Background Seismicity Research Articles

Spatiotemporal Analysis of the Background Seismicity Identified by Different Declustering Methods in Northern Algeria and Its Vicinity

The main purpose of this paper was to, for the first time, analyse the spatiotemporal features of the background seismicity of Northern Algeria and its vicinity, as identified by different declustering methods (specifically: the Gardner and Knopoff, Gruenthal, Uhrhammer, Reasenberg, Nearest Neighbour, and Stochastic Declustering methods). Each declustering method identifies a different declustered catalogue, namely a different subset of the earthquake catalogue that represents the background seismicity, which is usually expected to be a realisation of a homogeneous Poisson process over time, though not necessarily in space. In this study, a statistical analysis was performed to assess whether the background seismicity identified by each declustering method has the spatiotemporal properties typical of such a Poisson process. The main statistical tools of the analysis were the coefficient of variation, the Allan factor, the Markov-modulated Poisson process (also named switched Poisson process with multiple states), the Morisita index, and the L–function. The results obtained for Northern Algeria showed that, in all cases, temporal correlation and spatial clustering were reduced, but not totally eliminated in the declustered catalogues, especially at long time scales. We found that the Stochastic Declustering and Gruenthal methods were the most successful methods in reducing time correlation. For each declustered catalogue, the switched Poisson process with multiple states outperformed the uniform Poisson model, and it was selected as the best model to describe the background seismicity in time. Moreover, for all declustered catalogues, the spatially inhomogeneous Poisson process did not fit properly the spatial distribution of earthquake epicentres. Hence, the assumption of stationary and homogeneous Poisson process, widely used in seismic hazard assessment, was not met by the investigated catalogue, independently from the adopted declustering method. Accounting for the spatiotemporal features of the background seismicity identified in this study is, therefore, a key element towards effective seismic hazard assessment and earthquake forecasting in Algeria and the surrounding area.

Acoustic Impedance Inversion from Seismic Imaging Profiles Using Self Attention U-Net

Seismic impedance inversion is a vital way of geological interpretation and reservoir investigation from a geophysical perspective. However, it is inevitably an ill-posed problem due to the noise or the band-limited characteristic of seismic data. Artificial neural network have been used to solve nonlinear inverse problems in recent years. This research obtained an acoustic impedance profile by feeding seismic profile and background impedance into a well-trained self-attention U-Net. The U-Net got convergence by appropriate iteration, and the output predicted the impedance profiles in the test. To value the quality of predicted profiles from different perspectives, e.g., correlation, regression, and similarity, we used four kinds of indexes. At the same time, our results were predicted by conventional methods (e.g., deconvolution with recursive inversion, and TV regularization) and a 1D neural network was calculated in contrast. Self-attention U-Net showed to be robust to noise and does not require prior knowledge. Furthermore, spatial continuity is also better than deconvolution, regularization, and 1D deep learning methods in contrast. The U-Net in this paper is a type of full convolutional neural network, so there are no limits to the shape of the input. Based on this, a large impedance profile can be predicted by U-Net, which is trained by a patchy training dataset. In addition, this paper applied the proposed method to the field data obtained by the Ceduna survey without any label. The predictions prove that this well-trained network could be generalized from synthetic data to field data.

Lowering the vertical component seismic noise-floor in the normal-mode band by frequency-dependent air-pressure corrections

