall panel (LP) 3 of coal seam no. 503. The
routine mine location showed that the event occurred when
mining front approached the syncline axis. The lack of damage at
mining level and the fact that the event was felt on the surface at
great distance from its epicenter indicated that its hypocenter was
much below mined seam suggesting tectonic character of the
event.12 Its great depth was later confirmed by 3D locations
(Fig. 2). Interestingly, distribution of smaller events, typically accompanying exploitation, also exhibited great depths. What is
more, the seismicity became more intense when the mining front
passed approximately half of planned panel's length.
3. Data
The strong seismic event of ML ¼3.7 occurred on December
16th, 2009 during mining of panel 3/503 in Bobrek mine. The
mine, located in one of the most seismically active parts of USCB
(Fig. 1), has been extracting coal from twelve seams using multilevel method and longwall system. Local magnitudes have been
calculated from energy measurements using formula developed
for USCB and based on local mine network recordings.27 A local
network was designed to monitor and locate seismicity accompanying exploitation. At the time of the event occurrence it consisted of seven vertical and five three-component short period (1–
200 Hz) DLM3D seismometers manufactured by CMI, with sampling rate of 500 sps. In the second half of January 2010 the network was extended with 6 additional vertical sensors with the
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a) 4800
0
b)
5200
400
6000
6400
800
depth [m]
coal seams
X [m]
5600
1200
6800
1600
7200
7200
80 0
400
0
−400
5200
5600
6000
Y [m]
6400
6800
X [m]
Fig. 2. Distribution of seismicity associated with LP 3/503 exploitation – black points, showing the ML 3.7 event – red star, and seismic stations closest to the panel
3 – triangles and black rectangle, respectively. Arrows show exploitation direction. a) Map view including seismicity recorded during exploitation of other mining panels of
seam 503 – grey points, b) N-S cross section showing exploitation level – black horizontal line. X and Y coordinates are given in local coordinate system “Sucha Gora”. Note
that not all stations presented in cross section are shown in a map view because of their large horizontal distance to the panel.
Events behind mining front
Events ahead of mining front
1000
800
N
600
400
200
500
400
300
200
100
0
-100
-200
-300
-400
0
-500
same parameters. The mining routine location and determination
of events' energy was based on manual picking of P and S waves
arrivals and performed only in 2D. Exploitation of seam 503 was
held in four longwall panels, advancing from north to south. Since
the start of exploitation of panel 1 in 2005, three strong events
with local magnitude above 3.0 were observed, two of which are
supposed to be associated with underlying Bytom syncline axis.
The seismicity accompanying the exploitation of panel 3 became
the subject of Laboratory for Monitoring Mining Induced Seismicity project (LMMIS) held by Central Mining Institute, a part of ISEPOS project (http://is-epos.eu/). It has been relocated by CMI
using the same software as the mining geophysical survey, but in
3D mode, using repicked signals. The final catalog comprises of
2996 events with magnitude of completeness MC ¼ 1.5. CMI located ML3.7 event at depth of E700 m below exploited seam. The
depths of smaller events accompanying exploitation exhibit untypical distribution - the majority of seismic events have also been
located much below the seam with only few events typically
surrounding the stope level (Fig. 2b). Note that no prior exploitation has been performed at such depth. The depth distribution
changed at some point when, according to Marcak and Mutke 12,
the mining front reached the Bytom syncline axis. At this point the
seismicity climbed toward stope level, probably along southern
limb of the syncline, reaching it at approximately 700 m of exploitation front advance. Rapid increase in a number of recorded
events visible in Fig. 2b at approximately 6400 m could be linked
to network extension, however the Modified Goodness-of-fit test
used to determine Mc28 did not reveal decrease of Mc for catalog
after network extension. What is more, such an increase in a
number of events was observed not only in panel 3, but also in all
other panels of coal seam no. 503 which were monitored by stable
seismic network (Fig. 2a). This may indicate that such distribution
of events is mainly the result of local geology and tectonics, rather
than only the expansion of network. Unfortunately, we could not
compare our data with the vertical distribution of seismicity from
mentioned panels since we had an access only to mining routine
2D locations. However, according to Ref. 12, seismic events which
occurred in other panels were also located at great depths below
the seam.
