ISSN  2096-3955

CN  10-1502/P

2021 Vol.5(6)

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Preface to the special collection of Induced Earthquakes
HongFeng Yang, XiaoWei Chen, Rebecca Harrington, YaJing Liu
2021, 5(6): 483-484. doi: 10.26464/epp2021057
Spatial-temporal evolution of injection-induced earthquakes in the Weiyuan Area determined by machine-learning phase picker and waveform cross-correlation
Wing Ching Jeremy Wong, JinPing Zi, HongFeng Yang, JinRong Su
2021, 5(6): 485-500. doi: 10.26464/epp2021055
Anthropogenic induced seismicity has been widely reported and investigated in many regions, including the shale gas fields in the Sichuan basin, where the frequency of earthquakes has increased substantially since the commencement of fracking in late 2014. However, the details of how earthquakes are induced remain poorly understood, partly due to lack of high-resolution spatial-temporal data documenting the evolution of such seismic events. Most previous studies have been based on a diffusive earthquake catalog constructed by routine methods. Here, however, we have constructed a high resolution catalog using a machine learning detector and waveform cross-correlation. Despite limited data, this new approach has detected one-third more earthquakes and improves the magnitude completeness of the catalog, illuminating the comprehensive spatial-temporal migration of the emerging seismicity in the target area. One of the clusters clearly delineates a potential unmapped fault trace that may have led to the Mw 5.2 in September 2019, by far the largest earthquake recorded in the region. The migration of the seismicity also demonstrates a pore-pressure diffusion front, suggesting additional constraints on the inducing mechanism of the region. The patterns of the highly clustered seismicity reconcile the causal link between the emerging seismicity and the activity of hydraulic fracturing in the region, facilitating continued investigation of the mechanisms of seismic induction and their associated risks.
Machine-learning-facilitated earthquake and anthropogenic source detections near the Weiyuan Shale Gas Blocks, Sichuan, China
PengCheng Zhou, William L. Ellsworth, HongFeng Yang, Yen Joe Tan, Gregory C. Beroza, MinHan Sheng, RiSheng Chu
2021, 5(6): 501-519. doi: 10.26464/epp2021053
Seismic hazard assessment and risk mitigation depend critically on rapid analysis and characterization of earthquake sequences. Increasing seismicity in shale gas blocks of the Sichuan Basin, China, has presented a serious challenge to monitoring and managing the seismicity itself. In this study, to detect events we apply a machine-learning-based phase picker (PhaseNet) to continuous seismic data collected between November 2015 and November 2016 from a temporary network covering the Weiyuan Shale Gas Blocks (SGB). Both P- and S-phases are picked and associated for location. We refine the velocity model by using detected explosions and earthquakes and then relocate the detected events using our new velocity model. Our detections and absolute relocations provide the basis for building a high-precision earthquake catalog. Our primary catalog contains about 60 times as many earthquakes as those in the catalog of the Chinese Earthquake Network Center (CENC), which used only the sparsely distributed permanent stations. We also measure the local magnitude and achieve magnitude completeness of ML0. We relocate clusters of events, showing sequential migration patterns overlapping with horizontal well branches around several well pads in the Wei202 and Wei204 blocks. Our results demonstrate the applicability of a machine-learning phase picker to a dense seismic network. The algorithms can facilitate rapid characterization of earthquake sequences.
Development of a new high resolution waveform migration location method and its applications to induced seismicity
SiYu Miao, HaiJiang Zhang, YuYang Tan, Ye Lin
2021, 5(6): 520-531. doi: 10.26464/epp2021056
Locating seismic events is a central task for earthquake monitoring. Compared to arrival-based location methods, waveform-based location methods do not require picking phase arrivals and are more suitable for locating seismic events with noisy waveforms. Among waveform-based location methods, one approach is to stack different attributes of P and S waveforms around arrival times corresponding to potential event locations and origin times, and the maximum stacking values are assumed to indicate the correct event location and origin time. In this study, to obtain a high-resolution location image, we improve the waveform-based location method by applying a hybrid multiplicative imaging condition to characteristic functions of seismic waveforms. In our new stacking method, stations are divided into groups; characteristic functions of seismic waveforms recorded at stations in the same group are summed, and then multiplied among groups. We find that this approach can largely eliminate the cumulative effects of noise in the summation process and thus improve the resolution of location images. We test the new method and compare it to three other stacking methods, using both synthetic and real datasets that are related to induced seismicity occurring in petroleum/gas production. The test results confirm that the new stacking method can provide higher-resolution location images than those derived from currently used methods.
