The earthquake catalog of the Sakhalin Branch of Geophysical Survey of the Russian Academy of Sciences (SB GS RAS) from 2000 to 2020 was used [for example, Fokina, 2019] to study the change in the seismicity of the area, under the conditions of the intensification of open pit mining, in square of 48.4°-49.4° N and 141.7°-142.4° E, which includes both tectonic active structures and the territories of closed mines and areas of intensively developed open coal deposits (first of all, the Solntsevsky coal mine).
The ZMAP software suite [Wiemer, 2001] was used to analyze the catalog, by means of which the catalog declustering was carried out using the algorithm [Gardner, Knopoff, 1974] to exclude the influence of the aftershock sequences of 2000 and 2020 earthquakes on the recurrence graphs and the maps of epicenter positions for assessing the seismicity.
The result of dynamics of change in seismicity of the specified area during 20 years, after declustering, is presented in Figure 3.
It is worthy of note the increase in the seismicity of the area in 2012-2013, which coincides with the beginning of active development of the Solntsevsky Coal Mine and, accordingly, a significant increase in the volume of overburden operations at the open pit during this period. The recurrence graphs were plotted for the first and second decade (during the period of active development of the Solntsevsky coal mine) in order to compare the characteristics of the seismic regime in the studied area (Figure 4). The difference in a slope angle of the recurrence graph in the period of 2011-2020 is quite significant. The increase of a slope angle means more low energy earthquakes in the total number of events. According to [Yakovlev, 2013; Emanov et al., 2020], such b-values (about 1.0) are typical for anthropogenic activations in the areas with induced seismicity. For comparison, the graph on the left (Figure 4) shows the b-value inherent in natural seismicity.
Studying the change in the spatial distribution of earthquake epicenters in the period of 2000-2010 and 2011-2020 is also of interest (Figure 5).
As it can be seen, location of the epicenters of seismic events during 2000-2010 (on the left in the figure) is confined mainly to the fault structures, that testify to activity of the Krasnopol'evskiy fault, which is a part of the West Sakhalin deep fault, during this period [Prytkov, Vasilenko, 2006]. Contraction of the seismic events concentration zones to the mining areas, first of all to the Solntsevsky coal mine (on the right in the figure) is occurred in the second decade of the 21st century, while the fault remains active. Such a combination allows us to talk about an increase in seismicity of the region during the last years and change in its character from the natural to a mixed natural and technogenic.
It is necessary to pay attention to the seismic dislocations of the largest earthquakes of first (earthquake of 2000) and second (earthquake of 2020) decades in order to confirm the change in character of seismicity and the reasons of earthquake occurrence in the studied area. The focal mechanism of the earthquake in 2000 and its strongest aftershocks are identified in [Poplavskaya et al., 2011] as reverse faults (or normal faults), which is typical for most earthquakes occurring on Sakhalin Island. A movement in the focus of the earthquake of September 13, 2020, and its largest aftershock (Mw=4.5) has realized under the conditions of horizontal sublatitudinal extension and near-horizontal submeridional compression and is classified as strike-slip fault [Semenova et al., 2020]. Considering that the West Sakhalin fault manifests itself as a system of interlinked normal and reverse faults, the type of seismic dislocations of the earthquakes of September, 2020, is clearly unusual for the studied area. Configuration of the aftershocks of earthquake on September 13, 2020, with their sublatitudinal orientation indicates the influence of mining operations (movement of the rocks when overburden works) as a possible trigger effect, which has affected this earthquake occurrence. In this case, it is possible to draw a parallel with the strongest technogenic earthquakes on the Kola Peninsula, where the strike-slip character of displacements in earthquake foci was found to be caused by high tectonic stresses acting in the massifs, the presence of tectonic disturbances and voids formed during the preparation and extraction of ore deposits [Lovchikov, 2011 ]. The authors computed the mechanism of the seismic event of the same 2020, which occurred on the 3rd of January (20:46) with M=3.9, by means of the FOCMEC computation module integrated in the SEISAN complex of seismic programs [Ottemöller et al., 2011], in order to obtain an additional information about the earthquake character in the studied area. A total of 19 arrival signs of the P-wave first swings, registered on the vertical component of the seismic vibration recording, were used. According to the obtained solution, the type of seismic dislocation was a normal fault, which generally corresponds to the normal fault with a reverse component seismicity of the area [Dymovich et al., 2017]. The mechanisms of all earthquakes are computed at the IMGG FEB RAS and presented in Table 1.
