Dense Array Data Research Articles

Earthquake migration characteristics and triggering mechanisms in the Baihetan Reservoir Area based on machine-learning microseismic detection

SUMMARY The Baihetan Reservoir, the second largest in the world, is located at the intersection of multiple large active fault zones on the eastern boundary of the Sichuan-Yunnan rhombic block. After impoundment on 6 April 2021, many earthquakes occurred around the reservoir area submerged by water. The largest ML 4.7 earthquake in the reservoir area occurred after the water level reached its highest point. But the seismogenic structures and mechanisms of earthquakes in the reservoir area are still unclear. Based on dense array data from the reservoir area, this paper uses the experimental site submodel of USTC-Pickers, transfer learned with ‘DiTing’ data set of China to obtain a high-precision earthquake catalogue that is twice as large as that the manual catalogue. This study show that earthquakes in the reservoir region primarily occur on secondary faults of pre-existing ones, characterized by a prominent feature of high dip angles trending northwest to southeast. Combined with the spatiotemperal migration characteristics of earthquakes and the relationship between earthquakes and water levels, we infer that most earthquakes are rapid response type and may be induced by rapid increase in elastic stress. Only the spatiotemporal distribution image of the ML 3.2 earthquakes sequence in the dam site-Toudaogou section conforms to the law of pore pressure diffusion, and belongs to the fast response type, which may be induced by the poroelasiticity coupling mechanism. The ML 3.0 earthquake swarm with deep depths in the Heishui River section belongs to the delayed response type and may be induced by the poroelasiticity coupling mechanism.

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

AbstractWe develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. The utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed. Program summaryProgram Title: EVPFFTCPC Library link to program files:https://doi.org/10.17632/2k8579fyyv.1Developer's repository link:https://github.com/lanl/FierroLicensing provisions: BSD 3-Clause LicenseProgramming language: C++External routines/libraries: MPI, Kokkos, MATAR, HeFFTe, HDF5Nature of problem: EVPFFT is a crystal plasticity code designed to compute micro-mechanical fields within a polycrystalline representative volume element (RVE) and predict the macroscale response of the RVE.Solution method: EVPFFT uses the periodic Green's function method in Fourier space to solve the field equations of static stress equilibrium in a periodic spatial domain.

Pervasive Crustal Volcanic Mush in the Highly Stretched Sunda Plate Margin of Northern Sumatra

AbstractArc volcanism, crustal deformation, and their interplay are poorly understood in northwestern Sumatra. Traditional receiver function H‐κ stacking studies constrain the variations in crustal thickness and Vp/Vs ratio in volcanic zones but rarely estimate the melt fractions. Here, we propose a H‐Φ stacking method, a variant of the H‐κ stacking method, and apply it to the dense nodal array data from Aceh, northern Sumatra, to estimate crustal thickness, Vp/Vs ratio, and melt fraction. Most results show considerably high Vp/Vs ratios (∼1.98) and melt fractions (up to 19%), indicating pervasive crustal magmatic mush. The northwestern edge of the Aceh crust is much thinner (∼22 km) than extended crust globally, reflecting a highly stretched crust due to tectonic processes governing the opening of the Andaman Sea. This thin crust and high melt fractions explain the Bouguer gravity anomaly, and partly explain the northward migration of Quaternary volcanics.

Multi-Mode Surface Wave Tomography of a Water-Rich Layer of the Jizhong Depression Using Beamforming at a Dense Array

Urban structure imaging using noise-based techniques has rapidly developed in recent years. Given the complexity of the cross-correlation function in high-frequency signals, here, the beamforming (BF) method was used to analyze one data set taken from a dense array in the Jizhong Depression and obtain multi-mode dispersion curves. Multi-mode surface waves improved inversion stability, reduced non-uniqueness, and yielded a one-dimensional shear wave (S-wave) velocity model. Interpolation yielded a high-resolution three-dimensional (3D) S-wave velocity model for the study area. The model shows that velocity gradually changed in the horizontal direction and greatly increased in the vertical direction, which is largely consistent with changes in the sedimentary environment related to the continuous subsidence of the Jizhong Depression since the Quaternary. A low-velocity anomaly at a depth of ~300–400 m was revealed and determined to be caused by either a deep-buried ancient river course or low-lying area. This study demonstrates the potential of the BF method for processing dense array data sets of urban exploration. The high-resolution 3D S-wave velocity model provides a new reference for studying the Quaternary structure of the Jizhong Depression, as well as groundwater resources, urban infrastructure, and underground spaces.