SUMMARY Contrary to popular belief in seismology, the vertical component seismic background level of Earth’s body in the normal-mode band is lower than current low-noise models would indicate. With a correction of atmospherically induced disturbances the low-noise level of the vertical component of the STS-1 at Black Forest Observatory (BFO) is reduced below the Peterson low noise model (NLNM). We demonstrate this with a moving window analysis (MWA) of 10 yr of data in the normal-mode band between 0.2 and 2 mHz. The 5th percentile low-noise level for the data initially is at the level of the NLNM. We lower this by 8 dB at the frequency of 0S2 (0.31 mHz) by partially correcting the seismometer recording in the time domain for disturbances caused by mass fluctuations in the atmosphere. The disturbances are estimated by the frequency dependent ‘improved Bouguer plate model’ (IBPM, defined by asymptotic admittance αDC and notch-frequency fn) from a recording of local air-pressure. In more than 90 per cent of the time windows of the MWA the signal level is lowered when using a priori set IBPM-parameters ($\alpha _{\text{DC}}= -3.5\, {\rm nm\, s}^{-2}\, {\rm hPa}^{-1}$, $f_{\text{n}}=2.25\, {\rm mHz}$). In 50 per cent of the time windows the background level at the frequency of 0S2 is reduced by at least 6 dB. With a priori set IBPM-parameters the level of the 1st percentile is lowered by up to 16 dB for windows of $1\, {\rm d}$ length and by 13 dB for windows of $7\, {\rm d}$ length. Overall, there is little additional benefit from optimizing the IBPM-parameters per time window. If optimized per time window, the parameters show a slight annual variation which apparently compensates for systematic deviations of the dynamics of the atmosphere from the simple considerations of the IBPM-model. By application of the correction procedure and with seismic sensors of sufficiently low self-noise, the range of observations for signals from Earth’s body can be extended to below current low-noise models at frequencies below 2 mHz.

Time Domain Source Parameter Estimation of Natural and Man-Induced Microearthquakes at the Geysers Geothermal Field

Water injection in geothermal areas is the preferential strategy to sustain the natural production of geothermal resources. In this context, monitoring microearthquakes is a fundamental tool to track changes in the reservoirs in terms of soil composition, response to injections, and resource exploitation with space and time. Therefore, refined source characterization is crucial to better estimate the size, source mechanism, and rupture process of microearthquakes, as they are possibly related to industrial activities, and to identify any potential variation in the background seismicity. Standard approaches for source parameter estimation are ordinarily based on the modelling of Fourier displacement spectra and its characteristic parameters: the low-frequency spectral level and corner frequency. Here, we apply an innovative time domain technique that uses the curves of P-wave amplitude vs. time along the seismogram. This methodology allows estimation of seismic moment, source radius, and stress release from the plateau level and the corner time of the average logarithm of P-wave displacement versus time with the assumption of a triangular moment rate function, uniform rupture speed, and a constant/frequency-independent Q-factor. In the current paper, this time domain methodology is implemented on a selected catalog of microearthquakes consisting of 83 events with a moment magnitude ranging between 1.0 and 1.5 that occurred during a 7-year period (2007–2014) of fluid extraction/injection around Prati-9 and Prati-29 wells at The Geysers geothermal field. The results show that the time domain technique provides accurate seismic moment (moment magnitude) and rupture duration/radius estimates of microearthquakes down to the explored limit (M 1) while accounting for the anelastic attenuation effect in the radiated high-frequency wavefield. The retrieved source radius vs. moment scaling is consistent with a self-similar, constant stress drop scaling model, which proves an appropriate attenuation correction and the validity of the assumed, triangular moment rate function for microearthquake ruptures. Two alternative mechanical models are proposed to explain the observed difference (about two orders of magnitude) in the retrieved average stress release estimates between the time and frequency domain methods. We argue that the two quantities may not refer to the same physical quantity representing the stress release of earthquake ruptures. Either the smaller stress release values from the time domain method may indicate a larger fracture area (by a factor of 20) radiating the observed P-waveforms than the one estimated from the corner frequencies, or the frequency domain estimate is a proxy for dynamic stress release while the time domain is more representative of the static release. The latter is associated with a much lower dynamic friction value than static friction value at the fault during the rupture process.

Question-Driven Ensembles of Flexible ETAS Models

AbstractThe development of new earthquake forecasting models is often motivated by one of the following complementary goals: to gain new insights into the governing physics and to produce improved forecasts quantified by objective metrics. Often, one comes at the cost of the other. Here, we propose a question-driven ensemble (QDE) modeling approach to address both goals. We first describe flexible epidemic-type aftershock sequence (ETAS) models in which we relax the assumptions of parametrically defined aftershock productivity and background earthquake rates during model calibration. Instead, both productivity and background rates are calibrated with data such that their variability is optimally represented by the model. Then we consider 64 QDE models in pseudoprospective forecasting experiments for southern California and Italy. QDE models are constructed by combining model parameters of different ingredient models, in which the rules for how to combine parameters are defined by questions about the future seismicity. The QDE models can be interpreted as models that address different questions with different ingredient models. We find that certain models best address the same issues in both regions, and that QDE models can substantially outperform the standard ETAS and all ingredient models. The best performing QDE model is obtained through the combination of models allowing flexible background seismicity and flexible aftershock productivity, respectively, in which the former parameterizes the spatial distribution of background earthquakes and the partitioning of seismicity into background events and aftershocks, and the latter is used to parameterize the spatiotemporal occurrence of aftershocks.

