Local Earthquakes Research Articles

Broad fault zones enable deep fluid transport and limit earthquake magnitudes

Constraining the controlling factors of fault rupture is fundamentally important. Fluids influence earthquake locations and magnitudes, although the exact pathways through the lithosphere are not well-known. Ocean transform faults are ideal for studying faults and fluid pathways given their relative simplicity. We analyse seismicity recorded by the Passive Imaging of the Lithosphere-Asthenosphere Boundary (PI-LAB) experiment, centred around the Chain Fracture Zone. We find earthquakes beneath morphological transpressional features occur deeper than the brittle-ductile transition predicted by simple thermal models, but elsewhere occur shallower. These features are characterised by multiple parallel fault segments and step overs, higher proportions of smaller events, gaps in large historical earthquakes, and seismic velocity structures consistent with hydrothermal alteration. Therefore, broader fault damage zones preferentially facilitate fluid transport. This cools the mantle and reduces the potential for large earthquakes at localized barriers that divide the transform into shorter asperity regions, limiting earthquake magnitudes on the transform.

Three-dimensional numerical modeling of ground motion in the Valley of Mexico: A case study from the Mw3.2 earthquake of July 17, 2019

In this study, a 3D physics-based numerical approach, based on the spectral element numerical code SPEED, is used to simulate seismic wave propagation due to a local earthquake in the Mexico City area. The availability of detailed geological, geophysical, geotechnical, and seismological data allowed for the creation of a large-scale (60 km × 60 km in plan, 10 km in depth) heterogeneous 3D numerical model of the Mexico City area, dimensioned to accurately propagate frequencies up to about 1.3 Hz. The results of numerical simulations are validated against the ground motion recordings of the July 17, 2019, Mw3.2 earthquake, with peak ground acceleration exceeding 0.3 g about 1 km away from the epicenter. A good agreement with records is found, quantitatively evaluated through goodness-of-fit checks. Furthermore, for the lake zone, the simulated decay trend of the peak ground velocity with epicentral distance is reasonably close to the observations, for both horizontal and vertical components. In spite of some limitations, the simulations are successful to provide a realistic picture of seismic wave propagation both in the hill and in the lake zones of Mexico City, including the onset of long-duration quasi-monochromatic ground motion in the basin, with strong amplification at low frequencies (between 0.4 and 0.7 Hz). The numerical results also suggest that surface waves, with predominant prograde particle motion at the ground surface and large ellipticities, dominate the wavefield in the lake zone. Based on these positive outcomes, we conclude that this numerical model may be useful for both a better insight into the seismic response of the Valley of Mexico and the simulation of ground motions during larger-magnitude earthquakes, to generate improved seismic damage scenarios in Mexico City.

P and S Wave Anisotropic Tomography of the Banda Subduction Zone

AbstractIn subduction zones with slab‐slab interactions, the pattern of mantle convection is very complex and still unclear. In this study, we jointly invert a large number of P and S wave arrival time data of local earthquakes for 3‐D isotropic and anisotropic velocity structures of the Banda subduction zone. Along the curved Banda arc, the subducting Indo‐Australian slab is detected clearly as a high‐velocity zone, and its azimuthal anisotropy changes along the arc strike, representing fossil anisotropy within the slab and modified anisotropy by the subduction processes. Around the northern edge of the Banda slab, a semi‐toroidal pattern of anisotropy appears in low‐velocity anomalies, representing mantle flow extruded from the Banda arc and escaped from a gap of the Banda‐Molucca slab toward the northeast. Our 3‐D anisotropic tomography uncovers the mantle convection pattern induced by the slab‐slab interactions, shedding new light on the complex dynamical processes in this curved subduction zone.