Updated absolute gravity rate of change associated with glacial isostatic adjustment in Southeast Alaska and its utilization for rheological parameter estimation

In Southeast Alaska (SE-AK), rapid ground uplift of up to 3 cm/yr has been observed associated with post-Little Ice Age glacial isostatic adjustment (GIA). Geodetic techniques such as global navigation satellite system (GNSS) and absolute gravimetry have been applied to monitor GIA since the last 1990s. Rheological parameters for SE-AK were determined from dense GNSS array data in earlier studies. However, the absolute gravity rate of change observed in SE-AK was inconsistent with the ground uplift rate, mainly because few gravity measurements from 2006 to 2008 resulted in imprecise gravity variation rates. Therefore, we collected absolute gravity data at six gravity points in SE-AK every June in 2012, 2013, and 2015, and updated the gravity variation rate by reprocessing the absolute gravity data collected from 2006 to 2015. We found that the updated gravity variation rate at the six gravity points ranged from −2.05 to −4.40 upmuGal/yr, and its standard deviation was smaller than that reported in the earlier study by up to 88 %. We also estimated the rheological parameters under the assumption of the incompressible Earth to explain the updated gravity variation rate, and their optimal values were determined to be 55 km and 1.2 times 10^{19} Pa s for lithospheric thickness and upper mantle viscosity, respectively. These optimal values are consistent with those independently obtained from GNSS observations, and this fact indicates that absolute gravimetry can be one of the most effective methods in determining sub-surface structural parameters associated with GIA accurately. Moreover, we utilized the gravity variation rates for estimating the ratio of gravity variation to vertical ground deformation at the six gravity points in SE-AK. The viscous ratio values were obtained as −0.168 and −0.171 upmuGal/mm from the observed data and the calculated result, respectively. These ratios are greater (in absolute) than those for other GIA regions (−0.15 to −0.16 upmuGal/mm in Antarctica and Fennoscandia), because glaciers in SE-AK have melted more recently than in other regions.Graphical

Ambient noise tomography for a high-resolution 3D S-wave velocity model of the Kinki Region, Southwestern Japan, using dense seismic array data

Research interest in the Kinki region, southwestern Japan, has been aroused by the frequent occurrence of microearthquake activity that do not always coincide with documented active fault locations. Previous studies in the Kinki region focused mainly on deep, large-scale structures and could not efficiently resolve fine-scale (~ 10 km) shallow crustal structures. Hence, characterization of the upper crustal structure of this region at an improved spatial resolution is required. From the cross-correlation of the vertical components of the ambient seismic noise data recorded by a densely distributed seismic array, we estimated Rayleigh wave phase velocities using a frequency domain method. Then, we applied a direct surface wave tomographic method for the measured phase velocity dispersion data to obtain a 3D S-wave velocity model of the Kinki region. The estimated velocity model reveals a NE–SW trending low-velocity structure coinciding with the Niigata–Kobe Tectonic Zone (NKTZ) and the active Biwako-seigan Fault Zone (BSFZ). Also, we identified fine-scale low-velocity structures coinciding with known active faults on the eastern side of the NKTZ, as well as sets of low-velocity structures across the Tanba region. Furthermore, sedimentary basins manifest as low-velocity zones extending to depths ranging from ~ 1.5 to 2 km, correlating with those reported in previous studies. Our results therefore contribute towards fundamental understanding of earthquake faulting as well as tectonic boundary and will be useful for hazard assessment and disaster mitigation.Graphical abstract

The Investigation of Shallow Structures at the Meishan Fault Zone with Ambient Noise Tomography Using a Dense Array Data

