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Unstable rock slopes, prone to collapse, pose an increasingly severe threat to both people and infrastructures, necessitating effective monitoring for risk mitigation. While many techniques rely on surface displacements to assess slope stability, seismic indicators such as resonance frequency, variations in seismic wave velocity and site amplification offer valuable insights into the structural integrity of the slope, aspects not captured by surface deformation alone. Research has demonstrated that these site-response parameters can serve as monitoring tools to detect precursory signs of failure, such as a drop in resonance frequency and relative seismic wave velocity prior to collapse. Still, environmental factors like temperature, precipitation, snow melt, earthquakes and freeze-thaw cycles transiently influence the seismic response. Our main objective is to understand the correlations and drivers between environmental parameters and seismic response, distinguishing between reversible and irreversible changes in dynamic behaviour. Over a 5-yr monitoring period, we continuously recorded ambient vibration data at the Brienz/Brinzauls instability and monitored three different site-response parameters (resonance frequency, site amplification, relative seismic wave velocity variation) using enhanced frequency domain decomposition, site-to-reference spectral ratio and single station ambient vibrations correlation techniques. Our results highlight a long-term increase in site amplification and a long-term decrease in first and second resonance frequencies, indicating ongoing structural weakening. Temperature was found to correlate with seasonal variations of seismic wave velocity with a few day's time lag. Snow melting and rainfalls exerted a secondary influence, temporarily reducing relative seismic wave velocity during snowmelt and rainfall. Our findings suggest that single-station relative seismic velocity variations are mainly influenced by the shallow subsurface (depth of about 30 m), limiting its application to study the stability this deep structure. [ABSTRACT FROM AUTHOR]

The advancement of seismic methods is vital for mineral exploration in the ongoing energy transition. In this study, we investigate the application of ambient noise seismic interferometry and surface-wave analysis to characterize the subsurface in a mineral exploration context. We then confirm the results of the passive seismic investigation through an active source experiment. We collected ambient noise data using a 2-D seismic line initially deployed for an active source reflection seismic study. By cross-correlating the signals, we retrieved the surface waves and constructed a 2-D shear-wave velocity profile using conventional surface-wave analysis. We utilized the active source data to establish initial assumptions about the surveyed medium and then validated the passive seismic experiment. The passive seismic results are concordant with the active source results and allow for the interpretation of geological contacts and fault zones. Our work demonstrates the potential of passive seismic methods for investigating local tectonic settings and their role in hardrock mineral exploration. [ABSTRACT FROM AUTHOR]

Distributed acoustic sensing (DAS) turns a fibre optic into a very dense network of equally distributed seismic sensors. We focused on the high-density sampling of the seismic wavefield, expressed in strain rates, measured by DAS. Classical approaches used to identify seismic signals rely on the recorded features at one station, but it is difficult to include spatial information in case of dense seismic station networks. This work aims at introducing new spatial and similarity features for seismic event classification suitable to analyse DAS observations. We propose a processing chain based on the XGBoost algorithm and the use of specifically designed spatiotemporal and similarity features for the event classification, and Markov random field for the spatial clustering. The methodology is designated to be applied on a continuous stream of DAS observations. We tested our processing chain to detect earthquakes and quarry blasts recorded in the region by permanent seismic networks and included in the RENASS catalogue. These events are part of a strain-rate seismic survey carried out during a 3 weeks campaign of DAS measurements along à 91 km fibre optic cable deployed in the central Pyrenees mountains (France). Despite the high anthropogenic activities along the fibre optic path, the proposed method succeeded in detecting earthquakes of magnitude >0.4 and quarry blasts of magnitude >1.0 while limiting the number of false alarms. This performance is particularly noteworthy for low-magnitude events, where detection is accomplished despite a lower signal-to-noise ratio compared to traditional seismometers. The methodology opens the door to real time detection and classification of seismic events measured with long-distance fibre optic systems. [ABSTRACT FROM AUTHOR]