Relative Afterslip Moment Does Not Correlate With Aftershock Productivity: Implications for the Relationship Between Afterslip and Aftershocks

AbstractAseismic afterslip has been proposed to drive aftershock sequences. Both afterslip moment and aftershock number broadly increase with mainshock size, but can vary beyond this scaling. We examine whether relative afterslip moment (afterslip moment/mainshock moment) correlates with several key aftershock sequence characteristics, including aftershock number and cumulative moment (both absolute and relative to mainshock size), seismicity rate change, b‐value, and Omori decay exponent. We select Mw ≥ 4.5 aftershocks for 41 tectonically varied mainshocks with available afterslip models. Against expectation, relative afterslip moment does not correlate with tested aftershock characteristics or background seismicity rate. Furthermore, adding afterslip moment to mainshock moment does not improve predictions of aftershock number. Our findings place useful empirical constraints on the link between afterslip and potentially damaging Mw ≥ 4.5 aftershocks and raise questions regarding the role afterslip plays in aftershock generation.

Multiscale recurrent-guided denoising network for distributed acoustic sensing-vertical seismic profile background noise attenuation

In recent years, distributed optical fiber acoustic sensing (DAS) has emerged as a novel seismic acquisition technique. Compared with conventional hydrophones and geophones of microelectromechanical systems, DAS has an advantage in terms of acquisition geometry, such as low-cost and high-density observations. However, the collected DAS records always suffer from various types of noise, which poses challenges for subsequent processing. Thus, deep learning-based solutions have addressed the attenuation of seismic background noise. Denoising networks can provide excellent denoising results. Nonetheless, the architectures of these networks are relatively simple, which may result in degeneration when confronted with the complex DAS background noise. To effectively attenuate complex noise, a novel multiscale network called recurrent-guided self-enhanced attention network (RGSA-Net) is developed for complex seismic data processing. Specifically, the backbone of RGSA-Net uses a conventional feedforward neural network to preliminarily extract the potential features. Meanwhile, multiscale modules, inspired by the recurrent-guided scheme, are used to enhance the contour information. On this basis, a self-enhanced attention module is applied to fuse the multiscale features and further reinforce the effective information, thereby improving the noise attenuation capability. Synthetic and field experiments demonstrate that RGSA-Net indicates promise in complex noise attenuation and weak upgoing signal recovery.

Estimation of Damage Scenarios in Mexico City Caused by Nearby Crustal Earthquakes

ABSTRACT Mexico City has sustained severe damage from earthquakes located in the subduction zone and within the subducted Cocos plate. The city lies in the trans-Mexican volcanic belt (TMVB). Earthquakes in the TMVB are relatively infrequent but have reached Mw>6. A recent Mw 6.9 crustal earthquake occurred in 1912, 80 km from Mexico City. Damage scenarios are estimated for two hypothetical crustal earthquakes located 40 and 80 km from the city. The seismic sources represent hazard-critical earthquakes and are based on historical seismicity and on the geological record. The probability distribution of ground acceleration is determined by ground-motion models (GMMs) from similar tectonic regions. Site effects are included to account for the geotechnical zonation of the city, and vulnerability curves are calculated for residential buildings in the cadastral record of Mexico City. The results show that an earthquake near the 1912 earthquake would produce accelerations of 37 and 148 cm/s2 on firm ground and in the lake region, respectively. In this scenario, damage is concentrated in buildings 1-2 stories high located near the transition zone. The earthquake located ∼40 km from Mexico City shows accelerations of 79 and 318 cm/s2 on firm ground and in the lake region, respectively. This scenario concentrated potential damage in buildings 1-2 stories high and broadly distributed in the region underlain by soft clays. Under both scenarios, no damage is expected in buildings higher than ∼11 stories. A deterministic approach using two potential seismic sources instead of a probabilistic seismic hazard model is used because of the lack of background seismicity and the unknown recurrence times of events in the TMVB. The results show very different damage patterns for crustal earthquakes. The two scenarios presented here may be useful for decision makers and insurance companies to estimate physical damage and to implement mitigation programs.