Interestingly, only vertical distribution of seismicity seems to
be unusual; the horizontal distribution follows the typical pattern
where mining events occur at close epicentral distances from active mining front (Fig. 3). To verify the unusual seismicity depths,
epicentral distance to the front [m]
Fig. 3. Distribution of number of events relative to the epicentral distance from the
mining front, for seismicity of LP 3/503. Positive values of distance stand for events
occurring ahead of mining front, within intact rock; negative values stand for
events occurring behind active front.
we relocated the strongest events using the single event relocation
method based on probabilistic inverse theory.29 In the second step
of depths verification the signals cross-correlation was performed.
These two techniques are described below.
4. Events relocation
Seismic events location procedure carried out by mining geophysical surveys usually has to deal with some specific issues. Two
of them are crucial for our analysis, namely lack of origin time and,
consequently, poor depth estimation. Since network timing is not
controlled by any standardized time, it is also difficult to use some
relocation approaches based on differences of recorded first arrivals times e.g. Double Difference.29 Here we used seismic signals
recorded on vertical seismometers to relocate induced seismic
events of ML 42.3 associated with LP. The location procedure
worked with probabilistic inverse approaches and was already
tested for Polish local mining seismic networks. Details of the
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M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
procedure are described in Rudziński and Dębski.29 The locations
were obtained using mean P-wave velocity of 3850 m/s, based on
average velocities estimated for seismic stations at the time of
longwall excavation (mining geophysical survey – personal information). Our procedure gave similar results as CMI relocation,
with horizontal location differences not greater than 60 m. For five
out of nine relocated strong events, new depths were smaller than
those reported by CMI, however they were still much below
exploited seam, e.g. E500 m below in case of the ML3.7 event (red
star in Fig. 2b). The location errors differ among coordinates. Mean
latitude error was 38 m (min: 33 m; max: 46 m) while mean
longitude error was 42 m (min: 37 m; max: 50 m). Depths of hypocenters were much more influenced by location inaccuracy with
mean errorE130 m (max: 171 m). Even though depths are the
weakest point of events location, it did not affect observed seismic
pattern. To investigate whether different velocity model could
change events' depths, we performed tests using different velocities by adding and subtracting up to 500 m/s. Final results did
not change the general observation that events' depths changed in
time. Thus, the relocation step helped us confirm great depths of
observed events and their untypical time pattern. In subsequent
steps of the analysis, we applied new locations for the strongest
events and CMI locations for the rest of the data bearing in mind
small differences between these two relocation results.
check whether their signals differ significantly between and
within these groups. We used signals from 1 s before to 4 s after
P-wave onsets and their maximum cross-correlation value as an
indicator of signals similarities. Fig. 4 shows a matrix of correlation
coefficients calculated for all event-event pairs. We used signals
from a station with epicentral distance exceeding 900 m to be able
to assume similar wave paths for all events. Also, this station was
the least noisy from all distant ones. The mean cross-correlation
coefficient within shallow events group – quarter II in Fig. 4-is
0.53. The same value within deep events group – quadrant III - is
0.52. By cross-correlating events from these two groups we get
mean coefficient value of 0.48 – quadrants I and IV. The mean
values of correlation coefficients are not significantly higher
within groups than between them, however there are some eventevent pairs with very high cross-correlation close to 1 which occurred within both groups (Fig. 5). What is more, there is highly
correlated group of about twenty-five events within quadrant II –
shallow events.
The cross-correlation analysis did not give us clear evidence of
the changing events' depth, however it revealed some highly
correlated pairs within both deep and shallow events groups. Such
high values were not observed when correlating events between
groups. It may indicate a changing depth of events.
4.1. Signals cross-correlation analysis
5. Characterisation of seismic source of ML3.7 event
According to CMI relocation, events depths changed at the time
when mining front approached the axis of Bytom syncline
(Fig. 2b). Since inaccuracy in depth estimation could affect our
interpretation, we decided to provide some further analysis to
verify this unusual distribution of seismicity. Based on the idea
that signals of events with close hypocenters and similar focal
mechanisms recorded on the same station are very similar, we
carried out additional signals processing, namely signals crosscorrelation. Assuming close epicentral distance among analyzed
events, possible differences in recorded signals are either due to
events' different depths or focal mechanisms. Here, we analyzed
only tremors from central part of mining panel 3 to exclude those
events which occurred close to panel's edges where local stress is
accumulated (Fig. 4). Thus we could assume that focal mechanisms
of analyzed events were similar. If so, only the vertical location
could be the factor affecting recorded signals shapes. In our analysis we relied on 50 tremors before and 50 after depth change to
5.1. Moment tensor solution
We manually picked P-wave onsets on all twelve available inmine stations and performed moment tensor inversion in the time
domain.30 The inversion was performed using FOCI 3.4 software,31
applying the relocated origins and constant velocity and density of
3850 m/s and 2700 kg/m3, respectively. In the inversion procedure
the amplitudes and polarities of the P-wave displacement onsets
are used. Fig. 5 shows the full moment tensor solution for the ML
3.7 event.
