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SUMMARY: For seismographic stations with short acquisition duration, the signal-to-noise ratios (SNRs) of ambient noise cross-correlation functions (CCFs) are typically low, preventing us from accurately measuring surface wave dispersion curves or waveform characteristics. In addition, with noisy CCFs, it is difficult to extract relatively weak signals such as body waves. In this study, we propose to use local attributes to improve the SNRs of ambient noise CCFs, which allows us to enhance the quality of CCFs for stations with limited acquisition duration. Two local attributes: local cross-correlation and local similarity, are used in this study. The local cross-correlation allows us to extend the dimensionality of daily CCFs with computational costs similar to global cross-correlation. Taking advantage of this extended dimensionality, the local similarity is then used to measure non-stationary similarity between the extended daily CCFs with a reference trace, which enables us to design better stacking weights to enhance coherent features and attenuate incoherent background noises. Ambient noise recorded by several broad-band stations from the USArray in North Texas and Oklahoma, the Superior Province Rifting EarthScope Experiment in Minnesota and Wisconsin and a high-frequency nodal array deployed in the northern Los Angeles basin are used to demonstrate the performance of the proposed approach for improving the SNR of CCFs. [ABSTRACT FROM AUTHOR]

The use of the HVSR (Horizontal-to-Vertical Spectral Ratio) method on single-station microtremor measurements is well documented in small alluvial plains for bedrock mapping. In large sedimentary basins, like the Po Plain, its application is still debated. To shed some light on this issue, we investigated two seismogenic structures buried below the Po Plain Quaternary deposits: the Mirandola and Casaglia anticlines. We acquired and analysed a dense distribution of HVSR data covering the two areas and mapped the frequency and amplitude values of the observed resonance peaks. The top of both anticlines is highlighted by high amplitude peaks picturing E-W elongated sectors with high-impedance contrast, where Quaternary deposits are reduced in thickness to about 60–130 m and directly overlay the Pliocene (Mirandola) and Miocene (Casaglia) marine units. In Mirandola, the high-amplitude peaks also correspond to higher resonance frequencies, while in Casaglia, the distribution of resonance frequencies is relatively uniform suggesting a flatter crestal region and the lateral continuity of the resonance surface. The combination of peak frequency and amplitude information on a dense grid of measurement points is thus confirmed to be useful for identifying and mapping buried geological structures such as structural highs. Further modelling is being carried out to estimate the depth of the surface responsible for the observed resonances, through calibration with borehole information. [ABSTRACT FROM AUTHOR]

SUMMARY: The Pohang Basin sustained the most extensive seismic damage in the history of instrumental recording in Korea due to the 2017 Mw 5.5 earthquake. The pattern of damage shows marked differences from a radial distribution, suggesting important contributions by local site effects. Our understanding of these site effects and their role in generating seismic damage within the study area remains incomplete, which indicates the need for a thorough exploration of subsurface information, including the thickness of soil to bedrock and basin geometry, in the Pohang Basin. We measured the depth to bedrock in the Pohang Basin using dense ambient noise measurements conducted at 698 sites. We propose a model of basin geometry based on depths and dominant frequencies derived from the horizontal-to-vertical spectral ratio (HVSR) of microtremor at 698 sites. Most microseismic measurements exhibit one or more clear HVSR peak(s), implying one or more strong impedance contrast(s), which are presumed to represent the interface between the basement and overlying basin-fill sediments at each measurement site. The ambient seismic noise induces resonance at frequencies as low as 0.32 Hz. The relationship between resonance frequency and bedrock depth was derived using data from 27 boreholes to convert the dominant frequencies measured at stations adjacent to the boreholes into corresponding depths to the strong impedance contrast. The relationship was then applied to the dominant frequencies to estimate the depth to bedrock over the whole study area. Maps of resonance frequency and the corresponding depth to bedrock for the study area show that the greatest depths to bedrock are in the coastal area. The maps also reveal lower fundamental frequencies in the area west of the Gokgang Fault. The results indicate a more complex basin structure than previously proposed based on a limited number of direct borehole observations and surface geology. The maps and associated profiles across different parts of the study area show pronounced changes in bedrock depth near inferred blind faults proposed in previous studies, suggesting that maps of bedrock depth based on the HVSR method can be used to infer previously unknown features, including concealed or blind faults that are not observed at the surface. [ABSTRACT FROM AUTHOR]

SUMMARY: Atmospheric pressure changes on Earth's surface can deform the solid Earth. Sorrells derived analytical formulae for displacement in a homogeneous, elastic half-space, generated by a moving surface pressure source with speed $c$. Ben-Menahem and Singh derived formulae when an atmospheric P wave impinges on Earth's surface. For a P wave with an incident angle close to the grazing angle, which essentially meant a slow apparent velocity $c_a$ in comparison to P- ($\alpha ^{\prime }$) and S-wave velocities ($\beta ^{\prime }$) in the Earth ($c_a \ll \beta ^{\prime } \lt \alpha ^{\prime }$), they showed that their formulae for solid-Earth deformations become identical with Sorrells' formulae if $c_a$ is replaced by $c$. But this agreement was only for the asymptotic cases ($c_a \ll \beta ^{\prime }$). The first point of this paper is that the agreement of the two solutions extends to non-asymptotic cases, or when $c_a /\beta ^{\prime }$ is not small. The second point is that the angle of incidence in Ben-Menahem and Singh's problem does not have to be the grazing angle. As long as the incident angle exceeds the critical angle of refraction from the P wave in the atmosphere to the S wave in the solid Earth, the formulae for Ben-Menahem and Singh's solution become identical to Sorrell's formulae. The third point is that this solution has two different domains depending on the speed $c$ (or $c_a$) on the surface. When $c/\beta ^{\prime }$ is small, deformations consist of the evanescent waves. When $c$ approaches Rayleigh-wave phase velocity, the driven oscillation in the solid Earth turns into a free oscillation due to resonance and dominates the wavefield. The non-asymptotic analytical solutions may be useful for the initial modelling of seismic deformations by fast-moving sources, such as those generated by shock waves from meteoroids and volcanic eruptions because the condition $c / \beta ^{\prime } \ll 1$ may be violated for such fast-moving sources. [ABSTRACT FROM AUTHOR]

This work presents a thorough reevaluation of soil amplification in the La Chana neighborhood of Granada through a pioneering application of the horizontal-to-vertical spectral ratio technique on seismic noise data using various spectral approaches. The research recycles old seismic noise data recorded at 34 stations with 2 Hz instruments in the year 2010, supplemented with additional measurements recorded with broadband seismometers at nearby locations in the years 2013 and 2017. Initial traditional processing identifies a narrowband dominant frequency around 1.5 Hz, attributed to artificial or anthropogenic sources. To address this, the Maximum Entropy Algorithm was implemented to smooth the spectral response below 1 Hz, and filter out frequency peaks with very narrow spectral bands, while preserving the narrowband frequency around 1.5 Hz in some records. The Thomson Multitaper method further refined the spectral ratio, emphasizing the detection and suppression of narrow frequency bands that may be related to industrial activity. The results demonstrated the reappearance of the 1.5 Hz frequency, but this time without narrow bandwidths, indicating its possible correlation with the natural ground movement. Fundamental periods, ranging from 0.45 s to 0.88 s, suggest a diverse lithological composition, indicating the presence of layers of sands, clays, conglomerates, and carbonates over a basement that represents the main impedance contrast in the area. The multispectral approach surpasses conventional methods in precision and reliability, providing valuable insights for earthquake risk assessment, urban planning, and engineering decisions in seismically active regions. [ABSTRACT FROM AUTHOR]

Ambient noise source localization is of great significance for estimating seismic noise source distribution, understanding source mechanisms and imaging subsurface structures. The commonly used methods for source localization, such as the matched field processing and the full-waveform inversion, are time-consuming and not applicable for time-lapse monitoring of the noise source distribution. We propose an efficient alternative of using deep learning for noise source localization. In the neural network, the input data are noise cross-correlation functions and the output are matrices containing the information of noise source distribution. It is assumed that the subsurface structure is a horizontally layered earth model and the model parameters are known. A wavefield superposition method is used to efficiently simulate ambient noise data with quantities of local noise sources labelled as training data sets. We use a weighted binary cross-entropy loss function to address the prediction inaccuracy caused by a sparse label matrix during training. The proposed deep learning framework is validated by synthetic tests and two field data examples. The successful applications to locate an anthropogenic noise source and a carbon dioxide degassing area demonstrate the accuracy and efficiency of the proposed deep learning method for noise source localization, which has great potential for monitoring the changes of the noise source distribution in a survey area. [ABSTRACT FROM AUTHOR]

