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Temporary seismic networks on Mt. Halla and Ulleung Island volcanoes were deployed, which employ broadband and geophone arrays to monitor potential volcanic activities and to estimate high-resolution magmatic structures beneath these volcanoes. The purpose of this paper is to introduce these networks and present early results through basic seismic analyses, suggesting the potential for future comprehensive seismological studies. The array in Mt. Halla volcano consists of five broadband sensors (JH array), and it has been operational around the Baengnokdam summit crater since October 2020. There was an additional linear geophone array (HL array) installed in September 2021 for detailed shallow subsurface imaging. Ulleung Island volcano had been under observation for two years since June 2021 with a network of nine broadband sensors (UL array) along its coast and in the Nari crater basin, complemented by a 52-geophone array (UG array) deployed in May 2022 for high-resolution subsurface studies. Despite the noisy environments typical of temporary setups, power spectral density analyses confirmed the quality of data as comparable to established reference noise models in permanent stations. Our study aimed to initiate studies uncovering seismic activities and structures beneath Mt. Halla and Ulleung Island volcanoes, specifically regarding volcanic activity. This approach detected no clear sign of volcanic seismicity on both islands, suggesting a period of magmatic dormancy. Seismic velocity variation (dv/v) analyses further indicated that environmental factors, rather than volcanic processes, influenced the changes in the physical properties of the underground structures. Conversely, the receiver function analysis and ambient noise data processing hinted at the presence of complex subsurface structures, potentially indicative of volcanic features, such as partial melting. Despite the lack of direct evidence for active magmatic processes, the collected seismic data provides a crucial baseline for future monitoring and a deeper understanding of the magmatic and tectonic dynamics beneath these volcanoes, offering valuable insights for ongoing volcanic research. [ABSTRACT FROM AUTHOR]

Within the framework of the Intercontinental Scientific Drilling Programme (ICDP) 'Drilling the Eger Rift' project, five boreholes were drilled in the Vogtland (Germany) and West Bohemia (Czech Republic) regions. Three of them will be used to install high‐frequency three‐dimensional (3D) seismic arrays. The pilot 3D array is located 1.5 km south of Landwüst (Vogtland). The borehole, with a depth of 402 m, was equipped with eight geophones and a fibre optic cable behind the casing used for distributed acoustic sensing (DAS) measurements. The borehole is surrounded by a surface array consisting of 12 seismic stations with an aperture of 400 m. During drilling, a highly fractured zone was detected between 90 m and 165 m depth and interpreted as a possible fault zone. To characterize the fault zone, two vertical seismic profiling (VSP) experiments with drop weight sources at the surface were conducted. The aim of the VSP experiments was to estimate a local 3D seismic velocity tomography including the imaging of the steep fault zone. Our 3D tomography indicates P‐wave velocities between 1500 m/s and 3000 m/s at shallow depths (0–20 m) and higher P‐wave velocities of up to 5000 m/s at greater depths. In addition, the results suggest a NW–SE striking low‐velocity zone (LVZ; characterized by Vp$V_p$ = 1500–3000 m/s), which crosses the borehole at a depth of about 90–165 m. This LVZ is inferred to be a shallow non‐tectonic, steep fault zone with a dip angle of about 60∘$60^{\circ }$. The depth and width of the fault zone are supported by logging data as electrical conductivity, core recovery and changes in lithology. In this study, we present an example to test and verify 3D tomography and imaging approaches of shallow non‐tectonic fault zones based on active seismic experiments using simple surface drop weights as sources and borehole chains as well as borehole DAS behind casing as sensors, complemented by seismic stand‐alone surface arrays. [ABSTRACT FROM AUTHOR]

Accurately estimated quarry blast equivalents can be compared with the quantity of initiated explosives to detect misfires or undetonated explosive remnants, thereby ensuring safe mining operations. Seismic waves are commonly used to estimate the equivalent; however, the ability of permanent seismic networks to detect low-magnitude events is limited. Therefore, we conducted experiments in the Minglongshan–Shangyao fault segment of the Tan–Lu fault zone in the Chuzhou area of Anhui Province in China, deploying six shallow-borehole short-period seismometers at a burial depth of 1 m for continuous monitoring for 20 days. Forty-two earthquakes were detected using a convolutional neural network, and the detected earthquakes were processed based on the source location, frequency spectrum analysis, time of occurrence, equivalent, and magnitude statistics. Through comparison, we found that one of the earthquakes was the M3.1 Suqian earthquake on March 19, 2022. Unlike this natural earthquake, the remaining 41 earthquakes have not been reported by any seismic network. The source location is concentrated, the frequency spectrum is simple, and the time of occurrence is concentrated in the daytime. Based on these results and the widespread quarries in this area, we speculate that these 41 earthquakes were caused by artificial blasting. Through seismic array monitoring, the precise locations of quarry blasts can be determined. Furthermore, the seismic wave energy-blast equivalent algorithm can be used to accurately estimate the quarry blast equivalent. [ABSTRACT FROM AUTHOR]