The full moment tensor solution shows that the earthquake
occurred as reverse faulting on a northwest-striking plane which
is consistent with approximate strike of Bytom syncline. Nodal
plane 1 is almost vertical and plane 2 almost horizontal. Very high
double-couple component of the moment tensor solution – almost
95%, can be well explained by the great depth of the event and,
thus, supports the idea of its tectonic, rather than purely mining,
Fig. 4. Cross – correlation coefficients matrix for selected seismic station (triangle in 3D view). Note that first 118 seismic events (blue points in 3D view) are stronger
correlated among each other in comparison with the rest 118 tremors (green points in 3D view). (For interpretation of the references to color in this figure legend, the reader
is referred to the web version of this article.)
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M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
0
100 200
[m]
approach proposed by Andrews32 to use J and K velocity and
displacement integrals33 as two independent parameters in frequency domain and based on them to calculate the low-frequency
spectral level Ω0 and corner frequency f0. The source radius r0, slip
u and stress drop ∆s were calculated using Brune's source model34
and Aki and Richards35 seismic moment definition. S wave velocity
Vs and density ρ for GRSS network are 2660 m/s and 2500 kg/m3,
respectively, giving shear modulus G value of 1.77 1010 Pa. Table 1
presents values of source parameters of ML3.7 event. Based on
obtained seismic moment we calculated a moment magnitude of
MW3.8,36 which is close to local magnitude.
strike dip slip
plane 1
plane 2
131°
309°
80° 90°
10° 87°
Tensor components:
ISO: 1.9 %
CLVD: -3.5 %
DC: 94.7 %
6. Numerical modelling of the effect of exploitation on analyzed depth rock mass
Fig. 5. Focal mechanism of ML 3.7 event (star) obtained by moment tensor inversion of P-wave onsets. The event is shown on corresponding mining layout: dashed
areas indicate mining panels: no. 2 (right hand panel – mined-out) and no. 3 (left
hand panel - under exploitation at the time of the event). An arrow shows exploitation direction.
character. The obtained mechanism is similar to the one described
in Ref. 12, where authors also present reverse fault mechanism
with similar strikes of both nodal planes, however, with different
dips. The possible reason for such difference may be the fact that
in 2009, when the analyzed event occurred, the mine network was
being replaced and extended. At the time of the event occurrence,
sensors from both networks, the old and new, modernized one,
were in operation. Marcak and Mutke12 presented focal mechanism calculated based on old network recordings, whereas we
present new network results. Unfortunately, data from the old
network are not available anymore, so we could not compare both
solutions.
5.2. Spectral analysis
Spectral analysis was performed using MULTILOK: Mining
Tremors Analysis Software developed by CMI. Since data from
mine network were mostly clipped, in the analysis of ML 3.7 event
we used S waves recorded at the one available at that time GRSS
station with epicentral distance of 4.4 km. MULTILOK applies the
Table 1
Mean source parameters of ML3.7 event calculated from six underground mine
stations.
Seismic moment M0
[Nm]
Source radius r0
[m]
Slip u [m] Stress drop ∆s
[MPa]
4.4 1014
195
0.21
26
A numerical modelling approach of past and ongoing exploitation of Bobrek mine coal seams was proposed to study the
stress and strain distribution in the rock mass. Particular attention
was being paid to the depth range of mine exploitation influence.
Our aim was to estimate the magnitude of stress and strain
changes at the level of studied earthquake, i.eE500 m below
exploited coal seam.