We will further consider the features of seismic processes in the studied area during the last decade taking into account the effect of industrial blasting on the geological environment, that is carried out on the Solntsevsky coal mine when overburden working. SB GS RAS monitors and records such blasts using the equipment of the «Uglegorsk» seismic station, which is located in the immediate vicinity of the Solntsevsky coal mine territory. The «Uglegorsk» station is equipped with the modern digital equipment by the Güralp Systems: a Güralp CMG-6T broadband seismometer and a CMG-5TD accelerometer [Mishatkin et al., 2011]. Over 100 blasts at the mine are recorded annually. The methods used by SB GS RAS for identifying and determining the blasts do not pose any difficulties in general case and are described in detail [Morozov, 2008; Asming et al., 2010]. The ratio of the amplitudes of P and S waves (P/S), the ratio of Pg and Sg waves (Pg/Sg), record form, first arrival signs, presence of a surface wave are usually considered as the criteria for separating the blasts and earthquakes. In addition to above criteria, many studies show, that the spectral and temporal analysis of seismograms of the records of blasts and earthquakes is the most informative [Dobrynina, German, 2016]. It was found that the studied blasts are characterized with lower-frequency radiation compared to earthquakes. Other authors aimed the analysis of local seismic events spectrograms recorded in the areas with technogenic influence on the geological medium not only at identifying the blasts, but also at discriminating technogenic and tectonic seismic events. In particular, the recording spectra of technogenic earthquakes are noted to be usually in the frequency band up to 7 Hz, and the frequency of the maximum spectral density is 2-3 Hz, which is usually lower than that of tectonic earthquakes [Andruschenko et al., 2012].
In this regard, an attempt to determine the regularities of the parameters of the produced blasts and earthquakes by the dynamic parameters of the seismic events foci is taken below. The frequency composition of earthquakes and blasts (during the period from 2015 to 2020) was studied in order to determine the corner frequency (Fc) from the focal velocity spectrum (Figure 6).
It is known [Dobrynina, 2009] that the study of the earthquake focal parameters (including corner frequency) allows to better understand the nature of the processes of accumulation and discharge of tectonic stresses in seismically active regions. Correlation was obtained between the focal parameters and local magnitude. The results are presented in Table 2. Separate calculation of the corner frequency was performed for 100 randomly selected blasts. According to the calculation results, it was found that corner frequency values in the case of blasts are in the range of 1.0-3.0 Hz.
Table 2. Correlation between magnitude, corner frequency and distance from a seismic station for the earthquakes during the period of 2015-2020.
№
|
Year
|
Month
|
Day
|
Hour
|
Minute
|
Latitude, °
|
Longitude, °
|
Depth, km
|
magnitude
|
Corner frequency (Fc), Hz
|
Distance to seismic station, km
|
1
|
2015
|
Jan
|
18
|
8
|
51
|
48.65
|
142.11
|
10
|
3.2
|
2.5
|
37.7
|
2
|
2015
|
Feb
|
1
|
2
|
21
|
49.02
|
141.99
|
15
|
2.8
|
5
|
9.8
|
3
|
2015
|
Mar
|
19
|
13
|
5
|
49.21
|
141.97
|
10
|
2.8
|
5.5
|
15.9
|
4
|
2015
|
Mar
|
28
|
3
|
23
|
48.95
|
142.08
|
10
|
2.6
|
3
|
11.2
|
5
|
2015
|
Jul
|
5
|
17
|
18
|
48.81
|
142.17
|
7
|
2.8
|
5.5
|
26.1
|
6
|
2015
|
Jul
|
10
|
15
|
56
|
48.57
|
142.22
|
5
|
3.5
|
8
|
47.6
|
7
|
2015
|
Aug
|
6
|
4
|
40
|
48.55
|
142.13
|
11
|
3.6
|
3.5
|
46.7
|
8
|
2015
|
Aug
|
20
|
11
|
31
|
49.4
|
142.12
|
9
|
2.8
|
6.5
|
29.1
|
9
|
2015
|
Dec
|
17
|
16
|
34
|
48.8
|
142.03
|
10
|
2.7
|
5
|
24.5
|
10
|
2015
|
Dec
|
21
|
7
|
27
|
48.92
|
142.04
|