A major aim in the study of crustal fluids is the development of automatic methodologies for monitoring deep‐source, non‐volcanic gas emissions' spatio‐temporal evolution. Crustal fluids play a significant role in the generation of large earthquakes and the characterization of their emissions on the surface can be essential for better understanding crustal processes generating earthquakes. We investigate seismic tremors recorded over 4 days in 2019 at the Mefite d'Ansanto (southern Apennines, Italy) that is located at the northern end of the fault system that generated the Mw 6.9 1980 Irpinia Earthquake. The Mefite d'Ansanto is hypothesized to be the largest natural, non‐volcanic, CO2‐rich gas emission on Earth. The seismic tremor is studied by employing a dense temporary seismic network and an automated detection algorithm based on non‐parametric statistics of the recorded signal amplitudes. We extracted signal characteristics (RMS amplitude and statistical moments of amplitudes both in time and frequency domains) for use in the subsequent supervised machine‐learning classification of the target tremor and accidently detected anthropogenic and background noise. The data set is used for the training and optimization of station‐based KNN (k‐Nearest‐Neighbors) binary classifiers obtaining good classification performances with a median overall accuracy across all stations of 92.8%. The classified tremor displayed common features at all stations: variable duration (16 s to 30–40 min), broad peak frequency (4–20 Hz) with varying amplitudes, and two types of signals: (a) long‐duration, high‐amplitude tremor and (b) pulsating tremor. Higher tremor amplitudes recorded at stations closer to local bubbling and pressurized vents suggest multiple local tremor sources. Key Points: A dense temporary seismic array enabled the acquisition of emission‐related seismic tremor at the Mefite d'Ansanto siteA detection algorithm and supervised machine‐learning approach for the identification and classification of tremors has been developedNew insights on the emission tremor would help to monitor the CO2 degassing at the Mefite d'Ansanto and its temporal evolution [ABSTRACT FROM AUTHOR]

Abstract A major aim in the study of crustal fluids is the development of automatic methodologies for monitoring deep‐source, non‐volcanic gas emissions’ spatio‐temporal evolution. Crustal fluids play a significant role in the generation of large earthquakes and the characterization of their emissions on the surface can be essential for better understanding crustal processes generating earthquakes. We investigate seismic tremors recorded over 4 days in 2019 at the Mefite d’Ansanto (southern Apennines, Italy) that is located at the northern end of the fault system that generated the Mw 6.9 1980 Irpinia Earthquake. The Mefite d’Ansanto is hypothesized to be the largest natural, non‐volcanic, CO2‐rich gas emission on Earth. The seismic tremor is studied by employing a dense temporary seismic network and an automated detection algorithm based on non‐parametric statistics of the recorded signal amplitudes. We extracted signal characteristics (RMS amplitude and statistical moments of amplitudes both in time and frequency domains) for use in the subsequent supervised machine‐learning classification of the target tremor and accidently detected anthropogenic and background noise. The data set is used for the training and optimization of station‐based KNN (k‐Nearest‐Neighbors) binary classifiers obtaining good classification performances with a median overall accuracy across all stations of 92.8%. The classified tremor displayed common features at all stations: variable duration (16 s to 30–40 min), broad peak frequency (4–20 Hz) with varying amplitudes, and two types of signals: (a) long‐duration, high‐amplitude tremor and (b) pulsating tremor. Higher tremor amplitudes recorded at stations closer to local bubbling and pressurized vents suggest multiple local tremor sources.

The Southern San Andreas Fault (SSAF) in California is one of the most thoroughly studied faults in the world, but its configuration at seismogenic depths remains enigmatic in the Coachella Valley. We use a combination of space geodetic and seismic observations to demonstrate that the relatively straight southernmost section of the SSAF, between Thousand Palms and Bombay Beach, is dipping to the northeast at 60–80° throughout the upper crust (<10 km), including the shallow aseismic layer. We constrain the fault attitude in the top 2–3 km using inversions of surface displacements associated with shallow creep, and seismic data from a dense nodal array crossing the fault trace near Thousand Palms. The data inversions show that the shallow dipping structure connects with clusters of seismicity at depth, indicating a continuous throughgoing fault surface. The dipping fault geometry has important implications for the long‐term fault slip rate, the intensity of ground shaking during future large earthquakes, and the effective strength of the southern SAF. Plain Language Summary: The San Andreas Fault (SAF) is capable of large, destructive earthquakes and poses significant seismic hazard in California. In the Coachella Valley, the geometry of the SAF beneath the Earth's surface has been the subject of much debate. Here, we present new constraints on the fault's structure in the uppermost 2–3 km of the crust from several new sets of observations. We measure slow movement of the fault at the surface using satellite‐based radar and perform simulations of what fault geometry is most likely to produce the observed motion. We also installed an array of sensors across the SAF to measure seismic waves that travel through or reflect off the fault. Analysis of both data sets indicates that the shallow portion of the SAF dips to the northeast in the Coachella Valley. Precise locations of small earthquakes at greater depths exhibit a similar trend—we thus suggest the fault dips throughout the Earth's crust. Better understanding the geometry of this section of the SAF has implications for earthquake hazards in Southern California, as well as the fault's geologic history. Key Points: InSAR measurements and models of shallow creep on the southernmost San Andreas Fault indicate a moderate‐to‐steep northeast fault dipSeismic imaging using data from a dense array deployed near Thousand Palms reveal northeast dipping fault damage zonesA joint interpretation of available data suggests that the northeast dip persists throughout the upper 10 km of the crust [ABSTRACT FROM AUTHOR]