Investigating subsurface shear wave velocity (v s) structures using surface wave dispersion data involves minimizing a misfit function that is commonly solved through gradient-based optimization. Sensitivity kernels for model updates are commonly estimated using numerical differentiation, variational methods or implicit functions which however, may involve numerical instability and computational challenges when dealing with complex velocity models and large data sets. In this study, we propose a novel surface wave inversion framework in which error-free gradients are calculated by automatic differentiation (AD) and forward modelling is implemented by convenient computational graphs in the state-of-the-art deep learning framework. The AD-based inversion approach is first validated using two synthetic data sets. Then, the subsurface structures at three distinct locations, namely the Great Plains and the Long Beach in the US and Tong Zhou in China, are also derived using this method with seismic ambient noise data, which show nice consistency with those obtained using traditional methods. With the significantly improved computational efficiency, a great number of initial models can be inverted simultaneously to mitigate the impact of local minima and to estimate the uncertainty in the invert models. We have developed a new surface wave inversion package named ADsurf based on automatic differentiation and computational graphs in the deep learning framework, and its computational efficiency is also compared with the traditional finite-difference-based gradient estimation approach. While a great number of intriguing studies on the geophysical inverse problems have been conducted recently using deep learning for end-to-end mapping, the use of AD provided in the in the deep learning frameworks to assist and expedite the gradient computations are still underexploited in geophysics. Thus, it is expected that various geophysical inverse problems in many different areas beyond the surface wave inversion can also be tackled with this new paradigm in the future. [ABSTRACT FROM AUTHOR]

Understanding glaciers structural heterogeneity is crucial for assessing their fate. Yet, places where structure changes are strong, such as crevasses fields, are often inaccessible for direct instrumentation. To overcome this limitation, we introduce an innovative technique that transforms seismic sources, here generated by crevasses, into virtual receivers using source‐to‐receiver spatial reciprocity. We demonstrate that phase interference patterns between well‐localized seismic sources can be leveraged to retrieve phase velocity maps using Seismic Michelson Interferometry. The obtained phase velocity exhibits sensitivity to changes in glacier structure, offering insights into the origins of mechanical property changes, with spatial resolution surpassing traditional methods by a factor of five. In particular, we observe sharp variations in phase velocity related to strongly damaged subsurface areas indicating a complex 3‐D medium. Applying this method more systematically and in other contexts will enhance our understanding of the structure of glaciers and other seismogenic environments. Key Points: We transform seismic sources from crevasses into virtual receivers using source‐to‐receiver spatial reciprocityWe derive phase velocity maps in previously inaccessible areas with a resolution five times larger than traditional approachesWe retrieve the influence of glacier geometry and structural heterogeneity on the glacier mechanical properties [ABSTRACT FROM AUTHOR]

This paper introduces SEISMONOISY, an application designed for monitoring the spatiotemporal characteristic and variability of the seismic noise of an entire seismic network with a quasi-real-time monitoring approach. Actually, we have applied the developed system to monitor 12 seismic networks distributed throughout the Italian territory. These networks include the Rete Sismica Nazionale (RSN) as well as other regional networks with smaller coverage areas. Our noise monitoring system uses the methods of Spectral Power Density (PSD) and Probability Density Function (PDF) applied to 12 h long seismic traces in a 24 h cycle for each station, enabling the extrapolation of noise characteristics at seismic stations after a Seismic Noise Level Index (SNLI), which takes into account the global seismic noise model, is derived. The SNLI value can be used for different applications, including network performance evaluation, the identification of operational problems, site selection for new installations, and for scientific research applications (e.g., volcano monitoring, identification of active seismic sequences, etc.). Additionally, it aids in studying the main noise sources across different frequency bands and changes in the characteristics of background seismic noise over time. [ABSTRACT FROM AUTHOR]

Ambient noise tomography on the basis of distributed acoustic sensing (DAS) deployed on existing telecommunication networks provides an opportunity to image the urban subsurface at regional scales and high-resolution. This capability has important implications in the assessment of the urban subsurface's potential for sustainable and safe utilization, such as geothermal development. However, extracting coherent seismic signals from the DAS ambient wavefield in urban environments at low cost remains a challenge. One obstacle is the presence of complex sources of noise in urban environments, which may not be homogeneously distributed. Consequently, long recordings are required for the calculation of high-quality virtual shot gathers, which necessitates significant time and computational cost. In this paper, we present the analysis of 15 d of DAS data recorded on a pre-existing fibre optic cable (dark fibres), running along an 11-km-long major road in urban Berlin (Germany), hosting heavy traffic including vehicles and trains. To retrieve virtual shot gathers, we apply interferometric analysis based on the cross-correlation approach where we exclude low-quality virtual shot gathers to increase the signal-to-noise ratio of the stacked gathers. Moreover, we modify the conventional ambient noise interferometry workflow by incorporating a coherence-based enhancement approach designed for wavefield data recorded with large-N arrays. We then conduct multichannel analysis of surface waves to retrieve 1-D velocity models for two exemplary fibre subsegments, and compare the results of the conventional and modified workflows. The resulting 1-D velocity models correspond well with available lithology information. The modified workflow yields improved dispersion spectra, particularly in the low-frequency band (<1 Hz) of the signal. This leads to an increased investigation depth along with lower uncertainties in the inversion result. Additionally, these improved results were achieved using significantly less data than required using conventional approaches, thus opening the opportunity for shortening required acquisition times and accordingly lowering costs. [ABSTRACT FROM AUTHOR]

Material density remains poorly constrained in seismic imaging problems, yet knowledge of density would provide important insight into physical material properties for the interpretation of subsurface structures. We test the sensitivity to subsurface density contrasts of spatial and temporal gradients of seismic ambient noise wavefields, using wave equation inversion (WEI), a form of seismic gradiometry. Synthetic results for 3-D acoustic media suggest that it is possible to estimate relative density structure with WEI by using a full acoustic formulation for wave propagation and gradiometry. We show that imposing a constant density assumption on the medium can be detrimental to subsurface seismic velocity images. By contrast, the full acoustic formulation allows us to estimate density as an additional material parameter, as well as to improve phase velocity estimates. In 3-D elastic media, severe approximations in the governing wave physics are necessary in order to invert for density using only an array of receivers on the Earth's free surface. It is then not straightforward to isolate the comparatively weak density signal from the influence of phase velocity using gradiometric WEI. However, by using receivers both at the surface and in the shallow subsurface we show that it is possible to estimate density using fully elastic volumetric WEI. [ABSTRACT FROM AUTHOR]

In this study, an analysis was conducted on the seismic response of three archaeological structures located in the Chichén Itzá area. The objective of this analysis was to gather relevant information that may be utilized to monitor and ensure the preservation of these monuments. Ambient seismic noise measurements were conducted over three days using broad-band seismographs. The objective was to assess the vibration frequencies of three buildings, namely Las Monjas, El Caracol and El Castillo or Kukulkan Pyramid, using HVSR method. The findings indicate that the dominant frequency of the El Caracol building is 1.3 Hz. Nevertheless, it is noteworthy that within the Las Monjas and El Castillo structures, an observable fundamental frequency of 5.1 Hz is present, accompanied by a relative amplification of around 6. The findings of this study indicate the behavior of the two pyramids can be likened to that of a soil layer overlaying a stiff stratum. The noise recorded by a seismograph at the base of El Castillo enables the observation of a kinematic interaction phenomenon resulting from the disparate stiffness properties of the soil and the structure. No directional effect was observed on the HVSR ratios due to internal irregularities in the pyramids. Considering the half-width of the base of each pyramid and that the site response is of topographic origin, the calculus of shear velocity is 255 m/s. This velocity relates to non-compact materials resting on competent rocks with velocities more than 1000 m/s, materials subject to stress changes that may eventually lead to structural degradation. The findings of this study indicate the need for continuous monitoring and instrumentation of lower levels to assess the influence of substructures during preconstruction stages and determine whether there are any other effects due to the karstic nature of the subsurface. [ABSTRACT FROM AUTHOR]