Comparing and integrating artificial intelligence and similarity search detection techniques: application to seismic sequences in Southern Italy

SUMMARYUnderstanding mechanical processes occurring on faults requires detailed information on the microseismicity that can be enhanced today by advanced techniques for earthquake detection. This problem is challenging when the seismicity rate is low and most of the earthquakes occur at depth. In this study, we compare three detection techniques, the autocorrelation FAST, the machine learning EQTransformer, and the template matching EQCorrScan, to assess their ability to improve catalogues associated with seismic sequences in the normal fault system of Southern Apennines (Italy) using data from the Irpinia Near Fault Observatory (INFO). We found that the integration of the machine learning and template matching detectors, the former providing templates for the cross-correlation, largely outperforms techniques based on autocorrelation and machine learning alone, featuring an enrichment of the automatic and manual catalogues of factors 21 and 7, respectively. Since output catalogues can be polluted by many false positives, we applied refined event selection based on the cumulative distribution of their similarity level. We can thus clean up the detection lists and analyse final subsets dominated by real events. The magnitude of completeness decreases by more than one unit compared to the reference value for the network. We report b-values associated with sequences smaller than the average, likely corresponding to larger differential stresses than for the background seismicity of the area. For all the analysed sequences, we found that main events are anticipated by foreshocks, indicating a possible preparation process for main shocks at subkilometric scales.

Improvements to seismicity forecasting based on a Bayesian spatio-temporal ETAS model

The epidemic-type aftershock sequence (ETAS) model provides an effective tool for predicting the spatio-temporal evolution of aftershock clustering in short-term. Based on this model, a fully probabilistic procedure was previously proposed by the first two authors for providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval. This procedure exploited the versatility of the Bayesian inference to adaptively update the forecasts based on the incoming information provided by the ongoing seismic sequence. In this work, this Bayesian procedure is improved: (1) the likelihood function for the sequence has been modified to properly consider the piecewise stationary integration of the seismicity rate; (2) the spatial integral of seismicity rate over the whole aftershock zone is calculated analytically; (3) background seismicity is explicitly considered within the forecasting procedure; (4) an adaptive Markov Chain Monte Carlo simulation procedure is adopted; (5) leveraging the stochastic sequences generated by the procedure in the forecasting interval, the N-test and the S-test are adopted to verify the forecasts. This framework is demonstrated and verified through retrospective early forecasting of seismicity associated with the 2017–2019 Kermanshah seismic sequence activities in western Iran in two distinct phases following the main events with Mw7.3 and Mw6.3, respectively.

A new data-domain reflection full-waveform inversion method based on common-image-point gathers

The migration velocity analysis (MVA) based on the common-image gathers (CIGs) in the image domain is an effective approach for evaluating the seismic background velocity, a crucial index for the full-waveform inversion (FWI) and migration. Compared with cumbersome conventional MVA methods, differential semblance optimization (DSO) is a variation of image-domain wavefield tomography that avoids interactive manual picking but increases the computation cost tremendously. In recent years, the reflection waveform inversions have been studied in depth to construct the background velocity, matching reflection travel time or waveform in the data domain, which requires expensive Born simulations based on accurate imaging results. This study performs a new reflection full-waveform inversion method in the image domain based on the flatness of arbitrarily selected common-image-point (CIP) gathers and their Born simulations. According to the relationship between imaging and background model, the flatness of CIP gathers under the L1 norm is measured. Afterwards, we construct the objective function to update the background model without manual picking or wave-equation migration in an extended dimension. The inversion accuracy is controlled by balancing the density of the imaging points and the computation capability. The whole procedure is implemented in the frequency domain, so the main computation comes from the LU decomposition in the frequency-domain wave-equation simulation, in which way, the proposed data-domain reflection full-waveform inversion achieves complete automation with lower costs. The objective function analysis shows a better convex, proving the weak dependence on the starting model of this method. Besides, synthetic experiments verify the validity and the field data test demonstrates its effectiveness.