The exploration of the deep structure of the earth is the core part of geophysical research. Seismic body waves can penetrate deep into the earth with a high resolution and it is an indispensable technical means for studying the internal structure of the earth. The rapid development of technology for extracting high signal-to-noise ratio body wave signals based on ambient noise has greatly promoted the development and application of seismology, making it increasingly play an important role in the imaging of deep earth structures and shallow urban space exploration. This article reviews in detail how to use seismic interferometry and array processing technology to extract various types of body wave signals for research on different detection scales (local, regional, global). Among them, the seismic interferometry cross-correlates the waveform signals recorded by the seismic stations to cancel out the coincident ray paths, and finally the seismic records between the station pairs are obtained; and the array processing method is based on the data developed by the receiver array processing means. This technology can not only further improve the signal-to-noise ratio (SNR), but also obtain position information. Generally speaking, since the energy of the body wave signal contained in the ambient noise is much weaker than that of the surface wave signal, it is difficult to extract. This article focuses on the Bin stack method, the double beamforming method (DBF) and the phase-weighted stacks method (PWS), and concludes the applicable conditions of the three methods.

In this paper, we present the work carried out to characterize the spatial variability of seismic site response related to local soil conditions in the city of Milan and its surroundings, an area with ∼3 million inhabitants and a high density of industrial facilities. The area is located at the northwestern end of the Po Plain, a large and deep sedimentary basin in northern Italy. An urban-scale seismo-stratigraphic model is developed based on new passive and active seismic data, supported by the available geological data and stratigraphic information from shallow and deep vertical wells. In particular, 33 single-station and 4 ambient-vibration array measurements are acquired, together with 4 active multichannel analyses of surface waves (MAWS). To estimate the resonant frequencies of the sediments, the horizontal to vertical spectral ratio technique (HVSR) is applied to the ambient-vibration recordings, whereas to determine the Rayleigh-wave dispersion curves from the passive array, the data are analysed using the conventional frequency-wavenumber, the modified spatial autocorrelation and the extended spatial autocorrelation (ESAC) techniques. The array data are used to determine the local shear wave velocity profiles, VS, via joint inversion of the Rayleigh-wave dispersion and ellipticity curves deduced from the HVSR. The results from HVSR show three main bands of amplified frequencies, the first in the range 0.17–0.23 Hz, the second from 0.45 to 0.65 Hz and the third from 3 to 8 Hz. A decreasing trend of the main peaks is observed from the northern to the southern part of the city, allowing us to hypothesize a progressive deepening of the relative regional chrono-stratigraphic unconformities. The passive ambient noise array and MASW highlight the dispersion of the fundamental mode of the Rayleigh-wave in the range 0.4–30 Hz, enabling to obtain detailed Vs. profiles with depth down to about 1.8 km. The seismo-stratigraphic model is used as input for 1D numerical modelling assuming linear soil conditions. The theoretical 1D transfer functions are compared to the HVSR curves evaluated from both ambient noise signals and earthquake waveforms recorded by the IV. MILN station in the last 10 years.

In this paper, we consider the problem of estimating the apparent slowness vector p of a plane P wave caused by a regional seismic event and recorded by a small-aperture seismic array. The case is considered when strong non-stationary and non-Gaussian random interferences act on the array sensors. In this case, the well-known estimate of wideband frequency-wave-number analysis (WFK) becomes ineffective due to large estimation errors. We have proposed three new algorithms for estimating the vector p that are robust i.e. resistant to changes in the statistical properties of the random interferences. They mainly use information about the slowness vector contained in the phases of the spectra of seismograms recorded by the array sensors. An intensive Monte Carlo simulation was carried out to compare the accuracy of the proposed phase-based estimates with the accuracy of WFK-estimate in the case when non-stationary and non-Gaussian anthropogenic interferences act on the array sensors. In the simulation we used synthetic mixtures of signals caused by a seismic event and anthropogenic seismic interferences. These signals and interferences were recorded by real small-aperture seismic arrays. It was shown that the proposed phase-based estimates of the vector p provide significantly better accuracy than traditional WFK-estimate in the case of strong anthropogenic interferences, and have approximately the same accuracy in the case of white Gaussian noise. [ABSTRACT FROM AUTHOR]

The purpose of seismic data processing in nuclear explosion monitoring is to accurately and reliably detect seismic or explosion events from complex ambient noises. Accurate detection and identification of seismic phases are of great significance to the detection and parameter estimation of seismic events. In seismic phase identification, discriminating between noise signals and real seismic signals is essential. Accurate identification of noise signals helps reduce false detections, improves the accuracy of automatic bulletins, and relieves the workload of analysts. At the same time, in seismic exploration, the prime objective in data processing is also to enhance the signal and suppress the noises. In this study, we combined a generative adversarial network (GAN) with a long short-term memory network (LSTM) to discriminate between noise and phases in seismic waveforms recorded by the International Monitoring System (IMS) array MKAR. First, using the beamforming data of the array as the input, we obtained the signal features of seismic phases through the learning of the GAN discriminator network. Then, we input these features and trained the joint network on mixed seismic phase and noise data, and successfully classified seismic phases and noise signals with a recall of 95.28% and 97.64%, respectively. Based on this model, we established a real-time data processing method, then validated the effectiveness of this method with real 2019 data of MKAR. We also verified whether improved noise signal identification improves the quality of phase association and event detection. [ABSTRACT FROM AUTHOR]