To model the described case FLAC2D (Itasca Consulting Group,
FLAC – Fast Lagrangian Analysis of Continua, Ver. 7.0. Minneapolis:
Itasca) software was used. It is two-dimensional Fast Lagrangian
Analysis of Continua software based on Finite Differences Method
(FDM), commonly used to analyze static and dynamic problems. In
our study we performed static analysis where modelled stress and
strain state resulted from the appearance of the excavation at the
particular depth.37 We applied Coulomb-Mohr constitutive model
and built a model of rock mass as a 1200 1200 m continuum in
plane strain conditions. The top edge of the model corresponds
with sea level. The roof of analyzed coal seam 503 lies at the depth
of 455 m bsl, however we are mostly focused on depth of ML3.7
event, namely around 1000 m.
The model consists of 135 geological layers, represented by four
different lithological units: sandstone, coal, sandy shale and clay
shale, according to local geology.38 Geomechanical parameters of
geological layers used in the model are presented in Table 2. The
order of the deposition of the layers and their thickness were
precisely read from the three borehole lithological profiles to the
depth of 600 m bsl (Mining Geophysical Survey – personal information). Deeper layers were scattered randomly, based on
general USCB geology.39 The grid consists of 257 856 elements
(474 elements horizontally and 544 vertically). Boundary conditions were assigned to the edges of the model: zero horizontal
displacements on both sides' edges and zero vertical displacement
were applied to the bottom of the model. The additional loading of
7.24 MPa equal to the weight of the overburden was added to the
top edge of the model. LP 3 in the coal seam 503 is located within
the operating edges of twelve other coal seams. In the model, the
order of exploitation has been preserved. The primary stress term,
which is used later in the text, refers to the stabilized stress state
Table 2
Geomechanical parameters of geological layers used in model.38,40
Coal
Sandy shale
Clay shale
Sandstone
Volume density
ρ
[kg/m3]
Frictional angle
ϕ
[deg]
Cohesion
c
[MPa]
Young's modulus
E
[GPa]
Poisson's ratio
ν
[dimensionless]
Splitting tensile strength
Rr
[MPa]
Tension
Rc
[MPa]
1290
2690
2600
2510
24
25
24
25.3
3.3
7.2
6
11.3
3.6
11.2
10
18
0.24
0.24
0.25
0.27
0.5
2.1
1.9
3.3
15.8
22.5
19.2
35.7
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M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
Fig. 6. Profiles at the depth of 945 m bsl presenting: a) vertical displacement, and primary and secondary b) vertical stress Syy, c) horizontal stress Sxx, d) shear stress Sxy.
Dashed line represents west edge of mined panel.
resulting from exploitation of mentioned coal seams.
The carried out numerical modelling of LP 3 exploitation resulted in the 2D distributions of secondary displacement and
stress in the rock mass on the plane perpendicular to the mined
panel. To carefully investigate the stress and displacement values
at the depth of the studied earthquake, horizontal profiles were
created (Fig. 6a–d). The location of the west edge of panel no.
3 was marked by a dashed line. Note that studied event's hypocentre was located E13 m east from panel's west edge.
The biggest changes of all studied parameters can be observed
near panel's edge, close to the hypocentre. The exact values read
for hypocenter location are presented in Table 3.
Presented results clearly show that past and ongoing mining
exploitation has influenced the stress state at the depth of ML3.7
event. The observed stress changes are close to 1 MPa. An increase
of compressive vertical stress around panel's edge resulted in
vertical displacement pointed downwards. The area at the greater
distance from panel's edge axis, especially on its west side, experienced opposite effect – relaxation of compressive stress caused
vertical displacement pointed upwards. Such changing vertical
stress regime can promote failure on pre-existing almost vertical
planes of weakness. The obtained focal mechanism of analyzed
event – almost vertical reverse fault – seems to support the presented idea. Also, the amplitude of vertical displacement along the
Table 3
Stress changes in the ML 3.7 event's hypocentre. Negative values of stress indicate compression, positive – tension.
Primary stress
Vertical SYY
Horizontal SXX
Shear SXY
31.93 MPa
10.09 MPa
0.15 MPa
Secondary stress
33.17 MPa
8.87 MPa
0.50 MPa
Absolute difference
1.24 MPa (increase)
1.22 MPa (decrease)
0.65 MPa (caution- sign change)
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profile at earthquake's depth is of similar order as the slip on the
fault – 0.21 m.
Table 4
Time, energy and depth of eight strong seismic events which occurred within two
months after ML3.7 event.
No.