The September 26, 2019 Silivri Earthquake (MW=5.6), NW Türkiye

The September 26, 2019 Silivri earthquake (MW=5.6-5.8) occurred along the North Anatolian Fault Zone segments extending beneath the Marmara Sea. In the present study the teleseismic P waveforms and 20-year long background seismicity of the earthquake (MW=5.6-5.8) have been analyzed. Point-source inversion of the teleseismic P waveforms revealed that the earthquake was due to oblique faulting and released a seismic moment of 3.2 x 1017 Nm (MW=5.6). The frequency-magnitude distributions (FMDs) for the background seismicity have been calculated after the 1999 İzmit earthquake. The considerable decrease of b-value of the FMD before the 2019 Silivri earthquake has been interpreted as stress increase along the fault segments.

Detection of Spatial and Temporal Stress Changes During the 2016 Central Italy Seismic Sequence by Monitoring the Evolution of the Energy Index

AbstractWe consider approximately 23,000 microearthquakes that occurred between 2005 and 2016 in central Italy to investigate the crustal strength before and after the three largest earthquakes of the 2016 seismic sequence (i.e., the Mw 6.2, 24 August 2016 Amatrice, the Mw 6.1, 26 October 2016 Visso, and the Mw 6.5, 30 October 2016 Norcia earthquakes). We monitor the spatiotemporal deviations of observed radiated energy, ES, with respect to theoretical values, ESt, derived from a scaling model between ES and M0 calibrated for background seismicity in central Italy. These deviations, defined here as Energy Index (EI), allow us to identify in the years following the Mw 6.1, 2009 L’Aquila earthquake a progressive evolution of the dynamic properties of microearthquakes and the existence of high EI patches close to the Amatrice earthquake hypocenter. We show the existence of a crustal volume with high EI even before the Mw 6.5 Norcia earthquake. Our results agree with the previously suggested hypothesis that the Norcia earthquake nucleated at the boundary of a large patch, highly stressed by the two previous mainshocks of the sequence. We highlight the mainshocks interaction both in terms of EI and of the mean loading shear stress associated to microearthquakes occurring within the crustal volumes comprising the mainshock hypocenters. Our study shows that the dynamic characteristics of microearthquakes can be exploited as beacons of stress change in the crust and thus be exploited to monitor the seismic hazard of a region and help to intercept the preparation phase of large earthquakes.

Regional Characteristics of Observable Foreshocks

Abstract Measures of foreshock occurrence are systematically examined using earthquake catalogs for eight regions (Italy, southern California, northern California, Costa Rica, Onshore Japan, Alaska, Turkey, and Greece) after imposing a magnitude ≥3.0 completeness level. Foreshocks are identified using three approaches: a magnitude-dependent space + fixed-time windowing method, a nearest-neighbor clustering method, and a modified magnitude-dependent space + variable-time windowing method. The method with fixed-time windows systematically yields higher counts of foreshocks than the other two clustering methods. We find similar counts of foreshocks across the three methods when the magnitude aperture is equalized by including only earthquakes in the magnitude range M*−2≤ M< M*, in which M* is the mainshock magnitude. For most of the catalogs (excluding Italy and southern California), the measured b-values of the foreshocks of all region-specific mainshocks are lower by 0.1–0.2 than b-values of respective aftershocks. Allowing for variable-time windows results in relatively high probabilities of having at least one foreshock in Italy (∼43%–56%), compared to other regional catalogs. Foreshock probabilities decrease to 14%–41% for regions such as Turkey, Greece, and Costa Rica. Similar trends are found when requiring at least five foreshocks in a sequence to be considered. Estimates of foreshock probabilities for each mainshock are method dependent; however, consistent regional trends exist regardless of method, with regions such as Italy and southern California producing more observable foreshocks than Turkey and Greece. Some regions with relatively high background seismicity have comparatively low probabilities of detectable foreshock activity when using methods that account for variable background, possibly due to depletion of near-failure fault conditions by background activity.