Seismic activity in volcanic settings could be the signature of processes that include magma dynamics, hydrothermal activity and geodynamics. The main goal of this study is to analyze the seismicity of Lipari Island (Southern Tyrrhenian Sea) to characterize the dynamic processes such as the interaction between pre-existing structures and hydrothermal processes affecting the Aeolian Islands. We deployed a dense seismic array of 48 autonomous 3-component nodes. For the first time, Lipari and its hydrothermal field are investigated by a seismic array recording continuously for about a month in late 2018 with a 0.1–1.5 km station spacing. We investigate the distribution and evolution of the seismicity over the full time of the experiment using self-organized maps and automatic algorithms. We show that the sea wave motion strongly influences the background seismic noise. Using an automatic template matching approach, we detect and locate a seismic swarm offshore the western coast of Lipari. This swarm, made of transient-like signals also recognized by array and polarization analyses in the time and frequency domains, is possibly associated with the activation of a NE-SW fault. We also found the occurrence of hybrid events close to the onshore Lipari hydrothermal system. These events suggest the involvement of hot hydrothermal fluids moving along pre-existing fractures. Seismological analyses of one month of data detect signals related to the regional tectonics, hydrothermal system and sea dynamics in Lipari Island.

In this work, an advanced machine learning technique named diffusion maps is applied for array-based earthquake-explosion discrimination. We rely on prior work that utilizes the diffusion map-based discrimination approach for data collected from a single seismometer. The discrimination task is an essential component of the Comprehensive Nuclear-Test-Ban Treaty verification regime and since many of the International Monitoring System (IMS) stations consist of arrays, the extension to array based processing is of interest. The proposed method includes a pre-processing step, which constructs time–frequency representations of the P-wave and S-wave seismograms followed by a non-linear dimensionality reduction step. Discrimination is performed in the low-dimensional space. The performance of the presented algorithm is demonstrated on a data set from Southern Israel, recorded at the IMS seismic array of Mt. Meron (MMAI). We show that the diffusion maps-based approach enables to enhance the discrimination capabilities of seismic arrays, even when processing low-magnitude events. [ABSTRACT FROM AUTHOR]

A ruptured front obtained from high-frequency energy radiation is the key to understand the complex source. It is commonly observed that rupture fronts derived from different arrays often show some variations due to the obvious difference of the positioning accuracy of the far-field array between the azimuth and the epicentral distance. We developed a new multi-array back-projection method based on the classical back-projection method and applied the method to the 2015 MW7.8 Nepal earthquake. The back azimuth information with small error is separated from the classical back-projection results, and the azimuth intersection of multiple arrays is used to obtain more accurate spatial and temporal distribution information of the source rupture fronts.

In a joint project called OMEGA, between GFZ-Potsdam and the Istituto Nazionale di Geofisica e Vulcanologia (INGV), an experimental seismic monitoring system was installed in 2015 near the power plants of the geothermal area of Mt. Amiata (central Italy). The main objectives of this three-year experiment are: i) to monitor the seismic activity connected to any type of seismicity inside the geothermal field, ii) to verify if the low local seismicity rate near Mt. Amiata reported by the INGV bulletin is natural, or due to the sparse distribution of the INGV network, and iii) to discriminate natural from possibly induced seismicity. The eight-station network was extended by a seven element seismic array for the first four weeks. The aim of this paper is to present the first automatic hypocentre locations of the joint network/array analysis. [ABSTRACT FROM AUTHOR]

In the literature, records and analyses have shown that in earthquake-prone areas local site conditions tend to alter the strong motion at the ground surface. More specifically, the surface topography, in combination to the soil stratigraphy and/or the geomorphology of the seismic bedrock, may have a substantial impact on the amplitude, the frequency content, and/or the duration of the seismic motion at the ground surface. The current study is involved with the Athenian Acropolis Hill, which is an unusual case of local site conditions affecting ground motion as a rock outcrop of limestone overlies the relatively soft Athenian schist. Since monuments of paramount importance are founded on the Hill (i.e. Parthenon, Propylaea, Erechtheion and Temple of Athena Nike) and Athens is characterised by moderate to high seismicity, a seismic array of accelerographs has been installed by the National Observatory of Athens and the Acropolis Restoration Service at specific locations on the Hill in order to monitor its seismic response in real time. Aiming to assess the impact of local site conditions on the seismic response of the Hill, an evaluation of the available recorded acceleration time histories has been conducted. Additionally, two-dimensional numerical simulations have been performed utilising the finite-element method. Various excitations, such as simple pulses and records obtained by the seismic array, have been used as input motion for the numerical analyses. Despite the discrepancies, the numerical results are in good agreement with the available records and demonstrate the importance of local site conditions on the seismic response of the Acropolis Hill. [ABSTRACT FROM AUTHOR]