Ambient noise tomography is a well-established tomographic imaging technique but the effect that spatially variable noise sources have on the measurements remains challenging to account for. Full waveform ambient noise inversion has emerged recently as a promising solution but is computationally challenging since even distant noise sources can have an influence on the interstation correlation functions and therefore requires a prohibitively large numerical domain, beyond that of the tomographic region of interest. We investigate a new strategy that allows us to reduce the simulation domain while still being able to account for distant contributions. To allow nearby numerical sources to account for distant true sources, we introduce correlated sources and generate a time-dependent effective source distribution at the boundary of a small region of interest that excites the correlation wavefield of a larger domain. In a series of 2-D numerical simulations, we demonstrate that the proposed methodology with correlated sources is able to successfully represent a far-field source that is simultaneously present with nearby sources and the methodology also successfully results in a robustly estimated noise source distribution. Furthermore, we show how beamforming results can be used as prior information regarding the azimuthal variation of the ambient noise sources in helping determine the far-field noise distribution. These experiments provide insight into how to reduce the computational cost needed to perform full waveform ambient noise inversion, which is key to turning it into a viable tomographic technique. In addition, the presented experiments may help reduce source-induced bias in time-dependent monitoring applications. [ABSTRACT FROM AUTHOR]

The Gulf of Guinea exhibits a continuous emission of narrow-band and long-period signals (16, 26 and 27 s) on teleseismic records, yet the underlying excitation mechanism remains unclear. This study establishes a connection between these tremors and the vibration of thin, decoupled crustal plates at unexplored volcanoes in the gulf. We first formulate the damped plate oscillation equation, by incorporating the vibration of the thin surface crustal plate and magma flow in the subsurface sill. The findings reveal that a fundamental-mode vibration with a period of several dozen seconds can be induced by a crustal plate that is less than 1.0 km thick but extends over tens of kilometres in both length and width, given a subsurface sill depth exceeding 10.0 cm. The thin plate hypothesis also allows for excitation of a few overtone modes, but such waves in higher frequencies diminish over long distances, leaving only the monotonous fundamental-mode vibration at teleseismic stations. The long duration of Guinea tremors at each recurrence is attributed to the presence of low viscosity basaltic magma, which influences the damping factor. Direct wave loads at the shallow gulf serve as the primary vibration source, accounting for seasonal variations and recurring patterns. Sporadic energy bursts may also occur due to large storms. Radiation patterns of Guinea tremors are linked to the geometric structure of the thin plate. Our theoretical estimates of tremor spectra closely align with observed data, confirming the model's accuracy in capturing reported Guinea tremor characteristics. This study provides valuable insights into the origins of very long-period tremors at continental volcanoes. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the seismic ambient noise spectral anomalies that occur near gas reservoirs. These anomalies involve a significant spectral amplification of the vertical component for frequencies generally between 1.5 and 4 Hz and have been reported at various hydrocarbon sites worldwide. There are differing views on the mechanisms responsible for these anomalies. The guideline for this study is that many hydrocarbon reservoirs share a common geological feature: an anticline structure. It appears to cause site effects that influence the amplitude of the ambient noise wavefield. This research examines a dense real data set of ambient noise recorded at the Chémery underground gas storage site in France. The analysis identifies stable spectral anomalies between 1.2 and 2.4 Hz that are correlated to the position of the anticline structure, which also corresponds to the position of the gas bubble. We use a beamforming technique to study the composition and the origin of the ambient noise, and show that the variations of the spectral anomalies over time are correlated to changes in the source wavefield. Finally, we perform numerical simulations of Rayleigh wave propagation within a realistic 3-D velocity model of the Chémery site, while using source distributions directly extracted from real data analysis. The comparison of the simulated anomalies with real data yields a satisfactory qualitative fit. We conclude that the fundamental-mode Rayleigh wave site effect on the anticline is the main mechanism of the spectral anomaly. [ABSTRACT FROM AUTHOR]

Borneo and Sulawesi are two large islands separated by the Makassar Strait that lie within the complex tectonic setting of central Indonesia. The seismic structure beneath this region is poorly understood due to the limited data availability. In this study, we present Rayleigh wave tomography results that illuminate the underlying crustal structure. Group velocity is retrieved from dispersion analysis of Rayleigh waves extracted from the ambient noise field by cross-correlating long-term recordings from 108 seismic stations over a period of 8 months. We then produce a 3-D shear wave velocity model via a two-stage process in which group velocity maps are computed across a range of periods and then sampled over a dense grid of points to produce pseudo-dispersion curves; these dispersion curves are then separately inverted for 1-D shear wave velocity (Vs), with the resultant models combined and interpolated to form a 3-D model. In this model, we observed up to ± 1.2 km s−1 lateral Vs heterogeneities as a function of depth. Our models illuminate a strong low shear wave velocity (Vs) anomaly at shallow depth (≤ 14 km) and a strong high Vs anomaly at depths of 20–30 km beneath the North Makassar Strait. We inferred the sediment basement and Moho depth from our 3-D Vs model based on iso-velocity constrained by the positive vertical gradient of the Vs models. The broad and deep sedimentary basement at ∼14 ± 2 km depth beneath the North Makassar Strait is floored by a shallow Moho at ∼22 ± 2 km depth, which is the thinnest crust in the study area. To the east of this region, our model reveals a Moho depth of ∼45 ± 2 km beneath Central Sulawesi, the thickest crust in our study area, which suggests crustal thickening since the late Oligocene. Moreover, the presence of high near-surface Vs anomalies with only slight changes of velocity with increasing depth in southwest Borneo close to Schwaner Mountain confirm the existence of a crustal root beneath this region. [ABSTRACT FROM AUTHOR]

Train traffic is a powerful source of seismic waves, with many applications for passive seismic imaging. Seismic signals were recorded a few metres away from the railway track. These records display harmonious waveforms below 15 Hz for trains driving at speeds of around 100 km hr−1. The sensors record an apparent wavelet emitted by the interaction of the axle on a few of the closest sleepers. From this, we build a simple modelling tool using shifted wavelets to simulate a train signal. The relationship involves the varying train speed, the distances between each axle, and the wavelet emitted by each axle. We propose a nonlinear deconvolution method to invert this relationship. We use a local minimization algorithm with gradients derived by the adjoint state method, and use a frequency continuation technique. A linearized picking-based inversion initializes the nonlinear inversion. On real data, we apply this automatic workflow to 300 train passages, with an excellent match between the best simulation and the data. We identify the trains decelerating as they enter a train station. We also identify the train type based on inverted wheel spacing with centimetric accuracy. The inverted wavelets are consistent with the assumption that trains emit seismic waves by bending the rail above sleepers, although the theory does not explain why the inverted wavelet is not zero phase. This automated kinematic inversion algorithm may allow for contactless railway monitoring, and be used for source characterization for subsurface monitoring below railway tracks. [ABSTRACT FROM AUTHOR]

The diffusion field theory has been widely used to interpret ambient noise wave fields. Based on this theory, 1-D subsurface velocity structure inversion method is developed. However, few studies have referred to the noise horizontal to vertical (NHV) spectral ratio inversion of 3-D subsurface velocity structures, and almost no effective 3-D NHV inversion tools have been developed. To develop a useful tool for obtaining 3-D soil layer velocity structures, we combined the NHV forward calculation formula derived from diffusion field theory with the guided Monte Carlo algorithm and then extended the single-point NHV inversion to multipoint joint inversion through a joint objective function. Subsequently, a new 3-D soil layer velocity structure inversion method was proposed. Subsequently, a synthetic 2-D case was used to verify the proposed method. Finally, the proposed method was applied to the Xiangtang Array in Tangshan, China, to identify the 3-D velocity structures of the site based on noise observations. The results show that the proposed multipoint joint 3-D inversion method is effective for identifying 3-D underground velocity structures. [ABSTRACT FROM AUTHOR]

In the territory of Dushanbe city, the capital of Tajikistan, detailed geological and geophysical data were collected during geophysical surveys in 2019–2020. The data comprise 5 microtremor array measurements, 9 seismic refraction tomography profiles, seismological data from 5 temporary seismic stations for standard spectral ratio calculations, 60 borehole datasets, and 175 ambient noise measurements. The complete dataset for Dushanbe was used to build a consistent 3D geologic model of the city with a size of 12 × 12 km2. The results of the seismological and geophysical surveys were compared and calibrated with borehole data to define the boundaries of each layer in the study area. The Leapfrog Works software was utilized to create a 3D geomodel. From the 3D geomodel, we extracted six 12 km long 2D geological cross-sections. These 2D geological cross-sections were used for 2D dynamic numerical modeling with the Universal Distinct Element Code software to calculate the local seismic response. Finally, the dynamic numerical modeling results were compared with the amplification functions obtained from the seismological and ambient noise data analysis. The 2D dynamic numerical modeling results allowed a better assessment of the site effects in the study area to support seismic microzonation and the determination of local peak ground acceleration changes in combination with regional seismic hazard maps. In addition, our results confirm the strong seismic amplification effects noted in some previous studies, which are attributed to the influence of local topographic and subsurface characteristics on seismic ground motions. [ABSTRACT FROM AUTHOR]