Assessing network-based earthquake early warning systems in low-seismicity areas

Earthquake early warning (EEW) technology, designed to alert the public of earthquake risks after initial P-wave detection but before the onset of strong tremors, has developed rapidly. Methodologies from various fields are combined in EEW systems to estimate earthquake locations, magnitudes, and expected intensities based on the initial P-wave data. These systems operate automatically because prompt responses are required. However, as no common evaluation framework for EEW system verification exists, potentially divergent evaluations from reviewers or countries could ensue. Moreover, evaluating EEW systems is more complicated when the target area does not experience frequent earthquakes. We aimed to establish a guidance review process for low-seismicity areas to ensure reliable and stable integrated EEW system operation. We incorporated management aspects through actual system operator surveillance and designed an EEW assessment process based on feedback from our surveys. Using this approach, we created a comprehensive and well-informed evaluation process that considers the diverse perspectives of experts involved in EEWs. Our proposed assessment method allows for a uniform and consistent evaluation process, regardless of changes in the methods or technologies used by EEW systems. The method aims to guide EEW system assessments in low-seismicity areas.

A novel deep-learning image condition for locating earthquake

SUMMARY Migration-based earthquake location methods may encounter the polarity reversal issue due to the non-explosive components of seismic sources, leading to an unfocused migration image. Such a problem usually makes it difficult to accurately retrieve the optimal location from the migrated source image. In this study, by taking advantage of the general pattern recognition ability of the convolutional neural network, we propose a novel deep-learning image condition (DLIC) to address this issue. The proposed DLIC measures the goodness of waveform alignments for both P and S waves, and it follows the geophysical principle of seismic imaging that the best-aligned waveforms represent fully a best-imaged source location. A synthetic test shows that the DLIC can effectively overcome the polarity reversal issues. Real data applications to southern California show that the DLIC can enhance the focusing of the migrated source image over the classic source scanning algorithm. Further tests show that the DLIC applies to continuous seismic data, to regions with few previously recorded earthquakes, and has the potential to locate small earthquakes. The proposed DLIC shall benefit the migration-based source location methods.

Monitoring of Local Earthquakes in Haiti Using Low-Cost, Citizen-Hosted Seismometers and Regional Broadband Stations

Abstract Seismic monitoring in Haiti is currently provided by a mixed network of low-cost Raspberry Shake (RS) seismic stations hosted by citizens, and short-period and broadband stations located mainly in neighboring countries. The level of earthquake detection is constantly improving for a better spatio-temporal distribution of seismicity as the number of RS increases. In this article, we analyze the impact of the quality of the signals recorded by the RS—low-cost seismometers with the smallest magnitude that the network can detect by studying the ambient noise level at these stations. Because the RS stations are installed as part of a citizen-science project, their ambient noise estimated by the power spectral density (PSD) method often shows a high-noise level at frequencies above 1 Hz. In the near field (<50 km), we show that the network detects seismic events of local magnitude on the order of 2.2 with signal-to-noise ratios (SNRs) greater than 4. Improving the network detection threshold requires densifying the network with more RS stations in locations that are less noisy, if possible. In spite of these limitations, this mixed network has provided near-field data essential to rapidly understand the mechanism of the mainshock of the 14 August 2021 Mw 7.2 earthquake, to monitor its sequence of aftershocks in near-real time, and to monitor background seismicity in Haiti on a routine basis.