Seismic monitoring relies on seismography. However, the high cost of seismic equipment has presented a challenge to increasing the density of seismic networks in previous decades. Due to the large station spacing and inferior coverage of stations, this situation has led to a loss of detail in many research results. Along with the improvement of technology, the problem of increasing the density of seismographic observations is no longer an impossible issue. This makes it feasible to deploy a dense seismic network for monitoring earthquakes. This study deployed a linear dense array across the Meishan Fault in west-southern Taiwan for the purpose of analyzing the shallow fault zone structure. While the 1906 Meishan earthquake occurred in a period when historic records were available, the surficial geology surveys of the Meishan Fault are challenging because farming and construction engineering have obscured the outcrop. Early surveys of the Meishan Fault were mainly seismic surveys. In recent decades, over thirty profiles have been completed. However, the reflection seismic records had poor signal-to-noise ratios because the Meishan Fault is buried under thick sediments. Thus, the shallow structure of the Meishan Fault is still not known in detail. This study applied double-beamforming tomography to a dense seismic array to obtain high-resolution images of the Meishan Fault zone. The result shows that there is a south-dipping interface near the fault trace as indicated by the Central Geological Survey of Taiwan. In addition, we observed velocity transitions of perturbation profiles that may be caused by a branch fault, the Chentsoliao Fault. This study demonstrates that the ambient noise double beamforming method is an effective tool for imaging the detailed shallow structure along with the dense seismic array.

Toward improved urban earthquake monitoring through deep-learning-based noise suppression.

Earthquake monitoring in urban settings is essential but challenging, due to the strong anthropogenic noise inherent to urban seismic recordings. Here, we develop a deep-learning-based denoising algorithm, UrbanDenoiser, to filter out urban seismological noise. UrbanDenoiser strongly suppresses noise relative to the signals, because it was trained using waveform datasets containing rich noise sources from the urban Long Beach dense array and high signal-to-noise ratio (SNR) earthquake signals from the rural San Jacinto dense array. Application to the dense array data and an earthquake sequence in an urban area shows that UrbanDenoiser can increase signal quality and recover signals at an SNR level down to ~0 dB. Earthquake location using our denoised Long Beach data does not support the presence of mantle seismicity beneath Los Angeles but suggests a fault model featuring shallow creep, intermediate locking, and localized stress concentration at the base of the seismogenic zone.

Contrasting crustal structures crossing the boundary region of the southwest Ordos block and its tectonic implications revealed by dense seismic arrays

High-resolution images of the crust were obtained along two high-density temporary seismic arrays that cross tectonic blocks in the southwest boundary of the Ordos block and its adjacent regions. Dense stations with <1-km station spacings allowed teleseismic receiver functions to unveil the unprecedented details of crustal structures from the northeast margin of the Tibetan Plateau and the Qinling orogenic belt to the southwest Ordos block. The observations from nearby broadband seismic stations and two-dimensional numerical simulation were used to verify the reliability and validity of our results from the temporary dense array data. The receiver function profiles and the migration images revealed the contrasting crustal structures beneath the southwest Ordos block and the adjacent regions. Liupanshan mountain is a boundary that resists the lateral growth of the Tibetan Plateau; however, the slight bending of the Moho indicates absence of large-scale deformation in west Liupanshan. The Moho transition zone beneath the Weihe graben and southwest corner of the Ordos block represented by the complicated P-to-S converted phases can be contributed to the eastward extrusion of hot uppermost mantle from the Tibetan Plateau driven by the mantle flow.

Seismic Site Response Inferred From Records at a Dense Linear Array Across the Chenghai Fault Zone, Binchuan, Yunnan

AbstractLow‐velocity zones (LVZ) in the shallow crust such as basins infilled with unconsolidated sediments could significantly amplify seismic waves and cause intense ground motions. In this study, we estimate the seismic site response in the Binchuan basin across the active Chenghai fault zone in northwest Yunnan Province, Southwest China using data from a large‐aperture (∼8 km) dense linear array of 125 three‐component seismometers deployed in 2018 for ∼1 month. We observe that local earthquakes with larger epicentral distances tend to produce stronger spatial variability in peak ground velocity (PGV) across the array. The PGV values are overall larger in the middle of the array than the two sides, especially in the horizontal directions, which is consistent with both tomographic and traveltime results. Using both nearby and distant earthquakes, we find that horizontal ground motions from 0.2 to 2 Hz at stations inside the LVZ are up to 20 times as large as that outside, and a more localized zone (∼500 m wide) enclosing the fault surface trace is characterized by broader frequency bands and larger factors of amplification. As the distance from the fault increases, amplification factors become smaller while the lower limit of the amplification frequency band gradually increases. Variations in predicted ground motion from one‐dimensional SH‐wave modeling reveal amplification and attenuation effects of the LVZ, suggesting that strong lateral heterogeneity should be considered. Our results demonstrate that based on dense array data, analyzing seismic site response is an alternative method to effectively constrain the shallow subsurface fault structure.