The ambient vibration analysis is a non-invasive and low-cost technique used in site characterization studies to reconstruct the subsurface velocity structure. Depending on the goal of the research, the investigated depth ranges from tens to hundreds of meters. In this work, we aimed at investigating the deeper contrasts within the crust and in particular down to the sedimentary-rock basement transition located at thousands of meters of depth. To achieve this goal, three seismic arrays with minimum and maximum interstation distances of 7.9 m and 26.8 km were deployed around the village of Schafisheim. Schafisheim is located in the Swiss Molasse Basin, a sedimentary basin stretching from Lake Constance to Lake Geneva with a thickness ranging from 800 to 900 m in the north to 5 km in the south. To compute the multimodal dispersion curves for Rayleigh and Love waves and the Rayleigh wave ellipticity angles, the data were processed using two single-station and three array processing techniques. A preliminary analysis of the inversion results pointed out a good agreement with the fundamental modes of Rayleigh and Love waves used in the inversion and a quite strong disagreement with the higher modes. The impossibility to explain at the same time most of the dispersion curves was interpreted as the co-existence, within the investigated area, of portions of the subsurface with different geophysical properties. The hypothesis was confirmed by the Horizontal-to-Vertical spectral analysis (H/V) which indicated the presence of two distinguished areas. The observation allowed a new interpretation and the identification of the Rayleigh and Love wave fundamental modes and of the S-wave velocity profiles to be reconstructed for each investigated zone. It results in two S-wave velocity profiles with similar velocities down to 15 km deferring only in their shallow portions due to the occurrence of a low velocity zone at a depth of 50–150 m at the centre of the investigated area. [ABSTRACT FROM AUTHOR]

Subsea hydrocarbon exploration comprises detection and estimation of shape, depth, volume and other physical properties of hydrocarbon fields within the Earth's subsurface layers. Marine seismic survey is a process that generally includes sending seismic waves into seabed and recording the intensity and travel time of reflected seismic waves to determine the subsurface features of the Earth. Different methods, equipment and techniques are used to conduct a survey, from sea surface seismic arrays to seabed local seismic station networks. In this paper different widely used seismic methods are presented, together with their advantages and drawbacks. Furthermore, new methods that are being developed and tested for future approach to more advanced and efficient seismic exploration are presented. [ABSTRACT FROM AUTHOR]

The purpose of seismic data processing in nuclear explosion monitoring is to accurately and reliably detect seismic or explosion events from complex ambient noises. Accurate detection and identification of seismic phases are of great significance to the detection and parameter estimation of seismic events. In seismic phase identification, discriminating between noise signals and real seismic signals is essential. Accurate identification of noise signals helps reduce false detections, improves the accuracy of automatic bulletins, and relieves the workload of analysts. At the same time, in seismic exploration, the prime objective in data processing is also to enhance the signal and suppress the noises. In this study, we combined a generative adversarial network (GAN) with a long short-term memory network (LSTM) to discriminate between noise and phases in seismic waveforms recorded by the International Monitoring System (IMS) array MKAR. First, using the beamforming data of the array as the input, we obtained the signal features of seismic phases through the learning of the GAN discriminator network. Then, we input these features and trained the joint network on mixed seismic phase and noise data, and successfully classified seismic phases and noise signals with a recall of 95.28% and 97.64%, respectively. Based on this model, we established a real-time data processing method, then validated the effectiveness of this method with real 2019 data of MKAR. We also verified whether improved noise signal identification improves the quality of phase association and event detection.

In this paper, we consider the analysis, implementation, and application of wideband sources using both seismic and acoustic sensors. We use the approximate maximum likelihood (AML) algorithm to perform acoustic direction of arrival (DOA). For non-uniform noise spectra, whitening filtering was applied to the received acoustic signals before the AML operation. For short-range seismic DOA applications, one method was based on eigen-decomposition of the covariance matrix and a second method was based on surface wave analysis. Two well-known optimization schemes were used to estimate the source locations from the estimated DOAs at sensors of known locations. Experimental estimation of the DOAs and resulting localizations using the acoustic and seismic signals generated by striking a heavy metal plate by a hammer were reported.

The collision of the Indian and Eurasian plates, to the east of the eastern Himalayan syntaxes, forms the Sanjiang lateral collision zone in the southeast margin of the Tibetan Plateau, where there are intense crustal deformation, active faults, earthquakes, as well as a metallogenic belt. Given the lack of adequate seismic data, shear‐wave splitting in this area has not been studied. With seismic data from a temporary seismic linear array, as well as permanent seismic stations, this paper adopts the identification on microseismic event to pick more events and obtains shear‐wave splitting parameters from local earthquakes. From the west to the east, the study area can be divided into three subzones. The "fast" polarization (i.e. the polarization of the fast shear wave) varies gradually from NNW to NS to NNE in these three subzones. The time delay of the slow shear wave (i.e. the time difference between the two split shear waves) also increases in the same direction, indicating the presence of seismic anisotropy above 25 km in the crust. Both shear‐wave splitting parameters are closely related to stress, faults and tectonics. The scatter and the "dual" (i.e. two) dominant orientations of the fast polarizations at several stations indicate strong distortions caused by nearby faults or deep tectonics. The anisotropic parameters are found to be related to some degree to the metallogenic belt. It is worth to further analyse the link between the anisotropic pattern and the metallogenic area, which suggests that shear‐wave splitting could be applied to study metallogeny. This paper demonstrates that the identification on microseismic event is a useful tool in detecting shear‐wave splitting details and exploring its tectonic implications. [ABSTRACT FROM AUTHOR]

