triggered earthquake
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Hydrofracturing, used for shale gas exploitation, may induce felt, even damaging earthquakes. On 15 June 2019, an Mw2.8 earthquake occurred, spatially correlated with the location of earlier exploratory hydrofracturing operations for shale gas in Wysin in Poland. However, this earthquake was atypical. Hydrofracturing-triggered seismicity mainly occurs during stimulation; occasionally, it continues a few months after completion of the stimulation. In Wysin, there were only two weaker events during two-month hydrofracturing and then 35 months of seismic silence until the mentioned earthquake occurred. The Wysin site is in Gdańsk Pomerania broader region, located on the very weakly seismically active Precambrian Platform. The historical documents, covering 1000 years, report no natural earthquakes in Gdańsk Pomerania. We conclude, therefore, that despite the never observed before that long lag time after stimulation, the Mw2.8 earthquake was triggered by hydrofracturing. It is possible that its unusually late occurrence in relation to the time of its triggering technological activity was caused by changes in stresses due to time-dependent deformation of reservoir shales. The Wysin earthquake determines a new time horizon for the effect of HF on the stress state, which can lead to triggering earthquakes. Time-dependent deformation and its induced stress changes should be considered in shall gas reservoir exploitation plans.

AbstractEarthquake swarms exhibit highly uncertain temporal behavior. We investigated the relationship between the swarm duration and the diffusivity of hypocenter migration for triggered earthquake swarms in northeastern Japan. These parameters were systematically estimated by applying a diffusion model and using a unified definition of time windows for the initial and final stages of swarm activity. This approach detected a clear negative correlation between the diffusivity and swarm durations. The relation follows a power-law with an exponent of $$-\,0.5$$ - 0.5 to $$-\,1.0$$ - 1.0 . Examination of published data confirmed that this relationship globally holds under various localities and tectonic environments. These results suggest that diffusivity, and by extension, crustal permeability and fluid viscosity play a key role in controlling the duration of the fluid-driven swarms.

On 30 October 2020, an Mw = 7.0 earthquake struck the eastern Aegean Sea. It triggered earthquake environmental effects (EEEs) on Samos Island detected by field surveys, relevant questionnaires, and Interferometric Synthetic Aperture Radar (InSAR) analysis. The primary EEEs detected in the field comprise coseismic uplift imprinted on rocky coasts and port facilities around Samos and coseismic surface ruptures in northern Samos. The secondary EEEs were mainly observed in northern Samos and include slope failures, liquefaction, hydrological anomalies, and ground cracks. With the contribution of the InSAR, subsidence was detected and slope movements were also identified in inaccessible areas. Moreover, the type of the surface deformation detected by InSAR is qualitatively identical to field observations. As regards the EEE distribution, effects were generated in all fault blocks. By applying the Environmental Seismic Intensity (ESI-07) scale, the maximum intensities were observed in northern Samos. Based on the results from the applied methods, it is suggested that the northern and northwestern parts of Samos constitute an almost 30-km-long coseismic deformation zone characterized by extensive primary and secondary EEEs. The surface projection of the causative offshore northern Samos fault points to this zone, indicating a depth–surface connection and revealing a significant role in the rupture propagation.

<p>Using long-term mining-induced earthquake statistics of the Khibiny Mountains (Kola Peninsula, Russia) we studied the spatial peculiarities of clustered seismicity. To declutter the earthquake catalog, we used the nearest neighbor method by Zaliapin and Ben-Zion, 2016, DOI: 10.1093/gji/ggw300. It was shown that the distribution of distances from triggering event to triggered earthquakes obeys a power law with a parameter independent of the trigger magnitude. This result is consistent with distribution of mainshock-aftershock distances obtained for tectonic seismicity by many researchers (e.g., Huc M., Main, DOI: 10.1029/2001JB001645; Felzer and Brodsky, DOI: 10.1785/0120030069; Richards-Dinger et al., DOI: 10.1038/nature09402). Combining the spatial power distribution and the law of earthquake productivity by Shebalin et al. 2020 (DOI: 10.1093/gji/ggaa252), confirmed for the seismicity of the Khibiny Mountains (Baranov et al., 2020, DOI: 10.1134/S1069351320030015) we derived a distribution of maximal distances from trigger to triggered earthquake.</p><p>Using this distribution, we suggest a probabilistic model of zone where triggered earthquakes are expected. The zone is a cylinder centered on the trigger hypocenter, its size (radius and height) depends on the probability of containing triggered earthquakes. The model validation was performed using Molchan’s error diagram. Applying the method of three strategies (Baranov and Shebalin, 2017, DOI: 10.1134/S1069351317020021) to the error diagram, we identified three limiting points on the error trajectory, corresponding to "soft," "neutral," and "hard" strategies. These strategies reflect the prediction importance.</p><p>The research was supported by Russian Foundation of Basic Research, Project No 19-05-00812.</p>