Site amplification factors (SAFs) of seismic ground motions are essential in evaluating and estimating seismic hazards. In our previous study, the authors proposed a simple and cost-effective method to estimate a SAF based on a deep neural network (DNN) model and microtremor horizontal-to-vertical spectral ratio (MHVR). Since the previous DNN model was based on the observed SAFs and MHVRs within a limited district in Japan, the applicability of the previous model to non-source regions with different site conditions was limited. This study explored the application of a transfer learning (TL) technique to adapt an existing (pre-trained) DNN model to new regions and a different database. The SAFs obtained through generalized spectral inversion technique (GIT) at the seismic observation stations (K-NET and KiK-net) in Japan were collated as the ground truth for site effects. MHVRs recorded at the stations in several districts of Japan were collected to construct a data set for the development of the TL model. Subsequently, a TL model was constructed, leveraging the neural network layers and their weights from the pre-trained model while incorporating additional neural network layers to enhance the performance. During the training process, a total data set of 112 sites was divided into training set, validation set, and external test set by 1:1:5. Utilizing a cross-validation strategy, the residuals between pSAFs (pseudo-SAFs) estimated by the TL model and the observed SAFs were analysed for the external test set containing 80 sites. The results showed that the TL model outperformed the pre-trained DNN model. The cross-validation results demonstrated that almost consistent prediction results were obtained regardless of any combination of 16 sites selected as the training set. Furthermore, by contrasting the influence of varying training set sizes on the performance of the TL model and comparing the TL model to a DNN model with an extended training set, the effectiveness of constructing the model with the limited number of data (16 sites) was ascertained. Finally, the effectiveness and limitations of the TL model were evaluated using MHVRs with peak frequencies falling outside the training set's range. [ABSTRACT FROM AUTHOR]

Dense array observation and seismic interferometry have revolutionized the imaging schemes of the earth structure. It is becoming possible to directly obtain the lateral variation of the earth's structure by applying array-based methods such as the cross-correlation beamforming (CBF) of the ambient noise to the subsets of the dense array, without tomography. CBF has been proven to extract the azimuth-averaged multimode surface wave dispersion curves. However, the resolution of the dispersion image generated by conventional CBF is low at high frequencies in the frequency–velocity (f - v) domain. Moreover, the irregular array geometry and uneven source distribution would bias the result of CBF, especially for the estimation of azimuth-dependent velocity. In this paper, two beamforming (BF) es are suggested to improve the resolution of multimode dispersion images in the f - v domain. First, the geometrical spreading of the wavefield is corrected to enhance the amplitude at high frequency (or large distance) and thereby improve the resolution of the dispersion image at high frequency. We call this scheme weighted correlation beamforming (WCBF). The azimuth-averaged velocity can be estimated with sufficient resolution using WCBF by stacking the BF output at each azimuth. We show that WCBF is the 2-D Fourier transform of the spatial wavefield from the viewpoint of the wavefield transform. Secondly, a modified beamforming scheme (MCBF) is suggested to reduce the effect of uneven source and/or irregular array geometry. The delay and summation in MCBF are performed only for plane waves incident from the stationary phase region. The azimuth-dependent velocity can therefore be estimated by MCBF with less dependence on the array geometry, as well as on the uneven source distribution. In terms of the estimation of azimuth-averaged phase velocity, we show the F-J method, another array-based method for extracting multimode surface waves from ambient noise using the Fourier–Bessel transform, is the azimuth-averaged version of WCBF. The reliability of WCBF and MCBF is verified based on the synthetic and field data using the array with different geometry. The dispersion image of multimode Rayleigh wave phase velocity at local and regional scales can be generated by WCBF or MCBF with high resolution. In particular, multimode dispersion curves at the local scale can be measured by MCBF with sufficient accuracy using quite short recordings from hours to days. This offers the possibility of a rapid assessment of the media properties. [ABSTRACT FROM AUTHOR]

We examined the seismic noise data collected from coastal and inland observatories in India, affected by the super cyclonic storm Amphan in the Indian Ocean, to understand the storm dynamics. Prominent disturbances in the 0.05–0.50 Hz frequency range were observed at the seismic stations, arising due to ocean‐continent interactions. The coastal stations displayed more pronounced ground motions contrary to the inland stations, with spindle‐shaped seismic wave envelopes intensifying as Amphan approached. The maximum ground displacements and energy occurred hours after the cyclone's eye, with maximum wind speed, moved away from the stations and not when it was close to the station. We observed significant variations in primary (0.05–0.10 Hz) and secondary microseism (0.10–0.50 Hz) energy during Amphan's directional changes. Secondary microseisms in short and long periods were found at 0.20–0.50 Hz and 0.10–0.20 Hz, respectively. Primary microseisms exhibited a simple pattern and were the weakest among the three energy bands. The CAL seismic station's seismic wave envelope showed an en‐echelon feature with increasing amplitude as Amphan approached, indicating the influence of ocean resonance and coastal wave reflection. This study demonstrates monitoring of the tropical cyclone paths based on seismic signatures obtained using microseisms recorded at seismic stations, a cost‐effective tool. Integrating these seismic signals with atmospheric observations in near real‐time would probably enable an effective monitoring of cyclones and timely issuance of their alerts. Key Points: Monitor the Super Cyclone Amphan in the Bay of Bengal using Coastal seismological ObservatoriesSecondary microseisms in the short and long periods were found at 0.20–0.50 Hz and 0.10–0.20 HzMicroseisms recorded at seismic stations can be potential source of information for cyclone tracking [ABSTRACT FROM AUTHOR]

We performed seismic ambient noise tomography to investigate the shallow crustal structure around the Ivrea geophysical body (IGB) in the Ivrea-Verbano Zone (IVZ). We achieved higher resolution with respect to previous tomographic works covering the Western Alps, by processing seismic data collected by both permanent and temporary seismic networks (61 broad-band seismic stations in total). This included IvreaArray, a temporary, passive seismic experiment designed to investigate the IVZ crustal structure. Starting from continuous seismic ambient noise recordings, we measured and inverted the dispersion of the group velocity of surface Rayleigh waves (fundamental mode) in the period range 4–25 s. We obtained a new, 3-D vS model of the IVZ crust via the stochastic neighbourhood algorithm (NA), with the highest resolution between 3 to 40 km depth. The fast and shallow shear wave velocity anomaly associated with the IGB presents velocities of 3.6 km s−1 directly at the surface, in remarkable agreement with the location of the exposed lower-to-middle crustal and mantle outcrops. This suggests a continuity between the surface geological observations and the subsurface geophysical anomalies. The fast IGB structure reaches vS of 4 km s−1 at 20–25 km depth, at the boundary between the European and Adriatic tectonic plates, and in correspondence with the earlier identified Moho jump in the same area. The interpretation of a very shallow reaching IGB is further supported by the comparison of our new results with recent geophysical investigations, based on receiver functions and gravity anomaly data. By combining the new geophysical constraints and the geological observations at the surface, we provide a new structural interpretation of the IGB, which features lower crustal and mantle rocks at upper crustal depths. The comparison of the obtained vS values with the physical properties from laboratory analysis of local rock samples suggests that the bulk of the IGB consists of a combination of mantle peridotite, ultramafic and lower crustal rocks, bound in a heterogeneous structure. These new findings, based on vS tomography, corroborate the recent interpretation for which the Balmuccia peridotite outcrops are continuously linked to the IGB structure beneath. The new outcomes contribute to a multidisciplinary framework for the interpretation of the forthcoming results of the scientific drilling project DIVE. DIVE aims at probing the lower continental crust and its transition to the mantle, with two ongoing and one future boreholes (down to 4 km depth) in the IVZ area, providing new, complementary information on rock structure and composition across scales. In this framework, we constrain the upper crustal IGB geometries and lithology based on new evidence for vS , connecting prior crustal knowledge to recent active seismic investigations. [ABSTRACT FROM AUTHOR]

We use continuous data from more than 200 vertical-component broad-band seismic stations for the years 2012 and 2013 to model the crustal and lithospheric structure of the southeastern United States (SEUS). Seismic interferometry via cross-coherence is used to retrieve the surface wave Empirical Green's function (EGF) between station pairs. We mitigate the problem of non-stationary sources contributing to the extracted EGF by applying double beamforming to pairs of subarrays of stations. The recovered Rayleigh waves are used to compute group velocity dispersion maps which are then inverted to find shear wave velocity profiles using a Markov Chain Monte Carlo technique. EGFs are computed for more than 80 000 station pairs after filtering to the period band 7–60 s. Results reveal tectonic features in the SEUS that support recent claims that the northernmost extent of the Suwannee suture is located near the boundary of the Carolinia and Charleston terranes and that the Charleston and Suwannee terranes are not seismologically distinct within the resolution limits of the data set. [ABSTRACT FROM AUTHOR]