Wind gusts are a major cause of damage to property and the natural environment and a source of noise in seismic networks such as the USArray Transportable Array. Wind gusts cause ground motion through shear stresses, pressure fluctuations and vegetation flexing. Herein, we demonstrate the presence of a seismic response signature to wind gusts at sites across the contiguous USA and explore important geophysical factors that determine the precise nature of wind gust–seismic response relationships. There is a consistent seismic response to wind gusts that is typically manifest at relatively low frequency (0.05–0.1 Hz). However, there is also a marked seasonality in the seismic frequency of peak response, possibly due to seasonal differences in atmospheric conditions and/or vegetation and soil mediation of the atmosphere–ground interaction. The gust–seismic response functions also exhibit a clear dependence on (1) distance from the coast, (2) land cover, (3) topographic complexity and (4) lithology. We propose a generalized methodology to extract wind gust magnitude distributions from seismic networks. Although initial results from this model overestimate the spatial variability in wind gusts as measured by meteorological networks, the analyses described here highlight the potential for new methods to remove wind gust noise from seismic time series and potentially to derive quantitative wind gust estimates from seismic observations. [ABSTRACT FROM AUTHOR]

In the framework of a scientific collaboration with the National Society for Earthquake Technology, Nepal, after the M7.8 Gorkha earthquake on 25 April 2015, the National Institute of Oceanography and Experimental Geophysics, Italy, organised a geophysical survey at Kathmandu, in order to have a better understanding of the seismic response of the valley in which the city is located. The main goal was to improve the knowledge of the spectral amplification of the ground motion, due to the fluvio-lacustrine sediments that constitute the Kathmandu basin, by combining the noise ratio H/V technique and velocity dispersion curve analysis. Ambient noise recordings were performed mostly in the Lalitpur area as a single station, and also by an array using ReMi measurement. This study mainly investigates the southern part of the city that was not covered by previous studies. In order to assess the resonant conditions of the soil foundation, microtremor measurements were also performed at Swayambhunath (Monkey Temple) hill and a site close to Boudhanath Stupa, the two prominent Buddhist temples-cummonasteries that had suffered significant damage during the Gorkha earthquake. The results show that the frequencies at the bottom of the basin are apparently lower than previous surveys and consequently also its depth would be greater. [ABSTRACT FROM AUTHOR]

We image the San Jacinto fault zone at Blackburn Saddle using earthquake waveforms recorded by a ~ 2-km across-fault linear array with 108 three-component sensors separated by ~ 10-30 m. The length and spatiotemporal sampling of the array allow us to derive high-resolution information on the internal fault zone structure with spatial extent that can be merged with regional tomography models. Across-fault variations in polarization, amplitude, and arrival time of teleseismic P waves indicate abrupt changes in subsurface structure near the surface trace of the fault (sensor BS55) and ~ 270 m to the northeast (sensor BS34). Analysis of fault zone head waves from local events reveals the existence of a deep bimaterial interface that extends from the array to at least 50 km southeast and has a section with > 10% velocity contrast. This analysis also corroborates the teleseismic results and indicates a broad damage zone primarily northeast of the fault bounded by a shallow bimaterial interface near BS34 that merges with the deep interface. Detection and waveform inversions of Love-type fault zone trapped waves generated by local events indicate a trapping structure within the broader damage zone with width of ~ 150 m, velocity reduction of ~ 55% from the surrounding rock and depth extent of ~ 2 km. The performed analyses provide consistent results on the subsurface location of the main seismogenic fault and properties of a major bimaterial interface and damage structure. The imaged fault zone properties are consistent with preferred propagation direction of earthquake ruptures in the area to the northwest. [ABSTRACT FROM AUTHOR]

Rotaphone-CY is a six-component short-period seismograph that is capable of the co-located recording of three translational (ground velocity) components along three orthogonal axes and three rotational (rotation rate) components around the three axes in one device. It is a mechanical sensor system utilizing records from elemental sensors (geophones) arranged in parallel pairs to derive differential motions in the pairs. The pairs are attached to a rigid frame that is anchored to the ground. The model design, the latest one among various Rotaphone designs based on the same principle and presented elsewhere, is briefly introduced. The upgrades of the new model are a 32-bit A/D converter, a more precise placing of the geophones to parallel pairs and a better housing, which protects the instrument from external electromagnetic noise. The instrument is still in a developmental stage. It was tested in a field experiment that took place at the Geophysical Observatory in Fürstenfeldbruck (Germany) in November 2019. Four Rotaphones-CY underwent the huddle-testing phase of the experiment as well as the field-deployment phase, in which the instruments were installed in a small-aperture seismic array of a triangular shape. The preliminary results from this active-source experiment are shown. Rotaphone-CY data are verified, in part, by various approaches: mutual comparison of records from four independent Rotaphone-CY instruments, waveform matching according to rotation-to-translation relations, and comparison to array-derived rotations when applicable. The preliminary results are very promising and they suggest the good functionality of the Rotaphone-CY design. It has been proved that the present Rotaphone-CY model is a reliable instrument for measuring short-period seismic rotations of the amplitudes as small as 10−7 rad/s.