10
|
2.7
|
5.5
|
14
|
11
|
2015
|
Dec
|
28
|
10
|
15
|
48.66
|
142.18
|
10
|
3
|
7
|
38.7
|
12
|
2016
|
Jan
|
22
|
9
|
38
|
48.93
|
142.07
|
10
|
2.8
|
6
|
12.8
|
13
|
2016
|
Jan
|
31
|
3
|
16
|
48.94
|
142.03
|
10
|
2.7
|
5.5
|
12.6
|
14
|
2016
|
Feb
|
1
|
21
|
55
|
48.97
|
142.29
|
12
|
1.7
|
6
|
26.6
|
15
|
2016
|
Feb
|
2
|
9
|
27
|
48.93
|
142.17
|
8
|
1.5
|
6
|
17.3
|
16
|
2016
|
Feb
|
5
|
9
|
41
|
48.97
|
142.21
|
10
|
2.9
|
5.5
|
18.5
|
17
|
2016
|
Apr
|
8
|
12
|
36
|
48.65
|
142.35
|
8
|
3.7
|
5.5
|
49
|
18
|
2016
|
Jul
|
11
|
8
|
35
|
49.01
|
142.36
|
12
|
3.4
|
3
|
33.2
|
19
|
2016
|
Oct
|
22
|
8
|
56
|
48.64
|
142.35
|
10
|
3.1
|
6
|
49.6
|
20
|
2016
|
Nov
|
11
|
2
|
55
|
48.84
|
142.07
|
10
|
2.9
|
6
|
20.7
|
21
|
2016
|
Nov
|
18
|
8
|
57
|
48.53
|
141.93
|
10
|
2.7
|
6
|
50.2
|
22
|
2016
|
Nov
|
19
|
2
|
57
|
48.62
|
142.39
|
10
|
3.1
|
6
|
53.9
|
23
|
2017
|
Jan
|
4
|
16
|
59
|
48.87
|
142.04
|
10
|
2.9
|
8
|
18.3
|
24
|
2017
|
Feb
|
24
|
1
|
31
|
49.33
|
142.4
|
10
|
2
|
3.5
|
43.3
|
25
|
2017
|
Apr
|
1
|
17
|
38
|
49.01
|
141.83
|
11
|
3.3
|
6
|
26.9
|
26
|
2017
|
Apr
|
2
|
20
|
55
|
49.15
|
142.4
|
6
|
2.7
|
9
|
37.7
|
27
|
2017
|
Jun
|
6
|
23
|
50
|
48.94
|
142.23
|
14
|
3.6
|
6
|
21.8
|
28
|
2017
|
Nov
|
16
|
21
|
52
|
48.65
|
142.09
|
10
|
3.1
|
6
|
37.5
|
29
|
2018
|
Jan
|
27
|
17
|
19
|
48.46
|
142.18
|
8
|
2.9
|
7
|
55.5
|
30
|
2018
|
Aug
|
27
|
17
|
58
|
48.59
|
142.36
|
12
|
3
|
5.5
|
53.8
|
31
|
2018
|
Sep
|
3
|
2
|
34
|
48.58
|
142.16
|
13
|
3
|
8
|
44.8
|
32
|
2018
|
Dec
|
22
|
23
|
51
|
48.66
|
142.35
|
12
|
3.3
|
7
|
48.3
|
33
|
2019
|
Apr
|
1
|
17
|
54
|
48.91
|
142.32
|
3
|
2.9
|
10.5
|
31.8
|
34
|
2019
|
Apr
|
3
|
8
|
39
|
48.7
|
142.12
|
8
|
2.7
|
7
|
33.6
|
35
|
2020
|
Jan
|
3
|
20
|
46
|
48.88
|
141.92
|
6
|
3.9
|
5.5
|
23.7
|
36
|
2020
|
Jan
|
4
|
11
|
47
|
48.94
|
141.93
|
10
|
1.5
|
9.5
|
19.3
|
37
|
2020
|
Jan
|
27
|
17
|
41
|
48.49
|
142.3
|
5
|
2.4
|
9
|
57.7
|
38
|
2020
|
May
|
6
|
2
|
17
|
49.24
|
141.86
|
5
|
1.9
|
10.5
|
27
|
39
|
2020
|
May
|
11
|
23
|
15
|
48.77
|
142.19
|
5
|
1.7
|
10.5
|
30.2
|
40
|
2020
|
May
|
12
|
18
|
41
|
49.22
|
141.85
|
5
|
1.5
|
10.5
|
27.1
|
41
|
2020
|
Sep
|
5
|
14
|
10
|
48.83
|
142.4
|
11
|
2.5
|
10.5
|
43
|
42
|
2020
|
Sep
|
13
|
13
|
42
|
48.89
|
142.14
|
8
|
4.8
|
2.5
|
18.3
|
43
|
2020
|
Sep
|
13
|
14
|
9
|
48.91
|
142.04
|
6
|
4.5
|
3
|
14.9
|
The values obtained and the trend graph of frequency dependence on magnitude, that was constructed according to these data (Figure 7, left), generally correspond to the works [Sycheva, 2017; Dobrynina, 2009]. At the same time, it is obvious that several seismic events have the values of corner frequency anomalous for earthquakes (they are highlighted in color on the graph, and numbers from the table are specified for them). The same list includes the earthquake of September 13, 2020, as well as its main aftershock (no. 42 and no. 43 events in the table).
Figure 7 is fully consistent with the distribution of the aftershock cloud of the seismic event of September 13, 2020, when considering the position of these “anomalous” earthquakes epicenters. In addition, these events being at the same time confined to the fault structures are also located in the immediate vicinity of the Solntsevsky coal mine.
Thus, the method for assessing the nature of a seismic event through the study of corner frequency dependence on magnitude makes it possible to distinguish both the seismic events of tectonic character (for example, no. 35 event, the mechanism of which has been constructed above and corresponds to the idea about the nature of seismicity manifestations in this area), and the seismic events of potentially technogenic character, possibly having a strike-slip character of the mechanisms. It is necessary to create a local seismic network in the studied area in order to confirm this assumption.