Thrust-dominated unilateral rupture of a blind listric fault associated with the 2024 Hualien earthquake

The 2024 Hualien Mw 7.4 earthquake struck the Longitudinal Valley, which accommodates the partial collision between the Eurasian and Philippine Sea plates. As the most significant event in Taiwan since the 1999 Chi-Chi Mw 7.6 earthquake, it presents a distinct opportunity for investigating the current rupture behavior related to the northern Longitudinal Valley. The spatiotemporal rupture process of the Hualien earthquake is reconstructed through the analysis of geodetic and seismic observations. We demonstrate that the Hualien earthquake occurs on a blind listric fault, manifesting as a unilateral rupture primarily extending toward the NNE. The slip distribution exhibits a compact pattern dominated by the thrust faulting. As indicated by the increased Coulomb failure stress, the 2022 Chihshang Mw 6.5 and Mw 6.9 earthquakes cause a triggering effect on the Hualien earthquake. The Hualien earthquake also promotes the occurrence of a seismic swarm at the southernmost tip of its rupture area.

Stress transfer outpaces injection-induced aseismic slip and triggers seismicity

As concerns rise over damaging earthquakes related to industrial activities such as hydraulic fracturing, geothermal energy extraction and wastewater disposal, it is essential to understand how subsurface fluid injection triggers seismicity even in distant regions where pore pressure diffusion cannot reach. Previous studies suggested long-range poroelastic stressing and aseismic slip as potential triggering mechanisms. In this study, we show that significant stress transfer far ahead of injection-induced aseismic slip can travel at much higher speeds and is a viable mechanism for distant earthquake triggering. It could also explain seismicity migration that is much faster than aseismic slip front propagation. We demonstrate the application of these concepts with seismicity triggered by hydraulic fracturing operations in Weiyuan shale gas field, China. The speed of stress transfer is dependent on the background stress level and injection rate, and can be almost an order of magnitude higher than that of the aseismic slip front.

Seismic source identification of the 9 November 2022 Mw 5.5 offshore Adriatic sea (Italy) earthquake from GNSS data and aftershock relocation

The fast individuation and modeling of faults responsible for large earthquakes are fundamental for understanding the evolution of potentially destructive seismic sequences. This is even more challenging in case of buried thrusts located in offshore areas, like those hosting the 9 November 2022 Ml 5.7 (M_w 5.5) and M_L 5.2 earthquakes that nucleated along the Apennines compressional front, offshore the northern Adriatic Sea. Available on- and offshore (from hydrocarbon platforms) geodetic observations and seismological data provide robust constraints on the rupture of a 15 km long, ca. 24° SSW-dipping fault patch, consistent with seismic reflection data. Stress increase along unruptured portion of the activated thrust front suggests the potential activation of longer portions of the thrust with higher magnitude earthquake and larger surface faulting. This unpleasant scenario needs to be further investigated, also considering their tsunamigenic potential and possible impact on onshore and offshore human communities and infrastructures.

Characteristic Magnitude and Spatiotemporal Relationships of Aftershocks and Background Earthquakes

Aftershocks, background earthquakes, and their spatiotemporal parameters have been studied for decades for the purpose of hazard assessment and forecasting. Methods for determining these parameters or seismic attributes are becoming increasingly sophisticated and varied; some optimize the results to fit observations using trial and error, while others do the same by giving prescriptions for a limited region. Here, we propose a method that is potentially useful in general hazard assessment and forecasting applications. We categorized the earthquakes into two groups, aftershocks (triggered events) and background earthquakes, by introducing the network distance, i.e., the shortest distance between two events of equal magnitude within a modified interevent time, into the k-means clustering, which couples the modified interevent time and magnitude hierarchically. Our results show a bimodal distribution consisting of a power law at shorter network distances and a lognormal distribution at longer network distances, implying that earthquakes of magnitudes larger than the characteristic magnitude, found to be 4.5 for Taiwan and 4.3 for California, may be only weakly linked to other same magnitude earthquakes and hence are hard to be triggered even by events of larger size.