Ambient noise seismic tomography has proven to be an effective tool for subsurface imaging, particularly in volcanic regions such as the Reykjanes Peninsula (RP), SW Iceland, where ambient seismic noise is ideal with isotropic illumination. The primary purpose of this study is to obtain a reliable shear wave velocity model of the RP, to get a better understanding of the subsurface structure of the RP and how it relates to other geoscientific results. This is the first tomographic model of the RP which is based on both on- and off-shore seismic stations. We use the ambient seismic noise data and apply a novel algorithm called one-step 3-D transdimensional tomography. The main geological structures in the study area (i.e. covered by seismic stations) are the four NE–SW trending volcanic systems, orientated highly oblique to the plate spreading on the RP. These are from west to east; Reykjanes, Eldvörp-Svartsengi, Fagradalsfjall and Krýsuvík, of which all except Fagradalsfjall host a known high-temperature geothermal field. Using surface waves retrieved from ambient noise recordings, we recovered a 3-D model of shear wave velocity. We observe low-velocity anomalies below these known high-temperature fields. The observed low-velocity anomalies below Reykjanes and Eldvörp-Svartsengi are significant but relatively small. The low-velocity anomaly observed below Krýsuvík is both larger and stronger, oriented near-perpendicular to the volcanic system, and coinciding well with a previously found low-resistivity anomaly. A low-velocity anomaly in the depth range of 5–8 km extends horizontally along the whole RP, but below the high-temperature fields, the onset of the velocity decrease is shallower, at around 3 km depth. This is in good agreement with the brittle–ductile transition zone on the RP. In considerably greater detail, our results confirm previous tomographic models obtained in the area. This study demonstrates the potential of the entirely data-driven, one-step 3-D transdimensional ambient noise tomography as a routine tomography tool and a complementary seismological tool for geothermal exploration, providing an enhanced understanding of the upper crustal structure of the RP. [ABSTRACT FROM AUTHOR]

First-arrival picking is a fundamental and challenging task in seismic data processing. Existing algorithms such as the cross-correlation algorithm (CCT) struggle to achieve satisfactory noise immunity while maintaining picking efficiency. In this paper, we propose the first-arrival picking through mathematical morphology and edge detection (FPME) algorithm with three steps. The converting step transforms the original data into a binary image though a filtering technique, where the binary image represents the global energy distribution of high-energy and low-energy samples. The rendering step delimits the signal zone in the binary image through morphological operations, where the signal zone eliminates the noise in the upper part. The picking step detects first arrivals in the signal zone through the edge detection methods, where an evaluation function is designed to select the optimal detection results as first arrivals. Experiments were performed on four field data sets. The results demonstrated that FPME is more stable and reliable than five classic and popular algorithms. [ABSTRACT FROM AUTHOR]

The Eastern-Europe region (EER), is a complex geotectonic area that captures part of the Alpine-Himalayan Orogen, the subduction of multiple NeoTethys Branches and part of the East European Craton. It is one of the most exciting geological areas in Europe due to a diversity of tectonic processes acting within it: extensional basin evolution, oceanic subduction, post-collisional volcanism, as well as active crustal deformation associated with the push of the Adria plate or the pull of the actively detaching Vrancea slab. This makes EER an excellent natural laboratory to study the behaviour of the lithosphere–asthenosphere system in a heterogeneous tectonic setting. To investigate the lateral heterogeneity and physical properties of the crust in the EER, we use ambient seismic noise data recorded by the vertical components of broad-band stations that have been operational between 1999 and 2020 in Eastern Europe and surrounding regions. We used this significant amount of data and the latest processing techniques of the ambient seismic noise field based on the continuous wavelet transform to compute cross-correlations between various station pairs, turning every available seismic station into a virtual source. The coda of the interstation cross-correlograms were used to determine coda quality factors (Qc) of Rayleigh waves in four different period ranges (3.0–5.0, 5.0–10.0, 10.0–20.0 and 20.0–30.0 s) and to invert them in the 2-D space, constructing the highest resolution attenuation tomography of the region. Our results reveal high attenuation features throughout the northeast Pannonian region, the Bohemian Massif, the East Carpathians and the Moesian Platform. Nevertheless, our findings do not emphasize a close correlation between the depth of sedimentary basins and attenuation features identified at longer periods. In addition, Qc variations are larger at short periods, indicating higher heterogeneity in the uppermost crust of Eastern Europe. Our findings demonstrate the higher efficiency of noise correlation approaches relative to earthquake data analyses investigating Qc at low frequencies. [ABSTRACT FROM AUTHOR]

In this work, we present both 1-D and 3-D shear wave velocity (Vs) models of the oceanic crust and uppermost mantle below the Deep OCean Test ARray area, located ∼ 70 km north of the central section of the Gloria Fault, in the eastern North-Atlantic Ocean. The velocity models are inferred from the dispersion of surface waves recorded on ocean bottom seismometers. Dispersion measurements are obtained from the analysis of ambient seismic noise at short periods (< 14 s) and teleseismic surface waves at long periods (> 14 s) using the two-station method. The 1-D Vs model is inferred from the joint inversion of Rayleigh wave phase velocities and Love wave group and phase velocities. The 3-D tomographic model is obtained by inversion of 2-D Love wave group velocity maps as a function of depth, further constrained by the average of Love wave phase velocities obtained from ambient noise (4–9 s) and the average Rayleigh and Love wave phase velocities calculated from teleseismic data (14–44 s). The 1-D Vs model shows a sediment layer with a low velocity of 1.05 km s−1, similar to previous studies in the region. Below the sediments, we find an oceanic crust with velocities ranging from 3.3 to 4.5 km s−1. The model reaches an unusually high velocity of 4.9 km s−1 in a 20 km thick layer at depths between 16 and 36 km. We interpret this fast velocity layer as indicative of the presence of harzburgite, a residue of enhanced melting that might have been formed by the proximity between the Mid-Atlantic Ridge and the Azores mantle plume. At greater depths the velocity decreases, forming a low-velocity zone that reaches a minimum at ∼ 70 km depth, which we interpret as the maximum depth for the lithosphere–asthenosphere boundary. The 3-D model shows a structure that is mostly horizontally layered, with Vs isocontours at 3.5–4.5 km s−1 highlighting oscillations of the crustal structure with wavelengths of ∼25–30 km. These oscillations may be due to changes in the rate of mantle upwelling and magma supply rate. [ABSTRACT FROM AUTHOR]

Abstract Understanding glaciers structural heterogeneity is crucial for assessing their fate. Yet, places where structure changes are strong, such as crevasses fields, are often inaccessible for direct instrumentation. To overcome this limitation, we introduce an innovative technique that transforms seismic sources, here generated by crevasses, into virtual receivers using source‐to‐receiver spatial reciprocity. We demonstrate that phase interference patterns between well‐localized seismic sources can be leveraged to retrieve phase velocity maps using Seismic Michelson Interferometry. The obtained phase velocity exhibits sensitivity to changes in glacier structure, offering insights into the origins of mechanical property changes, with spatial resolution surpassing traditional methods by a factor of five. In particular, we observe sharp variations in phase velocity related to strongly damaged subsurface areas indicating a complex 3‐D medium. Applying this method more systematically and in other contexts will enhance our understanding of the structure of glaciers and other seismogenic environments.

Abstract We examined the seismic noise data collected from coastal and inland observatories in India, affected by the super cyclonic storm Amphan in the Indian Ocean, to understand the storm dynamics. Prominent disturbances in the 0.05–0.50 Hz frequency range were observed at the seismic stations, arising due to ocean‐continent interactions. The coastal stations displayed more pronounced ground motions contrary to the inland stations, with spindle‐shaped seismic wave envelopes intensifying as Amphan approached. The maximum ground displacements and energy occurred hours after the cyclone's eye, with maximum wind speed, moved away from the stations and not when it was close to the station. We observed significant variations in primary (0.05–0.10 Hz) and secondary microseism (0.10–0.50 Hz) energy during Amphan's directional changes. Secondary microseisms in short and long periods were found at 0.20–0.50 Hz and 0.10–0.20 Hz, respectively. Primary microseisms exhibited a simple pattern and were the weakest among the three energy bands. The CAL seismic station's seismic wave envelope showed an en‐echelon feature with increasing amplitude as Amphan approached, indicating the influence of ocean resonance and coastal wave reflection. This study demonstrates monitoring of the tropical cyclone paths based on seismic signatures obtained using microseisms recorded at seismic stations, a cost‐effective tool. Integrating these seismic signals with atmospheric observations in near real‐time would probably enable an effective monitoring of cyclones and timely issuance of their alerts.