Determination of the local magnitudes of small earthquakes using a dense seismic array in the Changning−Zhaotong Shale Gas Field, Southern Sichuan Basin
Wen Yang, GuoYi Chen, LingYuan Meng, Yang Zang, HaiJiang Zhang, JunLun Li
2021, 5(6): 532-546. doi: 10.26464/epp2021026
With the development of unconventional shale gas in the southern Sichuan Basin, seismicity in the region has increased significantly in recent years. Though the existing sparse regional seismic stations can capture most earthquakes with \begin{document}$ {M}_{\mathrm{L}}\ge 2.5 $\end{document}, a great number of smaller earthquakes are often omitted due to limited detection capacity. With the advent of portable seismic nodes, many dense arrays for monitoring seismicity in the unconventional oil and gas fields have been deployed, and the magnitudes of those earthquakes are key to understand the local fault reactivation and seismic potentials. However, the current national standard for determining the local magnitudes was not specifically designed for monitoring stations in close proximity, utilizing a calibration function with a minimal resolution of 5 km in the epicentral distance. That is, the current national standard tends to overestimate the local magnitudes for stations within short epicentral distances, and can result in discrepancies for dense arrays. In this study, we propose a new local magnitude formula which corrects the overestimated magnitudes for shorter distances, yielding accurate event magnitudes for small earthquakes in the Changning−Zhaotong shale gas field in the southern Sichuan Basin, monitored by dense seismic arrays in close proximity. The formula is used to determine the local magnitudes of 7,500 events monitored by a two-phased dense array with several hundred 5 Hz 3C nodes deployed from the end of February 2019 to early May 2019 in the Changning−Zhaotong shale gas field. The magnitude of completeness (\begin{document}$ {M}_{\mathrm{C}} $\end{document}) using the dense array is −0.1, compared to \begin{document}$ {M}_{\mathrm{C}} $\end{document} 1.1 by the sparser Chinese Seismic Network (CSN). In addition, using a machine learning detection and picking procedure, we successfully identify and process some 14,000 earthquakes from the continuous waveforms, a ten-fold increase over the catalog recorded by CSN for the same period, and the \begin{document}$ {M}_{\mathrm{C}} $\end{document} is further reduced to −0.3 from −0.1 compared to the catalog obtained via manual processing using the same dense array. The proposed local magnitude formula can be adopted for calculating accurate local magnitudes of future earthquakes using dense arrays in the shale gas fields of the Sichuan Basin. This will help to better characterize the local seismic risks and potentials.
Teleseismic waves reveal anisotropic poroelastic response of wastewater disposal reservoir
Andrew J Barbour, Nicholas M Beeler
2021, 5(6): 547-558. doi: 10.26464/epp2021034
Connecting earthquake nucleation in basement rock to fluid injection in basal, sedimentary reservoirs, depends heavily on choices related to the poroelastic properties of the fluid-rock system, thermo-chemical effects notwithstanding. Direct constraints on these parameters outside of laboratory settings are rare, and it is commonly assumed that the rock layers are isotropic. With the Arbuckle wastewater disposal reservoir in Osage County, Oklahoma, high-frequency formation pressure changes and collocated broadband ground velocities measured during the passing of large teleseismic waves show a poroelastic response of the reservoir that is both azimuthally variable and anisotropic; this includes evidence of static shifts in pressure that presumably relate to changes in local permeability. The azimuthal dependence in both the static response and shear coupling appears related to tectonic stress and strain indicators such as the orientations of the maximum horizontal stress and faults and fractures. Using dynamic strains from a nearby borehole strainmeter, we show that the ratio of shear to volumetric strain coupling is ~0.41 which implies a mean Skempton's coefficient of \begin{document}$ A = 0.24 $\end{document} over the plausible range of the undrained Poisson's ratio. Since these observations are made at relatively low confining pressure and differential stress, we suggest that the hydraulically conductive fracture network is a primary control on the coupling between pore pressure diffusion and elastic stresses in response to natural or anthropogenic sources.