The Source Characteristics of the Mw6.4, 2016 Meinong Taiwan Earthquake from Teleseismic Data Using the Hybrid Homomorphic Deconvolution Method

The kinematic source rupture process of the 2016 Meinong earthquake (Mw = 6.4) in Taiwan was derived from apparent source time functions retrieved from teleseismic S-waves by using a refined homomorphic deconvolution method. The total duration of the rupture process was approximately 15 s, and one slip-concentrated area can be represented as the source model based on images representing static slip distribution. The rupture process began in a down-dip direction from the fault toward Tainan City, strongly suggesting that the rupture had a unilateral northwestern direction. The asperity with an area of approximately 15 × 15 km2 and the maximum slip of approximately 2 m were centered 12.8 km northwest of the hypocenter. Coseismic vertical deformation was calculated based on the source model. Compared with the results derived from InSAR (Interferometric Synthetic Aperture Radar) data, our results demonstrated that the location with maximum uplift was accurately well detected, but our maximum value was just approximately 0.4 times of the InSAR-derived value. It reveals that there are the other mechanisms to affect the vertical deformation, rather than only depending on the source model. At different depths, areas west, east, and north of the hypocenter maintained high values of Coulomb stress changes. This explains the mechanism behind aftershocks being triggered and provides a reference for predicting aftershock locations after a large earthquake. The estimated seismic spectral intensities, including spectral acceleration and velocity intensity (SIa and SIv), were derived. Source directivity effects caused damage to buildings, and we concluded that all damaged buildings were located within a SIa value of 400 gal. Destroyed buildings taller than seven floors were located in an area with a SIv value of 30 cm/s. These observations agree with those on damages caused by the 2010 Jiasian earthquake (ML 6.4) in Tainan, Taiwan.

A process-based approach to understanding and managing triggered seismicity

There is growing concern about seismicity triggered by human activities, whereby small increases in stress bring tectonically loaded faults to failure. Examples of such activities include mining, impoundment of water, stimulation of geothermal fields, extraction of hydrocarbons and water, and the injection of water, CO₂ and methane into subsurface reservoirs¹. In the absence of sufficient information to understand and control the processes that trigger earthquakes, authorities have set up empirical regulatory monitoring-based frameworks with varying degrees of success^2,3. Field experiments in the early 1970s at the Rangely, Colorado (USA) oil field⁴ suggested that seismicity might be turned on or off by cycling subsurface fluid pressure above or below a threshold. Here we report the development, testing and implementation of a multidisciplinary methodology for managing triggered seismicity using comprehensive and detailed information about the subsurface to calibrate geomechanical and earthquake source physics models. We then validate these models by comparing their predictions to subsequent observations made after calibration. We use our approach in the Val d'Agri oil field in seismically active southern Italy, demonstrating the successful management of triggered seismicity using a process-based method applied to a producing hydrocarbon field. Applying our approach elsewhere could help to manage and mitigate triggered seismicity.

Aftershocks are fluid-driven and decay rates controlled by permeability dynamics

One aspect of earthquake physics not adequately addressed is why some earthquakes generate thousands of aftershocks while other earthquakes generate few, if any, aftershocks. It also remains unknown why aftershock rates decay as ~1/time. Here, I show that these two are linked, with a dearth of aftershocks reflecting the absence of high-pressure fluid sources at depth, while rich and long-lasting aftershock sequences reflect tapping high-pressure fluid reservoirs that drive aftershock sequences. Using a physical model that captures the dominant aspects of permeability dynamics in the crust, I show that the model generates superior fits to observations than widely used empirical fits such as the Omori-Utsu Law, and find a functional relationship between aftershock decay rates and the tectonic ability to heal the co- and post-seismically generated fracture networks. These results have far-reaching implications, and can help interpret other observations such as seismic velocity recovery, attenuation, and migration.

In this study, the authors propose that a fluid rich environment is necessary to generate long-lasting aftershock sequences. Based on this premise, the study presents a theory for modeling fluid-driven earthquake sequences

Spatial Prediction of Aftershocks Triggered by a Major Earthquake: A Binary Machine Learning Perspective

Small earthquakes following a large event in the same area are typically aftershocks, which are usually less destructive than mainshocks. These aftershocks are considered mainshocks if they are larger than the previous mainshock. In this study, records of aftershocks (M > 2.5) of the Kermanshah Earthquake (M 7.3) in Iran were collected from the first second following the event to the end of September 2018. Different machine learning (ML) algorithms, including naive Bayes, k-nearest neighbors, a support vector machine, and random forests were used in conjunction with the slip distribution, Coulomb stress change on the source fault (deduced from synthetic aperture radar imagery), and orientations of neighboring active faults to predict the aftershock patterns. Seventy percent of the aftershocks were used for training based on a binary (“yes” or “no”) logic to predict locations of all aftershocks. While untested on independent datasets, receiver operating characteristic results of the same dataset indicate ML methods outperform routine Coulomb maps regarding the spatial prediction of aftershock patterns, especially when details of neighboring active faults are available. Logistic regression results, however, do not show significant differences with ML methods, as hidden information is likely better discovered using logistic regression analysis.