<p>The Corinth Rift (Greece) is one of the most seismically active regions in Europe and has been studied extensively during the past decades. It is characterized by normal faulting and extension rates between 6 and 15 mm yr−1 in an approximately N10E° direction. The seismicity of the area is continuously monitored by the stations of the Corinth Rift Laboratory Network (CRL Net). The availability of a dense permanent seismological network allows the extensive analysis of the seismic swarms which occur frequently. In this study, the September 2014 swarm located at the western part of the Corinth Gulf is analyzed. Initially, more than 4000 automatically located events, of a two month period, were relocated using the HYPODD algorithm, incorporating both catalogue and cross-correlation differential traveltimes. Consequently, the initial seismic cloud was separated into several smaller, densely concentrated clusters. Double difference relocation was also applied to 707 manually located events in order to investigate the Vp/Vs ratio variation, due to its sensitivity in pore fluids. The swarm’s parameters such as seismicity distribution and moment tensors were combined with the seismotectonic data of the area. The results indicate an initial activation of the Psathopyrgos normal fault; afterwards the seismicity extended both towards East and West, while most events occurred at the western part of the study area. The seismicity distribution revealed a main activation of the North – dipping faults. The seismicity migration with respect to pore pressure changes due to fluid movements was investigated through diffusivity calculations. The diffusivity value was found to be 4.5m<sup>2</sup>s<sup>-1</sup>, which is consistent with results of previous studies in the area. The results of the investigation of the fault- zone hydraulic behavior provide evidence for the fluid – triggered earthquake swarms and the related rock physical properties.</p>

An effective approach is introduced to predict the magnitude of reservoir-triggered earthquake (RTE), based on support vector machines (SVM) and fuzzy support vector machines (FSVM) methods. The main influence factors on RTE, including lithology, rock mass integrity, fault features, tectonic stress state, and seismic activity background in reservoir area, are categorized into 11 parameters and quantified by using analytical hierarchy process (AHP). Dataset on 100 reservoirs in China, including the 48 well-documented cases of RTE, are collected and used to train and validate the prediction models established with SVM and FSVM, respectively. Through numerical tests, it is found that both the SVM and FSVM models are effective in the prediction of the magnitude of RTE with high accuracy, provided that sufficient samples are collected. While the results of FSVM which is extended from SVM by introducing a fuzzy membership to reduce the influence of noises or outliers are found to be slightly less accurate than those of SVM in the current analysis of RTE cases. The reason might be attributed to the high discreteness of the sample data in the current study.

The possibility of reservoir-triggered earthquake occurrence in the Huoi Quang and Ban Chat hydropower dam area has been assessed based on studying and analyzing the relationships between the reservoir-triggered earthquake occurrence and the following factors: (1) the types of rocks underlying the reservoir; (2) the oscillating reservoir loads on faults in the reservoir area; (3) the incremental stress caused by reservoir loads; (4) the slip tendency of faults in the reservoir area; and (5) the Coulomb stress change of faults in the reservoir area. The results show that these factors have interactive effects and simultaneously contribute to the favorable conditions for reservoir-triggered earthquake occurrence. The Huoi Quang and Ban Chat hydropower reservoirs are located in the area of moderate seismicity; however, with the favorable conditions due to these five factors, reservoir-triggered earthquakes can possibly occur. If reservoir-triggered earthquakes occur, they will be concentrated around the Ban Chat hydropower dam area within a radius of 11 - 12 km and at a depth of about 6 ± 1 km.