Microcracks or micropores in rocks cause the elastic moduli to change with the applied strain owing to the nonlinear elasticity of the geomaterial, which causes temporal changes in the seismic wave velocity. Thus, variations in seismic wave velocity can be used as a proxy for understanding the strain or stress variations in the crust, which are crucial for figuring out the dynamics of the fault zones and volcanic domains. According to the theory of nonlinear elasticity, the second- and third-order elastic constants and strain tensors contribute to the strain derivative of seismic wave velocity changes. Although laboratory experiments have estimated third-order elastic constants for rock samples, the in situ values of those constants for the crust are difficult to obtain. In this study, seismic velocity changes were investigated in different directions of tidal deformations to provide constraints on the third-order elastic constants in the shallow crust by applying a seismic interferometry method to ambient noise records. We observed that negative velocity changes were of larger magnitude in the station-pair direction parallel to the tidal strain's direction. Nonlinear elasticity in shallow crust may cause anisotropic velocity variations in response to tidal deformations. Our results highlight the use of velocity change measurements in different directions of tidal strain to constrain nonlinear elastic parameters on a field scale. [ABSTRACT FROM AUTHOR]

Extreme weather events threaten life and property in populated areas. Timely and precise weather event monitoring and risk assessment are critical, but can be hampered by limited meteorological stations in cities. Recent studies have shown that seismic stations are sensitive to storm-induced noise. This study aims to investigate the sensitivity of distributed acoustic sensing (DAS), a technology capable of turning existing optical fibres into dense seismic sensors, for recording storm-induced seismic noise. We analyse 4-month continuous DAS recordings (June–September 2021) from a 4.2-km-long underground fibre-optic array in State College, PA. We calibrate the DAS data by comparing it to various meteorological data (rainfall and wind speed) from nearby weather stations. We first show DAS-recorded low-frequency wind-induced noise (0.5–8 Hz) probably caused by light poles swaying in the wind, as observed resonant frequencies agree with theoretical natural frequencies of nearby light poles. We find a strong linear correlation between DAS energy and wind speed. We further characterize rain-induced noise. Detailed observations from two rain events: a moderate rain and a heavy rain from Hurricane Ida, suggest that rain-induced noise is not generated by direct raindrops hitting the ground. Instead, the low-frequency noise (2–8 Hz) is attributed to the acoustic noise generated by water flow in stormwater drainage systems. Strong high-frequency noise up to 125 Hz is likely related to the rapid rainwater filling from the surface to the drainage system during heavy rain. We show linear relations between rain-induced DAS energy and rainfall rate, where the slopes of relations are related to the volume of rainwater, suggesting the influence of surface water and rainwater flow in the drainage system on DAS signals. Our results show the possibility of using DAS-equipped pre-existing telecom fibre-optic cables for sensing windstorms and rainstorms in urban areas and their interactions with urban infrastructures. [ABSTRACT FROM AUTHOR]

The orientation of S Hmax is commonly estimated from in situ borehole breakouts and earthquake focal mechanisms. Borehole measurements are expensive, and therefore sparse, and earthquake measurements can only be made in regions with many well-characterized earthquakes. Here, we derive the stress-field orientation using stress-induced anisotropy in nonlinear elasticity. In this method, we measure the strain derivative of velocity as a function of azimuth. We use a natural pump-probe (NPP) approach which consists of measuring elastic wave speed using empirical Green's functions (probe) at different points of the earth tidal strain cycle (pump). The approach is validated using a larger data set in the Northern Alpine Foreland region where the orientation of maximum horizontal compressive stress is known from borehole breakouts and drilling-induced fractures. The technique resolves NNW-SSW to N-S directed S Hmax which is in good agreement with conventional methods and the recent crustal stress model. We confirm that the NPP method can be applied to dense large-scale seismic arrays. The technique is then applied to the Southern Alps to understand the contemporary stress pattern associated with the ongoing deformation due to counterclockwise rotation of the Adriatic plate with respect to the European plate. Our results explain why the two major faults in Northeastern Italy, the Giudicarie Fault and the Periadriatic Line (Pustertal–Gailtal Fault) are currently inactive, while the currently acting stress field allows faults in Slovenia to deform actively. We have demonstrated that the pump-probe method has the potential to fill in the measurement gap left by conventional approaches, both in terms of regional coverage and in depth. [ABSTRACT FROM AUTHOR]

Stacking cross-correlations of time windows from continuous long-duration noise data is an effective solution to improve the quality of retrieved high-frequency (>1 Hz) surface waves and the accuracy of dispersion energy. The observation duration, however, is usually limited due to traffic control, making it difficult for ambient noise sources to fulfill the requirement of uniform distribution. Additionally, strong human-related noise sources exist near survey lines deployed along urban roads, which often act as interfering sources, such as local noise sources located in the non-stationary-phase zones. Local noise sources cause spurious arrivals in cross-correlations, degrade signal-to-noise ratio (SNR) of retrieved surface waves and distort their dispersion energy. To attenuate these adverse effects and improve the quality of surface waves retrieved from ultrashort noise data, we perform the eigendecomposition technique on the cross-spectral density matrix (CSDM) and apply a Wiener filter on the decomposed eigenvectors. The correct eigenvalues and the corresponding filtered eigenvectors are selected to reconstruct the CSDM related to stationary-phase sources based on the matched-field processing outputs. This procedure significantly suppresses the backpropagated signals and efficiently recovers surface waves by improving the contribution of the stationary-phase sources. We validate our scheme on a synthetic test and two practical applications and show that we obtain higher-SNR virtual shot gathers and higher-quality surface-wave dispersion images compared to seismic interferometry. Our scheme can be a new alternative technique to conduct passive seismic surveys in densely populated urban environments without being affected by local noise sources. [ABSTRACT FROM AUTHOR]

The Granada Basin in southeast Spain is an area of moderate seismicity. Yet, it hosts some of the highest seismic hazards in the Iberian Peninsula due to the presence of shallow soft sediments amplifying local ground motion. In urban areas, seismic measurements often suffer from sparse instrumentation. An enticing alternative to conventional seismometers is the distributed acoustic sensing (DAS) technology that can convert fibre-optic telecommunication cables into dense arrays of seismic sensors. In this study, we perform a shallow structure analysis using the ambient seismic field interferometry method. We conduct a DAS array field test in the city of Granada on the 26 and 27 August 2020, using a telecommunication fibre. In addition to the existing limitations of using DAS with unknown fibre-ground coupling conditions, the complex geometry of the fibre and limited data recording duration further challenge the extraction of surface-wave information from the ambient seismic field in such an urban environment. Therefore, we develop a processing scheme that incorporates a frequency–wavenumber (f − k) filter to enhance the quality of the virtual shot gathers and related multimode dispersion images. We are able to use this data set to generate several shear-wave velocity (VS) profiles for different sections of the cable. The shallow VS structure shows a good agreement with different geological conditions of soil deposits. This study demonstrates that DAS could provide insights into soil characterization and seismic microzonation in urban areas. In addition, the results contribute to a better understanding of local site response to ground motion. [ABSTRACT FROM AUTHOR]

We present a phase-delay detection procedure adapted for seismic arrays composed of a large number of stations. We use graph formalism to introduce a direct method to compute station phase delays starting from inter-station phase differences deduced from noise cross-correlation functions. We focus this study on surface wave main arrival as phase-difference evaluation at each station requires high coherence level. Then, we perform numerical experiments with synthetic data computed as a realistic and dense network of 79 stations in a 400 by |$400\, \mathrm{km^2}$| square box. For one of the 79 stations, we simulate a phase difference of 15 per cent of the signal period. Further, we evaluate the accuracy and precision of phase-delay estimation at each station with regard to the quality of the cross-correlation functions (i.e. the signal-to-noise ratio). When the inter-station coherence levels are larger than 0.6 (i.e. a high-quality signal), we show good agreement between the phase-delay estimation and its expected value of 15 per cent of the signal period. We introduce a coherence-weighted estimate of phase delay and show that applying this weighting allows us to be less vulnerable to phase-delay underestimation for intermediate-quality signals. Then, the method is applied to experimental data recorded by a high density nodal array with 923 vertical geophones with 19 d of continuous records, centred on the 600 by |$600\, \mathrm{m^2}$| damage zone of the Clark branch of the San Jacinto Fault Zone, Southern California (USA). We verify that the San Jacinto network is well synchronized, as most of the estimated phase delays are less than 2 per cent of the central period of the signal, and they are associated with high levels of inter-station coherence. More surprisingly, the spatial features of the estimated phase delays show deterministic geographical patterns that are related to topography and that exhibit similarities with phase velocity maps at |$4.5\, \mathrm{Hz}$| from previous 3-D velocity inversions. This suggests that the topographic effect may be accounted for to estimate accurate phase delays. Also, we note that the temporal variability of the estimated phase delays in the case of the San Jacinto data set are related to atmospheric forcing. Our direct method for estimating phase delays is applicable to structure-oriented monitoring studies, and it opens perspectives in the monitoring of seismic velocity variations. [ABSTRACT FROM AUTHOR]