Clock advance and magnitude limitation through fault interaction: the case of the 2016 central Italy earthquake sequence

Faults communicate with each other. Strong earthquakes perturb stress over large volumes modifying the load on nearby faults and their resistance to slip. The causative fault induces permanent or transient perturbations that can change the time to the next seismic rupture with respect to that expected for a steadily accumulating stress. For a given fault, an increase of stress or a strength decrease would drive it closer to - or maybe even trigger - an earthquake. This is usually perceived as an undesired circumstance. However, with respect to the potential damage, a time advance might not necessarily be a bad thing. Here we show that the central Italy seismic sequence starting with the Amatrice earthquake on 24 August 2016 advanced the 30 October Norcia earthquake (M_W = 6.5), but limited its magnitude by inhibiting the rupture on large portions of the fault plane. The preceding events hastened the mainshock and determined its features by shaping a patch of concentrated stress. During the Norcia earthquake, the coseismic slip remained substantially confined to this patch. Our results demonstrate that monitoring the seismicity with very dense networks and timely analyses can make it feasible to map rupture prone areas.

Deep learning of aftershock patterns following large earthquakes

Aftershocks are a response to changes in stress generated by large earthquakes and represent the most common observations of the triggering of earthquakes. The maximum magnitude of aftershocks and their temporal decay are well described by empirical laws (such as Bath's law¹ and Omori's law²), but explaining and forecasting the spatial distribution of aftershocks is more difficult. Coulomb failure stress change³ is perhaps the most widely used criterion to explain the spatial distributions of aftershocks^4-8, but its applicability has been disputed^9-11. Here we use a deep-learning approach to identify a static-stress-based criterion that forecasts aftershock locations without prior assumptions about fault orientation. We show that a neural network trained on more than 131,000 mainshock-aftershock pairs can predict the locations of aftershocks in an independent test dataset of more than 30,000 mainshock-aftershock pairs more accurately (area under curve of 0.849) than can classic Coulomb failure stress change (area under curve of 0.583). We find that the learned aftershock pattern is physically interpretable: the maximum change in shear stress, the von Mises yield criterion (a scaled version of the second invariant of the deviatoric stress-change tensor) and the sum of the absolute values of the independent components of the stress-change tensor each explain more than 98 per cent of the variance in the neural-network prediction. This machine-learning-driven insight provides improved forecasts of aftershock locations and identifies physical quantities that may control earthquake triggering during the most active part of the seismic cycle.

Combining stress transfer and source directivity: the case of the 2012 Emilia seismic sequence

The Emilia seismic sequence (Northern Italy) started on May 2012 and caused 17 casualties, severe damage to dwellings and forced the closure of several factories. The total number of events recorded in one month was about 2100, with local magnitude ranging between 1.0 and 5.9. We investigate potential mechanisms (static and dynamic triggering) that may describe the evolution of the sequence. We consider rupture directivity in the dynamic strain field and observe that, for each main earthquake, its aftershocks and the subsequent large event occurred in an area characterized by higher dynamic strains and corresponding to the dominant rupture direction. We find that static stress redistribution alone is not capable of explaining the locations of subsequent events. We conclude that dynamic triggering played a significant role in driving the sequence. This triggering was also associated with a variation in permeability and a pore pressure increase in an area characterized by a massive presence of fluids.

Stress imparted by the great 2004 Sumatra earthquake shut down transforms and activated rifts up to 400 km away in the Andaman Sea

The origin and prevalence of triggered seismicity and remote aftershocks are under debate. As a result, they have been excluded from probabilistic seismic hazard assessment and aftershock hazard notices. The 2004 M = 9.2 Sumatra earthquake altered seismicity in the Andaman backarc rift-transform system. Here we show that over a 300-km-long largely transform section of the backarc, M≥4.5 earthquakes stopped for five years, and over a 750-km-long backarc section, the rate of transform events dropped by two-thirds, while the rate of rift events increased eightfold. We compute the propagating dynamic stress wavefield and find the peak dynamic Coulomb stress is similar on the rifts and transforms. Long-period dynamic stress amplitudes, which are thought to promote dynamic failure, are higher on the transforms than on the rifts, opposite to the observations. In contrast to the dynamic stress, we calculate that the mainshock brought the transform segments approximately 0.2 bar (0.02 MPa) farther from static Coulomb failure and the rift segments approximately 0.2 bar closer to static failure, consistent with the seismic observations. This accord means that changes in seismicity rate are sufficiently predictable to be included in post-mainshock hazard evaluations.