Assessment of Liquefaction Hazard for Sites in Romania Using Empirical Models

This paper is focused on the evaluation of the liquefaction hazard for different sites in Romania. To this aim, a database of 139 ground motions recorded during Vrancea intermediate-depth earthquakes having moment magnitudes MW ≥ 6.0 is employed for the evaluation of the equivalent number of cycles for this seismic source. Several functional forms for the empirical evaluation of the equivalent number of cycles considering various seismological or engineering parameters are tested and evaluated. The regression analysis shows smaller uncertainties for the empirical models based on ground motion engineering parameters. Considering the lack of information in terms of engineering parameters, a simpler empirical model which accounts for the earthquake magnitude, source–site distance and soil conditions is selected for the liquefaction hazard analysis. Based on the proposed empirical model, specific magnitude scaling factors for Vrancea intermediate-depth earthquakes are proposed for the first time as well. The liquefaction hazard analysis is performed for sites whose seismic hazard is generated by either the Vrancea intermediate-depth seismic source or by local shallow crustal seismic sources. In the case of some of the selected sites, liquefaction phenomena were observed during past large-magnitude earthquakes. Unlike previous studies dealing with liquefaction analyses for sites in Romania, in this research, the hazard assessment is performed for various ground motion levels evaluated based on probabilistic seismic hazard assessment. Liquefaction hazard curves are constructed for each analyzed site. The results of the liquefaction hazard analysis show that this phenomenon is more likely to occur in the areas exposed to Vrancea intermediate-depth earthquakes, compared to the areas affected by local shallow earthquakes. In the case of the analyzed soil profiles from Bucharest, Craiova and Ianca, the minimum liquefaction safety factors less than one even for seismic hazard levels having mean return periods of 100 years and less.

Earthquake prediction technique: a comparative study

Earthquakes are one of the most dangerous natural disasters facing humans because of their occurrence without warning and their impact on their lives and property. In addition, predicting seismic movement is one of the main research topics in seismic disaster prevention. In geological studies, scientists can predict and know the locations of earthquakes in the long term. Therefore, about 80% of the major global earthquakes lie along the Pacific Ring belt, known as the Ring of Fire. Machine learning methods have also been used for short-term earthquake prediction, and studies have applied the random forest method to determine the factors that precede earthquakes. The machine learning method was based on various decision trees, each of which predicted the time to the nearest oscillation. The third group of scientists used the hybrid prediction method, which combines machine learning and geological studies. This research deals with a review of most of the geological studies and machine learning techniques applied to earthquake data sets, which showed a total lack of prediction of potential earthquakes through one approach, so studies designed by geologists were combined with machine learning.

Coda wave attenuation in Northern Aceh, Indonesia from a single station measurement: preliminary results

Sumatra-Andaman subduction zone is one of the most active tectonic areas in the world. Understanding seismic risk in this region is important for hazard mitigation. One of the crustal physical properties is attenuation. Attenuation structure may affect the seismic propagation through the medium. It expresses the seismic wave amplitude decay when wave propagates through a medium. In this preliminary result, we report the seismic attenuation characteristics in Northern Aceh, Indonesia. We estimate coda waves attenuation from a single station from GE network. using a single back-scattering model. We analyze about 123 waveforms from local earthquakes (less than 3°) with magnitudes between 3 and 6 using a single back-scattering model. The depth of the events is selected to be shallower than 40 km depth. We estimate coda quality factor (Qc ) for each event at frequencies 1 – 8 Hz. The coda window is estimated from two times of S-wave arrival time with different window length ranging from 20 to 80 s. Reference coda quality factor (Q0 ) is selected at frequency of 1 Hz. We obtain that Q0 varies from 74.34 ± 10.04 to 160.2 ± 5.96 at 20 s and 80 s window lengths, respectively. The frequency dependence factor (η) decreases from 1.12 ± 0.06 to 1.05 ± 0.03 at 20 s and 80 s window length, respectively. An increase of Q0 with window length may suggest the depth dependent of seismic wave attenuation at reference frequency of 1 Hz. Low Q0 and high η are also consistent with this region’s high tectonic activity.

Rapid Source Characterization of the Maule Earthquake Using Prompt Elasto‐Gravity Signals