• Tomography with a dense seismic array reveals the upper-mantle structure in SE China. • A low-velocity zone with high Poisson's ratio exists under the western Cathaysia block. • The low-velocity zone reflects thermal flow causing the late Mesozoic mineralization. Our study region is located in the Cathaysia block (CB), Southeast China. The most significant feature of the CB is the widespread Mesozoic magmatism and poly-metallic mineralization. However, there is still no consensus on their genesis and related tectonic processes. In this study, we determine high-resolution (0.3° in the horizontal direction) tomographic images of Vp and Vs and Vp/Vs ratio in the crust and upper mantle using 6773 P-wave and 4526 S-wave travel-time data of teleseismic events recorded by a broadband linear seismic array. The array was deployed by our team in the middle part of the CB, consisting of 81 portable stations with an interval of 5–8 km. Our tomographic results reveal two obvious low-velocity (low-V) zones with high Vp/Vs ratio (high-σ) beneath the Nanling ore belt and the Wuyishan terrane, which may reflect magmatic channels formed by partial melting that may provide heat for metal mineralization. Two high-V anomalies with low-σ are located beneath the western Wuyishan terrane and the eastern CB, which may represent refractory lithosphere or remnants of delaminated lithospheric material caused by underplating of the magma due to the subduction of the paleo-Pacific plate and its following rollback. There exists an anomaly with low-Vp, high-Vs and low-σ at depths of 150–300 km beneath the western Wuyishan terrane, which may be related to the reserved trace of magmatic conduits. On the basis of the tomographic results, we propose a geodynamic model to explain the deep mechanism of mineralization beneath the CB. [ABSTRACT FROM AUTHOR]

A comparative active experiment that is aimed at collocated measurement of seismic rotation rates along three orthogonal axes by means of three different methods is described. The rotation rates in a short-period range of 6–20 Hz were obtained using three different methods: the 6C Rotaphone sensor system developed by the authors, the commercial R-1 rotational sensor by Eentec, and a small-aperture array of twelve standard velocigraphs in a rectangular arrangement. Those three methods are compared and discussed in detail. A medium-size quarry blast was used as a seismic source. At a distance of approximately 240 m, the rotation rates reached an amplitude of the order of magnitude of 10−4–10−5 rad/s. The array derived rotation rates displayed serious limitations, as clearly documented. The R-1 instruments have shown certain technical problems that partly limit their applicability. The measured rotation rates were compared to the relevant acceleration components according to rotation-to-translation relations. Out of all the three methods, the records best matching the acceleration components were made by Rotaphone. The experiment also revealed that rotation rates in the given short-period range noticeably changed over a distance as short as 2 m.

Abstract: Precisely locating sites of nuclear tests is important for the Comprehensive Nuclear‐Test‐Ban Treaty and structure studies. Here we apply a relative relocation method to a dense regional seismic array, Hi‐net, to determine the relative locations of the sites of the North Korean nuclear tests from 2006 to 2017. Our results show that the sites of the 2013 to 2017 events are closely located together and within 600 m of the site of the 2009 event. The site of the 2006 event is located ~2 km southeast to the site of the 2009 event. A bootstrap resampling of azimuthal subsets of the array adds confidence to the relative locations. Seismic data recorded at regional distance by a dense network with azimuthal coverage as limited as 80° can resolve the relative locations of the nuclear tests to within a few hundred meters for all but the 2006 event. This approach can be extended to locating natural earthquakes as well. [ABSTRACT FROM AUTHOR]

Ambient seismic noise or microtremor observations used in spatial auto-correlation (SPAC) array methods consist of a wide frequency range of surface waves from the frequency of about 0.1 Hz to several tens of Hz. The wavelengths (and hence depth sensitivity of such surface waves) allow determination of the site S-wave velocity model from a depth of 1 or 2 m down to a maximum of several kilometres; it is a passive seismic method using only ambient noise as the energy source. Application usually uses a 2D seismic array with a small number of seismometers (generally between 2 and 15) to estimate the phase velocity dispersion curve and hence the S-wave velocity depth profile for the site. A large number of methods have been proposed and used to estimate the dispersion curve; SPAC is the one of the oldest and the most commonly used methods due to its versatility and minimal instrumentation requirements. We show that direct fitting of observed and model SPAC spectra generally gives a superior bandwidth of useable data than does the more common approach of inversion after the intermediate step of constructing an observed dispersion curve. Current case histories demonstrate the method with a range of array types including two-station arrays, L-shaped multi-station arrays, triangular and circular arrays. Array sizes from a few metres to several-km in diameter have been successfully deployed in sites ranging from downtown urban settings to rural and remote desert sites. A fundamental requirement of the method is the ability to average wave propagation over a range of azimuths; this can be achieved with either or both of the wave sources being widely distributed in azimuth, and the use of a 2D array sampling the wave field over a range of azimuths. Several variants of the method extend its applicability to under-sampled data from sparse arrays, the complexity of multiple-mode propagation of energy, and the problem of precise estimation where array geometry departs from an ideal regular array. We find that sparse nested triangular arrays are generally sufficient, and the use of high-density circular arrays is unlikely to be cost-effective in routine applications. We recommend that passive seismic arrays should be the method of first choice when characterizing average S-wave velocity to a depth of 30 m (Vs30) and deeper, with active seismic methods such as multichannel analysis of surface waves (MASW) being a complementary method for use if and when conditions so require. The use of computer inversion methodology allows estimation of not only the S-wave velocity profile but also parameter uncertainties in terms of layer thickness and velocity. The coupling of SPAC methods with horizontal/vertical particle motion spectral ratio analysis generally allows use of lower frequency data, with consequent resolution of deeper layers than is possible with SPAC alone. Considering its non-invasive methodology, logistical flexibility, simplicity, applicability, and stability, the SPAC method and its various modified extensions will play an increasingly important role in site effect evaluation. The paper summarizes the fundamental theory of the SPAC method, reviews recent developments, and offers recommendations for future blind studies. [ABSTRACT FROM AUTHOR]