Date
ML
Energy [J]
Depth [m]
1
2
3
4
5
6
7
8
19.12.2009
31.12.2009
6.01.2010
13.01.2010
4.02.2010
5.02.2010
12.02.2010
19.02.2010
2.4
2.4
2.3
2.3
2.5
3.0
2.4
2.3
2 106
2 106
1.4 106
1.6 106
3.2 106
3.2 107
2.5 106
1.7 106
1179
1224
899
1159
1302
1290
1224
1093
7. Static stress transfer analysis
In this chapter we want to investigate whether the strong
mining event which occurred in the Bobrek mine affected the
distribution of following seismicity. For this purpose we performed static stress transfer analysis, using Coulomb failure
function 41:
∆CFF =∆τ +μ′∆σn,
(1)
where ∆τ and ∆σn are the shear and normal stress changes along
receiving fault, respectively and μ′ is the effective coefficient of
friction.42,43 A positive value of ∆CFF moves the fault towards
failure, which increases the likelihood of fault rupture.
The detailed analysis of ∆CFF influence on seismicity distribution has been already performed for copper ore mines in Poland 15.
The results indicated clear influence of Coulomb stress changes on
rate and location of following seismicity. In the case of the Bobrek
mine, the seismicity rate variation in time shows no increase in
activity right after the occurrence of ML3.7 event (Fig. 7). The mean
daily rate in the week preceding the event was 10 events/day,
whereas in the week following the event it was eight events/day.
However, looking only at the number of strong events of energy
4106 J ( 4ML2.2) before and after the event, an increase is observed. Within two months after studied earthquake, eight events
of energy 4106 J ( 4ML2.2) have occurred, including one of energy 4 107 J (4 ML2.7). For comparison, in the same period prior
to the studied earthquake, only three events of energy 4106 J had
occurred (none 4107 J). It may indicate that ML3.7 event caused
an increase in number of strong events. One of possible explanations could be either static or dynamic stress change. However,
eight mentioned events did not happen immediately after the
main one, which excludes the dynamic character of the triggering
effect44 (Table 4). Thus, to study the influence of ML3.7 event on
following ones, we performed the static stress transfer analysis
using Coulomb 3.0 software.45,46 Since mentioned strong events
could also change the stress distribution in studied area, we included their effect in the performed modelling.
The stress changes caused by exploitation promote vertical
rather than horizontal fault rupture. Thus, in case of ML3.7 event,
nodal plane 1 was accepted as the correct fault plane. Since data
from mine network were clipped, we could not investigate the
rupture's directivity. Hence, we assumed the event's hypocentre in
the middle of the fault plane. We relocated all eight strong events
and determined their focal mechanisms using methods described
in previous sections (Fig. 9). To choose one of the nodal planes we
relied on the results of Ref. 21. The author analyzed the focal
mechanisms of mine tremors occurring in USCB and identified
three types of seismic sources coupled to exploitation. In all three
types the fault planes dips were greater than 45°. We performed
our analysis accepting nodal planes which fit this pattern. The
ML3.7 event and two strong following ones were close both in time
and location – they occurred within eleven days and at hypocentral distance not exceeding 65 m. They had also similar mechanisms. Thus, we assumed that they represent continuing rupture
and set hypocenters of strong events 1 and 2 in the lower edges of
fault planes (Fig. 8). For the rest of strong events 3–8 we assumed
the hypocenter in the middle of nodal planes.
In the modelling we used the shear modulus and Poisson ratio
values of 2.2 GPa and 0.24, respectively, which correspond to the
mean values of those parameters for four floor strata.38 Fig. 9
presents the cumulative static stress changes due to ML3.7 and
following events on receiver planes and at depths of target events
1-8.
To investigate the influence of ML3.7 event on distribution of following weaker seismicity we divided the study area in three regions
A-C, representing different parts of the panel (Fig. 10). For each region
70
Number of events per day
60
50
40
30
16.12.2009
ML=3.7
20
10
0
1.11.2009
30.11.2009
29.12.2009
28.01.2010
Time of seismc activity
Fig. 7. Seismic activity in LP 3 in time.
27.02.2010
Fig. 8. Map of fault projections of the ML3.7 (star) and 1–8 strong events (circles).
All planes are presented as projections at the hypocentres depths.