AbstractThe recently identified Prompt Elasto‐Gravity Signals (PEGS), generated by large earthquakes, propagate at the speed of light and are sensitive to the earthquake magnitude and focal mechanism. These characteristics make PEGS potentially very advantageous for tsunami early warning, which relies on fast and accurate estimation of the magnitude of large offshore earthquakes. PEGS‐based early warning does not suffer from the problem of magnitude estimation saturation, that P‐wave based early warning algorithms have, and could be faster than Global Navigation Satellite Systems (GNSS)‐based systems while not requiring a priori assumptions on slip distribution. We use a deep learning model called PEGSNet to evaluate the possibility to estimate in real time the evolution of the magnitude of big earthquakes in the tsunamigenic zone of Chile. The model is a Convolutional Neural Network (CNN) trained on a database of synthetic PEGS—simulated for an exhaustive set of possible earthquakes distributed along the Chilean subduction zone—augmented with empirical noise. The approach is multi‐station and leverages the information recorded by the seismic network to estimate as fast as possible the magnitude and location of an ongoing earthquake. Our results indicate that PEGSNet could have estimated that the magnitude of the 2010 Mw 8.8 Maule earthquake was above 8.7, 90 s after origin time. Our offline simulations using real data and noise recordings further support the instantaneous tracking of the source time function of the earthquake and show that deploying seismic stations in optimal locations could improve the performance of the algorithm.

Seismicity and Magmatic System of the Changbaishan Intraplate Volcano in East Asia

AbstractA high‐precision earthquake catalog is made from continuous waveform data recorded at 360 portable seismographs deployed for one month in the Changbaishan‐Tianchi volcanic area based on an automatic earthquake detection and location workflow. Then we investigate detailed 3‐D structures of P and S wave velocities (Vp and Vs) and Vp/Vs ratio of the crust beneath the study region. Our results reveal a high‐Vp/Vs zone accompanied with active volcanic earthquakes beneath the Tianchi caldera at ∼5 km depth, which may reflect a magma chamber. The intense seismic activities within 2 km depth beneath the Tianchi caldera from 2002 to 2005 occurred directly above the magma chamber revealed by this study, which could be related to upward migration of high‐pressure volatiles originating from the magma chamber. A potential middle‐crustal magma chamber might provide continuous magmatic materials feeding the upper‐crust magma chamber and lead to ruptures of surrounding rocks, resulting in two swarms of volcanic seismicity during the observation period. We deem that the diverse eruption styles of the Changbaishan volcano are closely associated with the multilevel structure of magma chambers in the upper and middle crust.

Improved lithospheric seismic velocity and density model of the Korean Peninsula from ambient seismic noise data using machine learning

To accurately estimate physical properties and tectonic behavior in the near-surface, a reliable seismic property model is needed for realistic seismic modeling and earthquake location estimation. Recording ambient seismic noise (ASN) data and producing interferometric reflection images traditionally provides subsurface structure observation without an active source. However, due to low signal-to-noise ratio (SNR) and vertical resolution, interpreting upper mantle structures and inverting seismic models from noise data is difficult. To address this, machine learning (ML) techniques are applied to enhance vertical resolution and interpret geologically meaningful boundaries. Spectral enhancement with convolutional U-net generates higher resolution data by preserving temporal continuity. Unsupervised ML interprets lithospheric boundaries more robustly and objectively than manual horizon picking, and model-based seismic inversion integrates improved seismic data with prior full-waveform inversion (FWI) models. ML-based results improve inverted models, displaying more detailed geological structures and seismic property changes, surpassing seismic data limitations.

Quantifying Site Effects and Their Influence on Earthquake Source Parameter Estimations Using a Dense Array in Oklahoma

AbstractWe investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge‐n Seismic Survey in Oklahoma (LASSO). While it is well known that near‐surface unconsolidated sediments can cause an apparent breakdown of earthquake self‐similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825‐station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P‐wave ground motions below 8 Hz, the surface geology correlates with P‐wave ground motions above 8 Hz and S‐wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes (ML = 0.01–3) estimated using a standard single‐spectra approach show negative correlations with the site‐effect proxy, while the seismic moments show positive correlations. In contrast, the spectral‐ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site‐related biases requires at least 30 stations. Correcting for site‐related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.