A large number of events with sources in the immediate vicinity of an array are usually detected during seismological observations with seismic arrays. These events should be detected and correctly interpreted during processing of seismic array records in order to avoid clogging up the event catalog. This problem can be solved by classifying records of local events by genetic features and creating a databank with the most representative samples. The present paper considers local events recorded using a unique scientific setup, the Mikhnevo small aperture seismic array. Epicenters of local seismic events are located less than 5 km from the center of the array. Seismic responses of acoustic shock waves are also examined. Seismic events caused by anthropogenic sources are identified and classified using cluster, cross-correlation, and wavelet analysis. Events accompanied only by the arrival of surface waves, as well as events represented by body, surface, and acoustic waves, are identified. Shock wave events are classified as a separate category. A small group of supposedly natural weak events is also found. As a result, a databank of waveforms of local seismic events for the Mikhnevo seismic array is established. In the future, this will make it possible to automate their identification when investigating the seismicity of the East European Platform. [ABSTRACT FROM AUTHOR]

The PoroTomo research team deployed two arrays of seismic sensors in a natural laboratory at Brady Hot Springs, Nevada in March 2016. The 1500 m (length) x 500 m (width) x 400 m (depth) volume of the laboratory overlies a geothermal reservoir. The distributed acoustic sensing (DAS) array consisted of about 8400 m of fiber-optic cable in a shallow trench and 360 m in a well. The conventional seismometer array consisted of 238 shallowly buried three-component geophones. The DAS cable was laid out in three parallel zig-zag lines with line segments approximately 100 m in length and geophones were spaced at approximately 60 m intervals. Both DAS and conventional geophones recorded continuously over 15 d during which a moderate-sized earthquake with a local magnitude of 4.3 was recorded on 2016 March 21. Its epicentre was approximately 150 km south-southeast of the laboratory. Several DAS line segments with co-located geophone stations were used to compare signal-to-noise ratios (SNRs) in both time and frequency domains and to test relationships between DAS and geophone data. The ratios were typically within a factor of five of each other with DAS SNR often greater for P-wave but smaller for S-wave relative to geophone SNR. The SNRs measured for an earthquake can be better than for active sources because the earthquake signal contains more low-frequency energy and the noise level is also lower at those lower frequencies. Amplitudes of the sum of several DAS strain-rate waveforms matched the finite difference of two geophone waveforms reasonably well, as did the amplitudes of DAS strain waveforms with particle-velocity waveforms recorded by geophones. Similar agreement was found between DAS and geophone observations and synthetic strain seismograms. The combination of good SNR in the seismic frequency band, high-spatial density, large N and highly accurate time control among individual sensors suggests that DAS arrays have potential to assume a role in earthquake seismology. [ABSTRACT FROM AUTHOR]

The fate of a subducted slab is a key ingredient in the context of plate tectonics, yet it remains enigmatic especially in terms of its crustal component. In this study, our efforts are devoted to resolve slab-related structures in the mid-mantle below eastern Indonesia, the Izu-Bonin region, and the Peru area by employing seismic array analysing techniques on high-frequency waveform data from F-net in Japan and the Alaska regional network and the USArray in North America. A pronounced arrival after the direct P wave is observed in the recordings of four deep earthquakes (depths greater than 400 km) from three subduction systems including the Philippines, the Izu-Bonin, and the Peru. This later arrival displays a slightly lower slowness compared to the direct P wave and its back-azimuth deviates somewhat from the great-circle direction. We explain it as an S-to-P conversion at a deep scatterer below the sources in the source region. In total, five scatterers are seen at depths ranging from ~930 to 1500 km. Those scatterers appear to be characterised by an ~7 km-thick low-velocity layer compared to the ambient mantle. Combined evidence from published mineral physical analysis suggests that past subducted oceanic crust, possibly fragmented, is most likely responsible for these thin-layer compositional heterogeneities trapped in the mid-mantle beneath the study regions. Our observations give a clue to the potential fate of subducted oceanic crust. [ABSTRACT FROM AUTHOR]