Microseismic data denoising in the sychrosqueezed domain by integrating the wavelet coefficient thresholding and pixel connectivity

SUMMARY Microseismic monitoring is crucial for risk assessment in mining, fracturing and excavation. In practice, microseismic records are often contaminated by undesired noise, which is an obstacle to high-precision seismic locating and imaging. In this study, we develop a new denoising method to improve the signal-to-noise ratio (SNR) of seismic signals by combining wavelet coefficient thresholding and pixel connectivity thresholding. First, the pure background noise range in the seismic record is estimated using the ratio of variance (ROV) method. Then, the synchrosqueezed continuous wavelet transform (SS-CWT) is used to project the seismic records onto the time–frequency plane. After that, the wavelet coefficient threshold for each frequency is computed based on the empirical cumulative distribution function (ECDF) of the coefficients of the pure background noise. Next, hard thresholding is conducted to process the wavelet coefficients in the time–frequency domain. Finally, an image processing approach called pixel connectivity thresholding is introduced to further suppress isolated noise on the time–frequency plane. The wavelet coefficient threshold obtained by using pure background noise data is theoretically more accurate than that obtained by using the whole seismic record, because of the discrepancy in the power spectrum between seismic waves and background noise. After hard thresholding, the wavelet coefficients of residual noise exhibit isolated and lower pixel connectivity in the time–frequency plane, compared with those of seismic signals. Thus, pixel connectivity thresholding is utilized to deal with the residual noise and further improve the SNR of seismic records. The proposed new denoising method is tested by synthetic and real seismic data, and the results suggest its effectiveness and robustness when dealing with noisy data from different acquisition environments and sampling rates. The current study provides a useful tool for microseismic data processing.

A Method to Generate Initial Fault Stresses for Physics-Based Ground-Motion Prediction Consistent with Regional Seismicity

ABSTRACTNear-field ground motion is the major blind spot of seismic hazard studies, mainly because of the challenges in accounting for source effects. Initial stress heterogeneity is an important component of physics-based approaches to ground-motion prediction that represents source effects through dynamic earthquake rupture modeling. We hypothesize that stress heterogeneity on a fault primarily originates from past background seismicity. We develop a new method to generate stochastic stress distributions as a superposition of residual stresses left by the previous ruptures that are consistent with regional distributions of earthquake size and hypocentral depth. We validate our method on Mw 7 earthquake models suitable for California by obtaining a satisfactory agreement with empirical earthquake scaling laws and ground-motion prediction equations. To avoid the excessive seismic radiation produced by dynamic models with abrupt arrest at preset rupture borders, we achieve spontaneous rupture arrest by incorporating a growth of fracture energy as a function of hypocentral distance. Our analyses of rupture and ground motion reveal particular signatures of the initial stress heterogeneity: rupture can locally propagate at supershear speed near the highly stressed areas; the position of high-stress and low-stress areas due to initial stress heterogeneity determines how the peak ground-motion amplitudes and polarization spatially vary along the fault, as low-stress areas slow down the rupture and decrease stress drop. We also find that the medium stratification in the fault zone amplifies fault slip and consequent ground motion, which requires understanding the interaction between site effects and rupture dynamics. Our approach advances our understanding of the relations between dynamic features of earthquake ruptures and the statistics of regional seismicity, and our capability to integrate information about regional seismicity into near-field ground-motion prediction.

A combination of tides and nontidal variations in ocean bottom pressure may generate interannual slip fluctuations in the transition zone along a subduction plate interface