12
M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
Fig. 9. Cumulative static stress changes due to ML3.7 and following events on receiver planes and at depths of target events 1–8 ((a–h)). ML3.7 event is marked by a black star,
subsequent strong events' epicentres are marked by black points. The rectangles represent mined-out areas, the position of front line of LP 3 corresponds to its actual
position on events' occurrence day.
M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
13
Fig. 10. Static stress changes due to ML3.7 event shown in three cross sections A-C. Seismicity following the event is shown as points coloured according to occurrence time:
black – events which occurred before strong event no. 2, green – before event no. 3, pink – before event no. 4, grey – before events no. 5 and 6, red – before event no. 7, orange
– before event no. 8, and points with no fill – after event no. 8. Strong events 1-8 are marked with stars coloured in the same manner as smaller events. An arrow indicates
exploitation direction. The dashed line in section A marks the limit between ∆CFF calculated for receiver planes defined for upper and lower part of the region. Note that
cross section A intersects the ML3.7 event's hypocentre.
we determined the representative focal mechanism based on observed events, separately for upper and lower part of the region. In
case of regions B and C, seismic events both in the upper and lower
part had similar mechanisms. It is consistent with the assumption
made in paragraph 4.1. In region A, seismic events closer to exploited
seam had different mechanisms from the deeper seismicity. This part
of LP is most affected by the exploitation geometry and stress changes
are the greatest (Fig. 6). It may explain changing focal mechanisms of
observed events. The fixed representative fault planes are as follows:
upper region A: Strike¼ 222°, Dip¼ 67°, Rake¼ 52°, lower region A:
Strike¼ 130°, Dip¼ 72°, Rake¼121°; region B: Strike¼ 265°, Dip¼ 76°,
Rake¼ 108°; and region C: Strike¼129°, Dip¼62°, Rake¼102°. We
performed the Coulomb stress change modelling accepting representative fault planes as receiver planes in each region separately.
Fig. 10 shows the results together with seismicity observed in each
region coloured according to the occurrence time.
The distribution of weaker seismic events shows distinct correlation with CFF stress changes, especially within the range of
lower depths of events. The seismicity which occurred within first
three weeks after ML3.7 event (black and green points in Fig. 10)
occurred mostly in two regions: below event's hypocenter and
much above it, close to mined coal seam. Both areas were influenced by positive stress changes. Also four strong events 3, 5,
6 and 7 occurred within positive stress changes caused by the
main and following strong events (Fig. 9).
Both performed analyzes showed that two strong events, no.
1 and 2, occurred within negative stress changes areas caused by
ML3.7 event. However, their close distance to event's fault plane
lets us suppose that they were the continuation of its rupture. The
actual stress change close to causative fault plane may be different
from the one presented here due to complex slip distribution in
the fault zone which cannot be well modelled without detailed
knowledge of source geometry.47
8. Discussion and conclusions
The presented results of ML3.7 event relocation, moment tensor
and spectral analysis show that it was strong and deep earthquake
with almost vertical fault plane and reverse faulting mechanism. It
clearly shows that the event could not be directly induced by
mining exploitation – the great depth of the event below exploited
seam, E500 m, and almost vertical fault plane, with strike at an
angle relative to panel's edges, do not match typical mining tremors observed in USCB and described in Ref. 21. The author
identified three types of seismic sources coupled to exploitation
based on seismicity of one of USCB mines with similar geology and
exploitation depth to the one analyzed in present study. The first
type are high energy tremors occurring in sandstone beds overlying the coal seam, with dominant normal faulting and fault
14
M. Kozłowska et al. / International Journal of Rock Mechanics & Mining Sciences 86 (2016) 5–15
planes at an angle of E 45° to the face line of LP. The second type
events are mostly of normal faulting type, parallel to the coal face,
within roof strata. The third type events have high explosive
component and are coupled to the failure of coal seam. High
energy seismic events occur mostly in roof strata, whereas low
energy events are coupled to coal seam. The analyzed event clearly
does not fit into any of these types.