On the non‐recursive implementation of multistage sampling without replacement

Variance estimation in multistage sampling without replacement usually requires considerable computational effort. One option is to implement explicit formulas on a computer, at least for some specific sampling designs. This approach becomes quite cumbersome to handle beyond two stages, both from the formulation and computer implementation points of view. Another option is to provide a general method to compute variance estimates for any number of stages. Such an approach may involve data structures and estimators which are recursively defined.•The solution we present in this article is intended to be both general and computationally efficient by relying on a full-iterative implementation.•The definition of the estimators remains implicit as in the recursive approach, but is expressed in terms of recurrence relations translated into iterative algorithms.•These algorithms rely only on (dense) array data structures. Moreover, most of the necessary computer memory is only used during preliminary steps and is not required when performing the statistical calculations.

Detailed space–time variations of the seismic response of the shallow crust to small earthquakes from analysis of dense array data

SUMMARYWe compute high-resolution space–time variations of subsurface seismic properties from autocorrelation functions (ACF’s) of noise and local earthquakes, recorded by the Sage Brush Flat dense array deployed around the Clark branch of the San Jacinto fault. The resolved temporal changes are referred to as apparent velocity changes because they reflect both nonlinear response and variations of material properties such as cracking and damage. Apparent velocity changes are estimated at four frequency bands (10–15, 10–20, 15–30 and 20–40 Hz) for two local earthquake data sets. In one analysis, ACF’s from P- and S-wave windows of 31 small events with magnitudes below 3.1 are used to compute the apparent velocity variations with respect to the mean ACF of each phase, and we also use the mean ACF of noise data as reference to estimate the changes. In a further analysis, the temporal evolution of properties is computed using moving time windows in continuous waveform over one-hour long data with noise and earthquake signals. The apparent velocity changes and recovery times are frequency dependent and present a strong spatial variability across the array. The resolved changes are larger and recovery time shorter with data associated with higher frequencies. At frequencies larger than 15 Hz, and using the mean ACF of noise data as a reference, the apparent average velocity changes across the array during the passage of the P and S waves from the small local events are 2.5 per cent and 6 per cent, respectively. The apparent velocity changes decrease by one order of magnitude when the earthquake data are used as a reference. The relatively large changes in response to very low ground motion have important implications on nonlinear processes involving degradation and healing of the subsurface material during common earthquake shaking.

Shallow Basin Structure and Attenuation Are Key to Predicting Long Shaking Duration in Los Angeles Basin

AbstractGround motions in the Los Angeles Basin during large earthquakes are modulated by earthquake ruptures, path effects into the basin, basin effects, and local site response. We analyzed the direct effect of shallow basin structures on shaking duration at a period of 2–10 s in the Los Angeles region through modeling small magnitude, shallow, and deep earthquake pairs. The source depth modulates the basin response, particularly the shaking duration, and these features are a function of path effect and not site condition. Three‐dimensional simulations using the CVM‐S4.26.M01 velocity model show good fitting to the initial portion of the waveforms at periods of 5 s and longer but fail to predict the long shaking duration during shallow events, especially at periods less than 5 s. Simulations using CVM‐H do not match the timing of the initial arrivals as well as CVM‐S4.26.M01, and the strong late arrivals in the CVM‐H simulation travel with an apparent velocity slower than observed. A higher‐quality factor than traditionally assumed may produce synthetics with longer durations but is unable to accurately match the amplitude and phase. Beamforming analysis using dense array data further reveals the long duration surface waves have the same back azimuth as the direct arrivals and are generated at the basin edges, while the later coda waves are scattered from off‐azimuth directions, potentially due to strong, sharp boundaries offshore. Improving the description of these shallow basin structures and attenuation model will enhance our capability to predict long‐period ground motions in basins.