During the RESOLVE project ("High‐resolution imaging in subsurface geophysics: development of a multi‐instrument platform for interdisciplinary research"), continuous surface displacement and seismic array observations were obtained on Glacier d'Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d'Argentière. Using multiple bandpass‐filtered copies of the continuous seismic waveforms, we compute energy‐based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on‐ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity. Plain Language Summary: Alpine glaciers are a major component in the dynamic cryospheric environment. They are characterized by a multitude of processes occurring side by side, including but not limited to melt water flow, crevasse formation, and frictional basal sliding of the ice mass over the rigid and obstructive bedrock. Each of these processes generates distinctive acoustic signals that can be recorded by seismic instruments and the changing on‐ice motions are resolvable with Global Positioning System. Considering the rapidly changing glacial environment, there is an increasing need for reliable models to predict glacial dynamics to properly assess any associated hazard. Understanding basal sliding is of particular interest to this problem. Investigated here is how to overcome the challenge of describing glacier sliding using seismic signals since the records often contains multiple "loud" signals originating from associated surface processes within the glacier. To uncover specific processes occurring at the ice‐bedrock interface, we design a machine learning model to incorporate signals recorded on the glacier to predict the on‐ice surface motions. The results provide valuable insights into the spatiotemporal dynamics of an active Alpine glacier with the potential to contribute to a better understanding of the driving mechanisms of glacier sliding. Key Points: Seismic and Global Positioning System (GPS) data are examined to study physical processes controlling glacial basal motionDecision tree model uses beamforming catalog and statistical features of time series to constrain correlations with GPS recorded motionsModel features indicate glacial on‐ice velocity is modulated by basal motions [ABSTRACT FROM AUTHOR]

Human activities generate seismic waves, which have been traditionally analysed by seismic interferometry. However, this processing technique often neglects the seismic source distribution and is prone to introducing biases in interpretations. This study proposes an alternative processing technique known as seismic stereometry to analyse seismic signals generated by cars. The proposed algorithm exploits the highly coherent wavefields recorded by dense seismic arrays and directly measures the seismic wave traveltime differences between sensors. By doing so, it intrinsically considers the seismic source distribution. Traveltime differences can be used to invert the positions of vehicles and the near-surface velocity structures. We demonstrate the analysis using a dense seismic array deployed atop a southern San Andreas Fault segment and invert the shallow S -wave velocity using seismic waves generated by only one car. The velocity inversion result reveals a clear contrast across the fault, consistent with previous studies. The developed technique, combined with the distributed acoustic sensing technology, has great potential for applications in the urban environment. [ABSTRACT FROM AUTHOR]

Automatic detection of seismic events in ocean bottom seismometer (OBS) data is difficult due to elevated levels of noise compared to the recordings from land. Popular deep-learning approaches that work well with earthquakes recorded on land perform poorly in a marine setting. Their adaptation to OBS data requires catalogues containing hundreds of thousands of labelled event examples that currently do not exist, especially for signals different than earthquakes. Therefore, the usual routine involves standard amplitude-based detection methods and manual processing to obtain events of interest. We present here the first attempt to utilize a Random Forest supervised machine learning classifier on marine seismological data to automate catalogue screening and event recognition among different signals [i.e. earthquakes, short duration events (SDE) and marine noise sources]. The detection approach uses the short-term average/long-term average method, enhanced by a kurtosis-based picker for a more precise recognition of the onset of events. The subsequent machine learning method uses a previously published set of signal features (waveform-, frequency- and spectrum-based), applied successfully in recognition of different classes of events in land seismological data. Our workflow uses a small subset of manually selected signals for the initial training procedure and we then iteratively evaluate and refine the model using subsequent OBS stations within one single deployment in the eastern Fram Strait, between Greenland and Svalbard. We find that the used set of features is well suited for the discrimination of different classes of events during the training step. During the manual verification of the automatic detection results, we find that the produced catalogue of earthquakes contains a large number of noise examples, but almost all events of interest are properly captured. By providing increasingly larger sets of noise examples we see an improvement in the quality of the obtained catalogues. Our final model reaches an average accuracy of 87 per cent in recognition between the classes, comparable to classification results for data from land. We find that, from the used set of features, the most important in separating the different classes of events are related to the kurtosis of the envelope of the signal in different frequencies, the frequency with the highest energy and overall signal duration. We illustrate the implementation of the approach by using the temporal and spatial distribution of SDEs as a case study. We used recordings from six OBSs deployed between 2019 and 2020 off the west-Svalbard coast to investigate the potential link of SDEs to fluid dynamics and discuss the robustness of the approach by analysing SDE intensity, periodicity and distance to seepage sites in relation to other published studies on SDEs. [ABSTRACT FROM AUTHOR]

Seismically triggered subaqueous mass movements in lakes may generate tsunamis that can cause significant damage on the shore. In this study, we assess the seismic response and stability of subaqueous slopes in Swiss lakes based on recorded seismological data, historical and geological information and geotechnical surveys. We performed seismic investigations at multiple locations in Lake Lucerne using Ocean Bottom Seismometers (OBS). For these locations, we derived ground-motion amplification functions from local and regional earthquakes and horizontal-to-vertical spectral ratios (H / V) from the earthquake and ambient vibration recordings. The results show (1) very high amplification levels, often exceeding values of 50–100 in the frequency range between 1 and 10 Hz, (2) the fundamental frequency of resonance in the range of 0.5–3.5 Hz and (3) laterally variable site response even for closely located stations. We sought also the signatures of non-linear site response in the H / V curves or ground-motion amplification functions but found only weak indicative effects and no clear evidence. This is most likely due to the low levels of ground motion recorded during the OBS campaigns. We conducted back analyses of historical earthquakes in Switzerland with available documental and/or geological evidence of induced (tsunamigenic) subaqueous slope failures in Swiss lakes. The data set of historical events was complemented with a selection of instrumentally recorded earthquakes in Switzerland. For the analyses, we selected multiple sites in Swiss lakes which failed in the past or are prone to failure in the future. We modelled the ground motion at these locations assuming Swiss standard reference rock conditions (v s 30 = 1105 m s−1). The modelled ground motion intensity measures (IM) included peak ground acceleration (PGA), peak ground velocity (PGV) and pseudospectral acceleration (PSA) at 0.3, 1 and 2 s. We estimated the minimum ground motion and macroseismic intensity at reference rock conditions required to trigger the failures of subaqueous slopes. In addition, we defined a threshold for the seismic triggering of such failures in terms of moment magnitude (M w) and epicentral distance (Re) as: $$\begin{eqnarray} M_{\rm w}=2.891+1.904\log_{10}(R_e+5.166)\: {\rm for}\: R_e\ge 3.7\: {\rm km}. \end{eqnarray}$$ Our results are consistent with previous studies based on worldwide observations. Furthermore, we related the modelled ground motions to the Swiss seismic hazard products and estimated the return period of critical ground shaking responsible for triggering subaqueous slope failures (with potential for tsunami generation) to be in the range of 36–224 yr. Finally, based on previously collected geotechnical data (in situ Cone Penetration Testing and laboratory sediment analysis), we determined the most likely values of the seismic coefficient k to be used with the ground motion IMs modelled at reference rock conditions in infinite slope stability analyses to estimate the factor of safety (FS). For PGA, we found a k = 1; for PGV, k = 2; for PSA0.3s, k = 0.6; for PSA1s, k = 2 and for PSA2s, k = 5.5. These estimates are conservative and affected by the trade-off between the thickness of unconsolidated sediments and the slope angle. Thus, we recommend applying them to slopes with a low-to-moderate gradient (<15°) and sediment thickness of more than 2 m. [ABSTRACT FROM AUTHOR]