An accurate and efficient method for picking the first arrival of microseismic signals is crucial for processing microseismic monitoring data. However, the weak magnitude and low signal-to-noise ratio (SNR) of these signals make picking arrivals challenging. Recent advancements in deep learning-based methods for picking the first arrivals of microseismic signals have effectively addressed the inefficiencies and inaccuracies of traditional methods. Nevertheless, these methods often require many training samples, and the substantial size and labelling effort significantly hinder the development of deep learning-based first-arrival picking methods. This study introduces Semi-Picking: a semi-supervised method for picking the first arrival of microseismic signals, utilizing the TransUGA network and SimMatch. This approach automatically labels microseismic signals following sample augmentation by establishing a semi-supervised learning framework, significantly reducing the time required for sample labelling. Initially, the TransUNet model is enhanced by incorporating the Self-Supervised Predictive Convolutional Attention Block (SSPCAB) module to create a Deep-TransUNet architecture, which more effectively separates signal from noise in microseismic signals with low SNR and improves the accuracy of first-arrival picking. Subsequently, the data sets for this study are compiled from microseismic traces collected from field monitoring records. Finite-difference forward modelling is applied to the microseismic data to train the network, and hyperparameter tuning is performed to optimize the UGATIT and Deep-TransUNet architecture. The outcomes of the arrival-picking experiments, conducted under conditions of low SNR using both synthetic and real microseismic records, demonstrated that Semi-Picking offers robust resistance to incorrect labels. This resilience stems from the synergistic use of the semi-supervised learning framework and self-attention mechanisms. The proposed method demonstrates superiority over the TransUNet, the SSPCAB-TransUNet, the UNet++ and the traditional short-term average/long-term average method, respectively, with the picking error rate of the Semi-Picking Net being less than 0.1 s. The proposed method outperforms the commonly used deep learning-based approaches for picking the first arrivals of microseismic signals, exhibiting superior performance. [ABSTRACT FROM AUTHOR]

Accurate timing corrections for seismic data recorded by ocean bottom seismometers (OBSs) are essential for a wide range of applications. The synchronization of internal OBS clocks with Global Positioning System (GPS) is typically only possible prior to deployment on the seafloor and upon retrieval. Thus, untracked, clock errors in seismic data may accumulate over the deployment period. The measurement of the clock's offset from GPS at retrieval, referred to as 'skew', can be used to correct the data solely under the assumption of a uniform rate of clock drift throughout the whole deployment. However, clock errors can be non-linear. We, therefore, develop a new workflow along with an associated open-source, interactive graphical user interface to estimate clock drift of large aperture OBS arrays. We use the workflow to estimate OBS clock drift curves for 40 OBSs of the large-scale UPFLOW seafloor array in the Madeira–Azores–Canaries region deployed for ∼14 months in 2021–2022. We use the relative shift of daily empirical Green's functions obtained from seismic ambient noise recorded by all available data channels to track clock error. We find that 95 per cent of our OBS clock drift observations have a substantial non-linear component: most maximum deviations to linearity are ∼0.75–1 s (and up to 2 s) occurring mainly halfway through the deployment. We test our drift curves by using them to correct teleseismic earthquake recordings, which enables larger numbers of high-quality P -wave traveltime measurements than when using linear drift corrections. Our drift curves have on average an uncertainty of ∼0.11 s indicating the suitability of the corrected data for future seismological studies such as for seismic tomography, seismicity analysis and moment tensor inversions. [ABSTRACT FROM AUTHOR]