Characterization with dense array data of seismic sources in the shallow part of the San Jacinto fault zone

SUMMARY We analyse dominant sources identified in a catalogue of more than 156 000 localizations performed using a 26-d data set recorded by a dense array set on the San Jacinto fault near Anza, in California. Events were localized using an array processing technique called Match Field Processing. As for all array processing techniques, the quality of the event position decrease when the events are outside of the array. We thus separate localizations in and outside the array using simple geometrical conditions. We compare the time distribution of the localization to additional data such as meteorological data, day of human activity as well as existing catalogues to determine the nature of the dominant events located using our method. We find that most of the events located outside of the array could be attributed to a surface structure excited by wind. On the other hand, part of the localizations under the array occur during regional earthquakes and could correspond to diffraction on the fault's heterogeneities. The rest of the localizations inside the array could be generated by the fault itself.

Seismic Azimuthal Anisotropy for the Southeastern Tibetan Plateau Extracted by Wave Gradiometry Analysis

AbstractWave Gradiometry (WG) is a dense array data processing method used to extract seismic velocity and other properties of the earth. In this study, we propose using WG for a plane wave field to measure azimuthal anisotropy by fitting the phase velocities from different back azimuths. We applied this new method to the Temporary Western Sichuan Array and obtained the isotropic and azimuthal anisotropy for period bands centered at T = 20, 40, and 60 s in the southeast Tibetan Plateau. Our results show that the fast orientations of anisotropy are well consistent with the strikes of the fault system and orogenic belt. The weak anisotropic magnitude in the northern part of the south Chuandian subblock and a consistence of fast orientation in boundary fault zone (BFZ) at different periods may be attributed to anisotropic relics associated with the Emeishan Large Igneous Province. Comparing our results with those of previous studies, we found that our anisotropic results are consistent with anisotropic structures measured by the Pms phase in the plateau area, while a systematical angular difference exists in the BFZ, Sichuan Basin, and south Chuandian subblock where high Rayleigh wave phase velocity was observed. The Lijiang‐Xiaojin fault and Longmenshan fault appear to form a deep‐rooted strong boundary at the lithospheric scale, as they serve as a boundary for anisotropic structures, isotropic velocity, and the other three WG parameters.

Brain Networks Communicate Through Theta Oscillations to Encode High Load in a Visuospatial Working Memory Task: An EEG Connectivity Study.

The encoding of visuospatial information is the foremost and indispensable step which determines the outcome in a visuospatial working memory (VSWM) task. It is considered to play a crucial role in limiting our ability to attend and process only 3-5 integrated items of information. Despite its importance in determining VSWM performance, the neural mechanisms underlying VSWM encoding have not been clearly differentiated from those involved during VSWM retention, manipulation and/or retrieval. The high temporal resolution of electroencephalography (EEG) and improved spatial resolution with dense array data acquisition makes it an ideal tool to study the dynamics in the functional brain connectivity during a cognitive task. In the present study, the changes in the functional brain connectivity due to memory load during VSWM encoding were studied using 128-channel EEG. Lagged linear coherence (LagR) was computed between 84 regions of interest (ROIs) defined according to the Brodmann areas for seven EEG frequency bands: delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-45Hz). Interestingly, out of seven EEG frequency bands investigated in the current study, LagR of only theta band varied significantly in 13 brain connections due to memory load during VSWM encoding. LagR of theta band increased significantly at high memory load when compared to low memory load in twelve brain connections with the maximum change observed between right cuneus and right middle temporal gyrus (Cohen's d = 0.836), indicating the integration of brain processes to confront the increase in memory demands. Theta LagR decreased significantly between left postcentral gyrus and right precentral gyrus at high memory load as compared to low memory load, which might have a role for sustaining attention during encoding. Change in the LagR values due to memory load between fusiform gyrus and lingual gyrus in the right hemisphere had a positive correlation (r = 0.464, p = 0.003) with the error rate, signifying the crucial role played by these two regions in predicting the performance. The current study has not only identified the neural connections that are responsible for the formation of working memory traces during VSWM encoding, but also support the notion that encoding is a rate-limiting process underlying our memory capacity limit.