The tidal triggering of earthquakes has been studied for many years. The discovery of slow earthquakes in the early 2000s, including slow slip, has urged scientists to investigate the tidal responses of these earthquakes due to their sensitivity to weak stress perturbations. Previous studies have shown that slow earthquakes correlate with diurnal and semidiurnal tides and seasonal variations in surface loads more clearly than ordinary earthquakes. However, little is known about long-term responses to external stresses. In this paper, based on a widely accepted frictional law for faults, a mechanism is proposed by which nontidal variations in ocean bottom pressure, when combined with tides, promote the occurrence of slow earthquakes. Because slow earthquakes accompany a slip on the plate interface, this mechanism allows one to estimate slip modulations. A one-degree-of-freedom slip model is constructed and applied to Ise Bay in the Tonankai region of southwestern Japan, where large-scale ocean mass redistributions have occurred. The model calculated with parameters determined from the observation of tectonic tremors is quantitatively consistent with the slip during 1997–2013 inferred from GNSS data, suggesting that the decrease in the sea-level change in approximately 2006 could cause the acceleration of a slip observed after that. This result implies that the decreases in sea level in approximately 1996 and 2014 could also cause subsequent slip accelerations. These three slip acceleration periods temporally coincide with the increases in background seismicity in a shallower portion of the plate interface. These changes in seismicity are common to shallow earthquakes in the Tokai area, and a similar model can reproduce them. Further studies are expected to reveal causality between shallow earthquakes and long-term slip fluctuations based on modeling that considers changes in the frictional property along the plate interface.

Along-strike distribution of seismicity and large slow slip correlated with gravity at the Nankai Trough

Various earthquakes and slow slip phenomena occur in different locations in the down-dip direction at subduction zones, for example, at the Nankai Trough, Japan. Many earthquakes, tectonic tremors, and slow slip events have occurred on the deeper side of the source areas of the past megathrust earthquakes. We show that three regions with high background seismicity correspond to the source areas of the large (> equivalent moment magnitude 6.5) slow slip events. These regions do not correspond to active areas of tectonic tremors. We note that considering broad-scale variations along the strike of the subduction zone, the three regions also correspond to areas with low free-air gravity anomalies. This fact implies that widespread stress perturbations in the along-strike direction, possibly coupled with pore fluid effects, may control the occurrence of seismic and aseismic slip on subduction faults regardless of whether at the plate interface or within the plate.

Direct Evidence of a Slow‐Slip Transient Modulating the Spatiotemporal and Frequency‐Magnitude Earthquake Distribution: Insights From the Armutlu Peninsula, Northwestern Turkey

AbstractEarthquakes and slow‐slip events interact, however, detailed studies investigating their interplay are still limited. We generate the highest resolution microseismicity catalog to date for the northern Armutlu Peninsula in a ∼1‐year period to perform a detailed seismicity distribution analysis and correlate the results with a local, geodetically observed slow‐slip transient within the same period. Seismicity shows a transition of cluster‐type behavior from swarm‐like to burst‐like, accompanied by an increasing relative proportion of clustered (non‐Poissonian) relative to background (Poissonian) seismicity and gradually decreasing b‐value as the geodetically observed slow‐slip transient ends. The observed slow‐slip transient decay correlates with gradually increasing effective‐stress‐drop values. The observed correlation between the b‐value and geodetic transient highlights the influence of aseismic deformation on seismic deformation and the impact of slow‐slip transients on local seismic hazard.

Seismically active structures of the Main Himalayan Thrust revealed before, during and after the 2015 Mw 7.9 Gorkha earthquake in Nepal

SUMMARY The Mw 7.9 2015 April 25 Gorkha earthquake is the latest of a millenary-long series of large devastating Himalayan earthquakes. It is also the first time a large Himalayan earthquake and its aftershocks were recorded by a local network of seismic stations. In the 5 yr following the main shock, more than 31 000 aftershocks were located by this permanent network within the ruptured area, including 14 362 events with ML greater than 2.5, 7 events with ML > 6, including one large aftershock with Mw 7.2 on 2015 May 12. In 2020, 5 yr after the main shock, the seismicity rate along the ruptured fault segments was still about 5 times higher than the background seismicity before the Gorkha earthquake. Several bursts of earthquakes, sometimes organized in clusters, have been observed from a few days to several years after the main shock. Some of these clusters were located at the same place as the clusters that happened during the decades of interseismic stress build-up that preceded the large earthquake. They also happened in the vicinity of the high frequency seismic bursts that occurred during the main shock. These heterogeneities contribute to a persistent segmentation of the seismicity along strike, possibly controlled by geological structural complexities of the Main Himalayan Thrust fault. We suggest that these pre-2015 clusters revealed the seismo-geological segmentation that influences both the coseismic rupture and the post-seismic relaxation.