Role of static stress diffusion in the spatiotemporal organization of aftershocks

We investigate the spatial distribution of aftershocks, and we find that aftershock linear density exhibits a maximum that depends on the main shock magnitude, followed by a power law decay. The exponent controlling the asymptotic decay and the fractal dimensionality of epicenters clearly indicate triggering by static stress. The nonmonotonic behavior of the linear density and its dependence on the main shock magnitude can be interpreted in terms of diffusion of static stress. This is supported by the power law growth with exponent H approximately 0.5 of the average main-aftershock distance. Implementing static stress diffusion within a stochastic model for aftershock occurrence, we are able to reproduce aftershock linear density spatial decay, its dependence on the main shock magnitude, and its evolution in time.

Earth Tides Can Trigger Shallow Thrust Fault Earthquakes

We show a correlation between the occurrence of shallow thrust earthquakes and the occurrence of the strongest tides. The rate of earthquakes varies from the background rate by a factor of 3 with the tidal stress. The highest correlation is found when we assume a coefficient of friction of mu = 0.4 for the crust, although we see good correlation for mu between 0.2 and 0.6. Our results quantify the effect of applied stress on earthquake triggering, a key factor in understanding earthquake nucleation and cascades whereby one earthquake triggers others.

Foreshocks and aftershocks in the Olami-Feder-Christensen model

With the help of numerical simulations we show that the established Olami-Feder-Christensen earthquake model exhibits sequences of foreshocks and aftershocks; this behavior has not been recognized in previous studies. Our results are consistent with Omori's empirical law, but the exponents predicted by the model are lower than observed in nature. The occurrence of foreshocks and aftershocks can be attributed to the nonconservative character of the Olami-Feder-Christensen model.

Earthquake triggering by seismic waves following the Landers and Hector Mine earthquakes

The proximity and similarity of the 1992, magnitude 7.3 Landers and 1999, magnitude 7.1 Hector Mine earthquakes in California permit testing of earthquake triggering hypotheses not previously possible. The Hector Mine earthquake confirmed inferences that transient, oscillatory 'dynamic' deformations radiated as seismic waves can trigger seismicity rate increases, as proposed for the Landers earthquake. Here we quantify the spatial and temporal patterns of the seismicity rate changes. The seismicity rate increase was to the north for the Landers earthquake and primarily to the south for the Hector Mine earthquake. We suggest that rupture directivity results in elevated dynamic deformations north and south of the Landers and Hector Mine faults, respectively, as evident in the asymmetry of the recorded seismic velocity fields. Both dynamic and static stress changes seem important for triggering in the near field with dynamic stress changes dominating at greater distances. Peak seismic velocities recorded for each earthquake suggest the existence of, and place bounds on, dynamic triggering thresholds. These thresholds vary from a few tenths to a few MPa in most places, depend on local conditions, and exceed inferred static thresholds by more than an order of magnitude. At some sites, the onset of triggering was delayed until after the dynamic deformations subsided. Physical mechanisms consistent with all these observations may be similar to those that give rise to liquefaction or cyclic fatigue.

Earthquakes as beacons of stress change

Aftershocks occurring on faults in the far-field of a large earthquake rupture can generally be accounted for by changes in static stress on these faults caused by the rupture. This implies that faults interact, and that the timing of an earthquake can be affected by previous nearby ruptures. Here we explore the potential of small earthquakes to act as 'beacons' for the mechanical state of the crust. We investigate the static-stress changes resulting from the 1992 Landers earthquake in southern California which occurred in an area of high seismic activity stemming from many faults. We first gauge the response of the regional seismicity to the Landers event with a new technique, and then apply the same method to the inverse problem of determining the slip distribution on the main rupture from the seismicity. Assuming justifiable parameters, we derive credible matches to slip profiles obtained directly from the Landers mainshock. Our results provide a way to monitor mechanical conditions in the upper crust, and to investigate processes leading to fault failure.