Detection of random noise and anatomy of continuous seismic waveforms in dense array data near Anza California

SUMMARY We develop a methodology to separate continuous seismic waveforms into random noise (RN), not random noise (NRN) produced by earthquakes, wind, traffic and other sources of ground motions, and an undetermined mixture of signals. The analysis is applied to continuous records from a dense seismic array on the San Jacinto fault zone. To detect RN signals, we cut hourly waveforms into non-overlapping 1 s time windows and apply cross-correlations to separate RN candidates from outliers. The cross-correlation coefficients between different RN candidates fall into a tight range (i.e. 0.09–0.35), while cross-correlation coefficients of RN candidates with NRN signals (e.g. seismic or air-traffic events) are lower. The amplitude spectra of RN candidates have a well-defined level, while the amplitude spectra of other signals deviate from that level. Using these properties, we examine the amplitude spectra of moving time windows and cross-correlation coefficients with RN templates in each hour. The hourly RN is quasi-stationary and the results cluster tightly in the parameter space of cross-correlation coefficients and L2 norm deviations from the mean spectra of RN candidates. Time windows with parameters in this tight cluster are identified as RN, windows that deviate significantly from the RN cluster are identified as NRN and windows with values in between are identified as mixed signals. Several iterations on each hourly data are used to update and stabilize the selection of RN templates and mean noise spectra. For the days examined, the relative fractions of RN, NRN and mixed signals in local day (night) times are about 26 (42 per cent), 40 (33 per cent) and 34 per cent (25 per cent), respectively.

Analysis of surface and seismic sources in dense array data with match field processing and Markov chain Monte Carlo sampling

SUMMARY We introduce a methodology based on array processing to detect and locate weak seismic events in a complex fault zone environment. The method is illustrated using data recorded by a dense array of 1108 vertical component geophones in a 600 m × 600 m area on the Clark branch of the San Jacinto Fault. Because surface and atmospheric sources affect weak ground motion, it is necessary to discriminate them from weak seismic sources at depth. Source epicentral positions and associated apparent velocities are extracted from continuous seismic waveforms using Match Field Processing (MFP). We implement MFP at specific frequencies targeting surface and subsurface sources, using for computational efficiency a forward model of acoustic source in a homogenous medium and Markov Chain Monte Carlo sampling. Surface sources such as Betsy gun shots and a moving vehicle are successfully located. Weak seismic events are also detected outside of the array, and their backazimuth angle is retrieved and found to be consistent with the fault geometry. We also show that the homogeneous acoustic model does not yield satisfying results when extracting microseismic event depth, because of the ambiguity between depth and the apparent velocity based on surface data.

Earthquake-induced prompt gravity signals identified in dense array data in Japan

Earthquake ruptures cause mass redistribution, which is expected to induce transient gravity perturbations simultaneously at all distances from the source before the arrival of P-waves. A recent research paper reported the detection of such prompt gravity signals from the 2011 Tohoku-Oki earthquake by comparing observed acceleration waveforms and model simulations. The 11 observed waveforms presented in that paper recorded in East Asia shared a similar trend above the background seismic noise and were in good agreement with the simulations. However, the signal detection was less quantitative because the significance of the observed signals was not discussed and the waveforms at other stations in the region were not shown. In this study, similar trends were not observed in most of the data recorded near the stations used in the aforementioned study, suggesting that the reported signals were only local noises. We thus took a different approach to identify the prompt signals. We optimized the multi-channel data recorded by superconducting gravimeters, broadband seismometers, and tiltmeters. Though no signal was identified in the single-trace records, the stacked trace of the broadband seismometer array data in Japan showed a clear signal above the reduced noise level. The signal amplitude was 0.25 nm/s2 for an average distance of 987 km from the event hypocenter. This detection was confirmed with a statistical significance of 7σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$7\\sigma$$\\end{document}, where σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma$$\\end{document} is the standard deviation of the amplitude of the background noise. This result provided the first constraint on the amplitude of the observed prompt signals and may serve as a reference in the detection of prompt signals in future earthquakes.