3D geomechanical modeling of the response of the Wilzetta Fault to saltwater disposal
Behzad Hemami, Shahla Feizi Masouleh, Ahmad Ghassemi
2021, 5(6): 559-580. doi: 10.26464/epp2021054
From 2009 to 2017, parts of Central America experienced marked increase in the number of small to moderate-sized earthquakes. For example, three significant earthquakes (~Mw 5) occurred near Prague, Oklahoma, in the U. S. in 2011. On 6 Nov 2011, an Mw 5.7 earthquake occurred in Prague, central Oklahoma with a sequence of aftershocks. The seismic activity has been attributed to slip on the Wilzetta fault system. This study provides a 3D fully coupled poroelastic analysis (using FLAC3D) of the Wilzetta fault system and its response to saltwater injection in the underpressured subsurface layers, especially the Arbuckle group and the basement, to evaluate the conditions that might have led to the increased seismicity. Given the data-limited nature of the problem, we have considered multiple plausible scenarios, and use the available data to evaluate the hydromechanical response of the faults of interest in the study area. Numerical simulations show that the injection of large volumes of fluid into the Arbuckle group tends to bring the part of the Wilzetta faults in Arbuckle group and basement into near-critical conditions.
Non-storm erosion of MeV electron outer radiation belt down to L* < 4.0 associated with successive enhancements of solar wind density
Ying Xiong, Lun Xie, SuiYan Fu, BinBin Ni, ZuYin Pu
2021, 5(6): 581-591. doi: 10.26464/epp2021051
We report an unusual non-storm erosion event of outer zone MeV electron distribution during three successive solar wind number density enhancements (SWDEs) on November 27−30, 2015. Loss of MeV electrons and energy-dependent narrowing of electron pitch angle distributions (PAD) first developed at L* = 5.5 and then moved down to L* < 4. According to the evolution of the electron phase space density (PSD) profile, losses of electrons with small pitch angles at L* > 4 during SWDE1 are mainly due to outward radial diffusion. However during SWDE2&3, scattering loss due to EMIC waves is dominant at 4 < L* < 5. As for electrons with large pitch angles, outward radial diffusion is the primary loss mechanism throughout all SWDEs which is consistent with the incursion of the Last Closed Drift Shell (LCDS). The inner edge of EMIC wave activity moved from L* ~5 to L* ~4 and from L ~6.4 to L ~4.2 from SWDE1 to SWDE2&3, respectively, observed by Van Allen Probes and by ground stations. This is consistent with the inward penetration of anisotropic energetic protons from L* = 4.5 to L* = 3.5, suggesting that the inward extension of EMIC waves may be driven by the inward injection of anisotropic energetic protons from the dense plasma sheet.
Study on electron stochastic motions in the magnetosonic wave field: Test particle simulations
Kai Fan, XinLiang Gao, QuanMing Lu, Shui Wang
2021, 5(6): 592-600. doi: 10.26464/epp2021052
Using the test particle simulation method, we investigate the stochastic motion of electrons with energy of 300 keV in a monochromatic magnetosonic (MS) wave field. This study is motivated by the violation of the quasi-linear theory assumption, when strong MS waves (amplitude up to ~1 nT) are present in the Earth’s magnetosphere. First, electron motion can become stochastic when the wave amplitude exceeds a certain threshold. If an electron initially resonates with the MS wave via bounce resonance, as the bounce resonance order increases, the amplitude threshold of electron stochastic motion increases until it reaches the peak at about the 11th order in our study, then the amplitude threshold slowly declines. Further, we find that the coexistence of bounce and Landau resonances between electrons and MS waves will significantly reduce the amplitude threshold. In some cases, the electron motion can become stochastic in the field of an MS wave with amplitudes below 1 nT. Regardless, if neither the bounce nor Landau resonance condition is satisfied initially, then the amplitude threshold of stochastic motion shows an increasing trend for lower frequencies and a decreasing trend for higher frequencies, even though the amplitude threshold is always very large (> 5 nT). Our study suggests that electron stochastic motion should also be considered when modeling electron dynamics regulated by intense MS waves in the Earth’s magnetosphere.