In this paper, a method is proposed for estimating the intensity distribution of microtremors for the arrival direction, from simultaneous observations of vertical motion, using an array of simple geometry consisting of only three receivers. This method is based on the fact that the complex coherence function, which is defined as the normalized cross-spectrum of microtremor recordings observed at two sites, contains information about the azimuthal intensity distribution of the microtremor field. To obtain the azimuthal intensity distribution from a limited number of conditions, the functional form of the azimuthal intensity distribution of the microtremor field was assumed and its parameters were estimated. Information on the arrival direction of the microtremor field was specifically obtained using particle swarm optimization (PSO), one of the metaheuristic methods, and then employed to identify the parameters. The proposed method was applied to ideal synthetic data to clarify the potential problems that may arise from using PSO as the core algorithm. Despite PSO-induced errors, the proposed method was able to accurately infer directional information over a wide frequency range. The proposed method was also applied to actual field data to verify its effectiveness and applicability. The results indicate that the proposed method can provide similar results to the frequency–wavenumber (FK) method in a wide frequency range. The quasi-FK spectrum, an effective mode representation of the FK spectrum, was displayed to visualize the directionality. [ABSTRACT FROM AUTHOR]

We performed laboratory tests and field surveys to evaluate the performance of a low‐cost 3‐component seismometer, consisting of three passive electromagnetic spring‐mass sensors, whose 4.5 Hz natural frequency is extended down to 0.5 Hz thanks to hyper damping. Both lab and field datasets show that the −3 dB band of the seismometer ranges approximately from 0.7 to 39 Hz, in agreement with the nominal specifications. Median magnitude frequency response curves obtained from processing field data indicate that lower corner of the −3 dB band could be extended down to 0.55 Hz and the nominal sensitivity may be overestimated. Lab results confirm the non‐linear behavior of the passive spring‐mass sensor expected for high‐level input signals (a few to tens of mm/s) and field data confirm relative timing accuracy is ±10 ms (1 sample). We found that absolute timing of data collected with USB GPS antennas can be affected by lag as large as +0.5 s. By testing two identical units, we noticed that there could be differences around 0.5 dB (i.e., about 6%) between the components of the same unit as well as between the same component of the two units. Considering shallow passive seismic applications and mainly focusing on unstable slope monitoring, our findings show that the tested seismometer is able to identify resonance frequencies of unstable rock pillars and to generate interferograms that can be processed to estimate subsurface velocity variations. Plain Language Summary: This study describes some tests that we did to evaluate a seismometer that is cheaper than similar products on the market. A seismometer is able to sense and collect seismic waves and can be used for several applications including global seismology and hydrocarbon exploration. In our work, we consider passive seismic applications, that is, we focus on seismic waves generated by non‐controlled sources (aka seismic noise). Either the seismic sources are natural or man‐made, a valuable seismometer should allow to record weak signals in a wide frequency band, especially at relatively low frequency (<5 Hz). The results of our tests show that the cheap seismometer can record frequencies down to approximately 0.5 Hz, while, to keep costs low, the highest frequency is limited to about 40 Hz. Field tests show that the seismometers can retrieve information from seismic noise as weak as a few micrometers per second, while lab test with higher inputs shows that the response of the seismometer is dependent upon the input velocity. Overall, we found that the nominal specifications of the seismometers are met, thus the tested unit is a valuable tool for shallow passive‐seismic applications with relatively‐low‐frequency, low‐amplitude signals, and a limited budget. Key Points: A low‐cost 3‐component seismometer has been tested for passive shallow applicationsThe seismometer has non‐linear response for high‐amplitude (mm/s) excitation signalsLab and field tests confirm the −3 dB band ranges from 0.7 to 39 Hz and an offset of about 0.5 s was found in the filed data whose timing was provided by a USB GPS antenna [ABSTRACT FROM AUTHOR]

In active underground mining environments, monitoring mine vibrations has important implications for both safety and productivity. Microseismic data processing is crucial for subsurface real-time monitoring during mineral mining processes. Microseismic events are difficult to detect due to their small magnitudes and low signal-to-noise ratios (SNRs). Useful microseismic signals are usually obscured by long-period microseisms, random noise and artificial strong noise. We propose a useful microseismic denoising algorithm based on the normal time–frequency transform (NTFT) to determine the instantaneous frequency, amplitude and phase information from useful microseismic signals. The energy difference in the time–frequency domain between useful microseismic signals and strong noise is small. Therefore, based on the different phase characteristics of microseismic signals and noise in the NTFT phase spectrum, noise can be filtered out by reconstructing the microseismic signals in useful real-time frequency bands. The proposed simple bandpass filtering (SBPF) method is advantageous because the denoising result does not produce phase shifts, energy leakage or artefacts. The only parameter of the proposed method that needs to be defined is the instantaneous cutoff frequency; thus, the denoising operation is simple. We use both synthetic and real data to demonstrate the feasibility of the method for denoising complicated microseismic datasets. [ABSTRACT FROM AUTHOR]

This paper introduces SEISMONOISY, an application designed for monitoring the spatiotemporal characteristic and variability of the seismic noise of an entire seismic network with a quasi-real-time monitoring approach. Actually, we have applied the developed system to monitor 12 seismic networks distributed throughout the Italian territory. These networks include the Rete Sismica Nazionale (RSN) as well as other regional networks with smaller coverage areas. Our noise monitoring system uses the methods of Spectral Power Density (PSD) and Probability Density Function (PDF) applied to 12 h long seismic traces in a 24 h cycle for each station, enabling the extrapolation of noise characteristics at seismic stations after a Seismic Noise Level Index (SNLI), which takes into account the global seismic noise model, is derived. The SNLI value can be used for different applications, including network performance evaluation, the identification of operational problems, site selection for new installations, and for scientific research applications (e.g., volcano monitoring, identification of active seismic sequences, etc.). Additionally, it aids in studying the main noise sources across different frequency bands and changes in the characteristics of background seismic noise over time.

In the territory of Dushanbe city, the capital of Tajikistan, detailed geological and geophysical data were collected during geophysical surveys in 2019–2020. The data comprise 5 microtremor array measurements, 9 seismic refraction tomography profiles, seismological data from 5 temporary seismic stations for standard spectral ratio calculations, 60 borehole datasets, and 175 ambient noise measurements. The complete dataset for Dushanbe was used to build a consistent 3D geologic model of the city with a size of 12 × 12 km2. The results of the seismological and geophysical surveys were compared and calibrated with borehole data to define the boundaries of each layer in the study area. The Leapfrog Works software was utilized to create a 3D geomodel. From the 3D geomodel, we extracted six 12 km long 2D geological cross-sections. These 2D geological cross-sections were used for 2D dynamic numerical modeling with the Universal Distinct Element Code software to calculate the local seismic response. Finally, the dynamic numerical modeling results were compared with the amplification functions obtained from the seismological and ambient noise data analysis. The 2D dynamic numerical modeling results allowed a better assessment of the site effects in the study area to support seismic microzonation and the determination of local peak ground acceleration changes in combination with regional seismic hazard maps. In addition, our results confirm the strong seismic amplification effects noted in some previous studies, which are attributed to the influence of local topographic and subsurface characteristics on seismic ground motions.

Surface wave retrieval from ambient noise records using seismic interferometry techniques has been widely used for multiscale shear wave velocity (Vs) imaging. One key step during Vs imaging is the generation of dispersion spectra and the extraction of a reliable dispersion curve from the retrieved surface waves. However, the sparse array geometry usually affects the ability for high-frequency (>1 Hz) seismic signals' acquisition. Dispersion measurements are degraded by array response due to sparse sampling and often present smeared dispersion spectra with sidelobe artefacts. Previous studies usually focus on interferograms' domain (e.g. cross-correlation function) and attempt to enhance coherent signals before dispersion measurement. We propose an alternative technique to explicitly deblur dispersion spectra through use of a phase-weighted slant-stacking algorithm. Numerical examples demonstrate the strength of the proposed technique to attenuate array responses as well as incoherent noise. Three different field examples prove the flexibility and superiority of the proposed technique: The first data set consists of ambient noise records acquired using a nodal seismometer array; the second data set utilizes distributed acoustic sensing (DAS) and a marine fibre-optic cable to acquire a similar ambient noise data set; the last data set is a vibrator-based active-source surface wave data. The enhanced dispersion measurements provide cleaner and higher-resolution spectra without distortions which will assist both human interpreters as well as ML algorithms in efficiently picking curves for subsequent Vs inversion.