The calculated stress drop of analyzed event – 26 MPa, is in the
range of both tectonic and induced earthquakes' values. There are
studies which present low stress drop values for mining induced
events,48,49 however, other studies present values similar to those
of natural earthquakes.50,51 Dubiński and Mutke52 estimated the
stress drops of earthquakes observed in USCB within limits of
0.028–32 MPa. Kwiatek et al.53 analyzed stress drops of microearthquakes with MW range from
4.1 to
0.8, recorded in a
South African mine. Their study revealed changing stress drops
between events close to the stope area and those at greater distances, within undamaged diorite dikes. The values varied from
E06.–1.5 MPa close to the stope area to E2–8 MPa within undamaged dike. It suggests that low values of stress drops are
linked to damaged zone surrounding the exploited area. The event
analyzed in this study occurred at a depth that was great enough
to assure undamaged rock and, as a result, stress drop comparable
to natural earthquakes.
Surprising is that after such strong deep event no clear aftershock sequence has been observed. This could be related to velocity of rupture and heterogeneity of the rock environment. The
general approximation of rupture velocity can be based on the
average relation of corner frequency for P-and S-wave spectra [Ref.
54 and the reference there]. Walter and Brune55 suggest that for
seismic events with very rapid rupture the corner frequency ratio
is around 1.4–1.5. For seismic events characterized by slow rupture, the discussed ratio is close to 1.0. In the case of the analyzed
strong event the corner frequency ratio, estimated from the records of regional network GRSS, has an average of 1.0, suggesting
slow rupture case. This would agree with other studies of mining
induced seismic events56,57 implying slower rupture velocities
than natural earthquakes of similar magnitudes.
Although we assumed that mining exploitation did not cause
fractures at the depth of E 500 m below exploited seam, we
analyzed its impact on the stress state at this depth. The numerical
modelling showed that past and ongoing exploitation influenced
the rock 500 m below. The magnitude of stress change at this
depth, close to the hypocentre, is around 1 MPa. For comparison,
modelled vertical stress change only 20 m below exploited seam,
in the event's epicenter, is close to 10 MPa, whereas below pillars
or intact rock it can even reach 40 MPa. It shows that mining
tremors which occur in close vicinity to the mine shaft are induced
by stress change much higher than the value observed at analyzed
target depth. Also, the event's stress drop is much higher than
stress change caused by mining. It means that the event could not
be directly induced by exploitation, but rather triggered.
The Coulomb stress change analysis was performed to investigate if the ML3.7 and subsequent strong events could influence the distribution of following seismicity. The obtained results,
combined with numerical modelling of exploitation effect, showed
that the magnitude of stress changes caused by mining E500 m
below its level are of the same order as Coulomb stress changes
due to ML3.7 event, i.e. around 1 MPa. Thus, the distribution of
seismicity at this level could have been driven by both exploitation
and coseismic stress changes. Fig. 10 supports this idea – the
seismicity which occurred within few weeks after ML3.7 event, at
the same level, followed positive stress changes. Two strong
events which occurred soon after the main one occurred within
negative stress changes, however, their hypocenters where very
close, mechanisms similar, so we assumed that they represent the
rupture on the same, continuing fault zone. The majority of other
strong events occurred within positive areas. The sudden change
of depth distribution of seismicity which occurred few weeks after
ML3.7 event was, according to Ref. 12, caused by mining front
crossing the axis of Bytom syncline, which at this point continued
as steeply dipping limb. The Coulomb stress change at this level
had magnitudes many times smaller than the exploitation influence. Thus we can conclude that the seismicity which occurred
after depths change, closer to mined seam, was induced by ongoing exploitation. However, as visible in Fig. 10 A, the ML3.7 event
could have influenced the tectonically vulnerable area close to
mined seam and promote its seismic activation.
The tectonic stress analysis presented in Ref. 12 supports the
hypothesis that ML3.7 event was the result of tectonic deformations caused by local geological structures. The complex analysis
presented in this study let us prove that the event was the tectonic
earthquake triggered by ongoing exploitation and that the distribution of following seismicity was affected by coupled natural,
exploitation-induced and coseismic stresses.
Acknowledgments
This work was done in the framework of the project IS-EPOS:
Digital Research Space of Induced Seismicity for EPOS Purposes
(POIG.02.03.00-14-090/13-00), funded by the National Centre for
Research and Development in the Operational Program Innovative
Economy in the years 2013–2015.
This work was financed by the Ministry of Science and Higher
Education of Poland under contracts no. 3841/E-41/M/2013 and
3841/E-41/S/2015. The authors like to thank KWK Bobrek and Coal
Company for sharing the data and support. Special thanks to K.
Stec and A. Pierzyna for consultations.
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