Sedimentary P- and S-Wave Velocity Structures in Shimousa Region of Kanto Basin Determined from Joint Autocorrelation and Receiver Function Analysis

ABSTRACT To determine the P- and S-wave velocities (VP and VS, respectively) of the sedimentary layers in the Shimousa region of the Kanto basin, Japan, the autocorrelations of P and S waves and the receiver function (RF) for the local earthquakes at the strong-motion stations in the region were jointly analyzed. Because the autocorrelations and RF were insensitive to the event location, the stacked functions for various events captured clear P and S reflections and the Ps phase at the bedrock of the basin. The PpPs phase was also clearly observed at some stations in the region. The arrival times of the P and S reflections and the Ps phase depended on the station. These phases arrived earlier at the northern and eastern parts of the region, and later at the southern and western parts. This trend shows good agreement with that expected from the 3D velocity structure model developed by the Japan Seismic Hazard Information Station. The VP, VS, and thickness (H) values were then estimated from the histogram of the H–V stack for the P and S autocorrelations and the Ps and PpPs phases in the RF. VP, which is less sensitive than VS and H, was not always well determined at some stations, whereas VS and H were well estimated with high resolution. It was found that the resolution depends on the station location in the region. This dependence could be caused by the appearance of clear phases in the functions.

Identifying attacks in the Russia-Ukraine conflict using seismic array data.

Seismometers are generally used by the research community to study local or distant earthquakes, but seismograms also contain critical observations from regional1,2 and global explosions3, which can be used to better understand conflicts and identify potential breaches of international law. Although seismic, infrasound and hydroacoustic technology is used by the International Monitoring System4 to monitor nuclear explosions as part of the Comprehensive Nuclear-Test-Ban Treaty, the detection and location of lower-yield military attacks requires a network of sensors much closer to the source of the explosions. Obtaining comprehensive and objective data that can be used to effectively monitor an active conflict zone therefore remains a substantial challenge. Here we show how seismic waves generated by explosions in northern Ukraine and recorded by a local network of seismometers can be used to automatically identify individual attacks in close to real time, providing an unprecedented view of an active conflict zone. Between February and November 2022, we observed more than 1,200 explosions from the Kyiv, Zhytomyr and Chernihiv provinces, providing accurate origin times, locations and magnitudes. We identify a range of seismoacoustic signals associated with various types of military attack, with the resulting catalogue of explosions far exceeding the number of publicly reported attacks. Our results demonstrate that seismic data can be an effective tool for objective monitoring of a continuing conflict, providing invaluable information about potential breaches of international law.

Structural constraints of induced earthquakes in the Weiyuan Shale Gas Field revealed by high-resolution body-wave tomography and earthquake relocation

Increasing concerns have been raised about hydraulic fracturing (HF) due to its capability of triggering damaging earthquakes. Although there is a common consensus that local geological settings play significant roles in these earthquakes, to what extent they influence earthquake locations and magnitudes within a shale gas field remains unclear. Here we conduct body-wave travel time tomography, earthquake relocation, and structural analysis in the Weiyuan Shale Gas Field (WSGF), Sichuan Basin, China. We find that structural deformation of the Weiyuan anticline and the newly revealed basement rift constrained the locations and magnitudes of ML ≥ 3.0 earthquakes in the WSGF. We also observe that ML ≥ 3.0 earthquakes are more prone to occur in low-velocity or velocity transition zones that are geologically susceptible. Based on high-resolution earthquake locations, we use aftershocks to delineate the fault plane of the largest Mw 5.0 in the WSGF. Our analysis shows the Mw 5.0 event nucleated in the basement rift and ruptured a fault plane strikes along northeast. Our results shed light on mitigating destructive earthquakes in shale gas fields by identifying geologically susceptible zones using structural deformation simulation and high-resolution tomography methods.

MAPPING OF S-WAVE ATTENUATION FIELD USING THE CODA ENVELOPES OF LOCAL EARTHQUAKES AND QUARRY BLASTS FOR THE EAST KAZAKHSTAN REGION ON THE DATA FROM PERMANENT AND TEMPORARY SEISMIC STATIONS

The paper considers the heterogeneities of short-period shear waves attenuation field in the east Kazakhstan lithosphere including the region of the Semipalatinsk Test Site where a lot of test detonations of nuclear weapons were performed underground in the past. The common S-waves coda envelopes were obtained by the records of near calibration explosions and quarry blasts as well as local earthquakes on the data from permanent and temporary stations. The obtained data allowed us to create attenuation field sections in the lithosphere of the considered region. The attenuation field heterogeneities were mapped for the lower crust and uppermost mantle of the east Kazakhstan. Very low Q-factor values (Qs~40–55) correspond to several stations installed in the area of the Balapan test site where the most powerful test explosions were conducted. These values are much lower than the minimum values corresponding to a large number of stations installed in seismically active region of the Northern Tien Shan. It is supposed that this is due to upwelling of deep-seated fluids along the active fault zones under a long-term intensive vibration effect. The obtained data can be used to reveal the zones having high concentration of fluids in the lithosphere parts of probable large earthquake generation. This information is quite important due to the planned construction of nuclear power plant in the east Kazakhstan region.

Qβ, Qc, Qi, Qs of the Gargano Promontory (Southern Italy)

We have provided the first estimate of scattering and intrinsic attenuation for the Gargano Promontory (Southern Italy) analyzing 190 local earthquakes with ML ranging from 1.0 to 2.8. To separate the intrinsic {Q}_{i} and scattering {Q}_{s} quality factors with the Wennerberg approach (1993), we have measured the direct S waves and coda quality factors ({Q}_{beta }, {Q}_{c}) in the same volume of crust. {Q}_{beta } parameter is derived with the coda normalization method (Aki 1980) and {Q}_{c} factor is derived with the coda envelope decay method (Sato 1977). We selected the coda envelope by performing an automatic picking procedure from {T}_{mathrm{start}}=1.5{T}_{S} up to 30 s after origin time (lapse time {T}_{L}). All the obtained quality factors clearly increase with frequency. The {Q}_{c} values correspond to those recently obtained for the area. The estimated {Q}_{i} are comparable to the {Q}_{c} at all frequencies and range between 100 and 1000. The {Q}_{s} parameter shows higher values than {Q}_{i}, except for 8 Hz, where the two estimates are closer. This implies a predominance of intrinsic attenuation over the scattering attenuation. Furthermore, the similarity between {Q}_{i} and {Q}_{c} allows us to interpret the high {Q}_{c} anomaly previously found in the northern Gargano Promontory up to a depth of 24 km, as a volume of crust characterized by very low seismic dumping produced by conversion of seismic energy into heat. Moreover, most of the earthquake foci fall in high {Q}_{i} areas, indicating lower level of anelastic dumping and a brittle behavior of rocks.

An envelope-based machine learning workflow for locating earthquakes in the southern Sichuan Basin

The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°, 0.02°, 2 ​km, and 1.25 ​s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.

The upper crustal shear wave structure of the Zagros collision zone from local earthquake Rayleigh wave tomography

The Zagros fold-and-thrust belt is the principal response to the Arabia–Eurasia continental collision, which generates significant seismic activity in Iran. Surface wave tomography can be a proper tool for crustal structure imaging in this region. We used observed dispersion curves of Rayleigh wave derived from high-quality local-earthquake waveforms to obtain 2D tomographic maps in the period range 1–28 s beneath the Zagros collision zone. Subsequently, local pseudo-dispersion curves for individual grid points are inverted for shear-wave velocity structure, in order to obtain a 3D velocity model of the crust. Our results indicate shallow low-velocity structures near the suture zone. Moreover, a low-velocity flexure shape in the south of the Zagros Mountain Front Fault could be due to the thick sedimentary basin beneath the Dezful embayment. Relatively an uplifting of the deeper structures beneath Sanandaj-Sirjan and the high Zagros might could be led to high-velocity structures at mid-crustal depths. The variation of shear-wave velocity along the Zagros indicates the inhomogeneous structures along this folding and thrust belt.