Imaging the detailed structure of sedimentary basins is crucial for natural resource exploration and essential for better analysis and correction of sediment responses when studying deeper interior earth structures using seismic data. In the Tarim Basin, previous studies on the sedimentary structures are mostly obtained by active-source seismic surveys, which can provide high-resolution underground interface information but are highly costly or environmentally unfriendly. In this paper, ambient noise tomography, an efficient and economical method based on background vibration, is employed to construct the sedimentary velocity structure at the southeast margin of the Tarim Basin. Based on ambient noise data collected from a linear dense short-period seismic array, we extract Love wave signals from T–T component cross-correlation functions (CCFs) and measure Love wave dispersion curves at a period band of ∼0.3–11.5 s. Then, we utilize a one-step direct surface wave tomography method to image a fine 2-D sedimentary shear wave velocity structure with a depth reaching 10 km. Our results reveal a clear layered sedimentary structure, the palaeo Tadong uplift and the thrust Cherchen fault. Our study provides reference sedimentary velocity models for the southeastern Tarim Basin, focusing on depths shallower than 10 km. This model is intended to serve as crucial input for studies requiring detailed shallow sedimentary velocity data. Moreover, our research demonstrates that the application of the ambient noise tomography method with dense arrays has great potential for enhancing resource exploration efforts in sedimentary basins. [ABSTRACT FROM AUTHOR]

We construct a 3-D shear-wave velocity model for the crustal structure and the geometry of the Adana and Iskenderun basins by using ambient noise tomography of Rayleigh waves. For this purpose, we compute interstation Green's functions and measure the group velocity dispersion in the period range of 8–25 s. Then Rayleigh wave group velocity maps obtained by tomographic inversion are used to derive a shear wave velocity model by linearized inversion. Both Rayleigh wave group velocity maps and the 3-D shear-wave velocity structure are correlated with the geology and the major tectonic features of the region. Cross sections taken from the velocity model suggest a sediment thickness of up to 11 km in the wedge-shaped Adana Basin with the velocity ranging between 2.4 and 2.9 km s−1. The horseshoe-like high velocities surrounding the basin correspond to the Taurus Mountains in the west and north, and the Amanos Mountains in the east. In the region, down to a depth of 35 km the crustal velocity varies between 2.9 and 3.7 km s−1. Our investigations reveal the detailed 3-D basin geometry and crustal structure that can be beneficial for hazard assessment, geodynamic modelling as well as hydrocarbon exploration studies. [ABSTRACT FROM AUTHOR]

We present a method to jointly invert surface wave dispersion data and gravity measurements for 3-D shear wave velocity and density models. We implemented a petrophysical approach to combine the kernels of both methodologies in a single process. The synthetic experiments show that jointly inverted models recover shear wave velocity and density better than separate inversions. In particular, density models benefit from the good vertical resolution of surface wave dispersion data, while shear velocity models benefit from the good lateral resolution of gravity data. We also proposed two methods to stabilize the solution when using high-grade polynomials. We applied the methodology to the Los Humeros Geothermal area to demonstrate its applicability in a complex geological scenario. Compared with separate inversion, the joint inversion contributes to enhancing key aspects of the geothermal system by (i) delimitating better the geometry of the caldera deposits in the first 0–2.8 km deep by increasing the vertical resolution in density, (ii) delimitating better the lateral borders of low- Vs bodies at different depths interpreted as a part of a complex magmatic chamber system and (iii) estimating the local shear wave velocity–density relationship that conforms to other known relationships for sedimentary and igneous rocks but with some differences that bring us additional information. [ABSTRACT FROM AUTHOR]

Monitoring seismic velocity changes obtained from ambient noise correlations is widely used to understand changes in rock properties in response to earthquakes, volcanic activities and environmental changes. Since continuous seismic data have been accumulated, this method can estimate long-term changes in seismic velocity, such as crustal recovery after a major earthquake and temporal variations in seismic velocity related to long-term environmental change. Changes in seismic velocity can be estimated with a high temporal resolution by measuring the phase differences of ambient noise correlations based on a seismic interferometry method. Still, these phase differences are influenced not only by seismic wave velocity changes but also by errors in clock timing in seismometers. The clock drift occurs due to out-of-synchronization with the GPS clock and the drift of the internal clock. Therefore, to accurately monitor temporal changes in crustal structure by measuring the phase differences of noise correlations, it is crucial to evaluate the contribution of errors in clock timing to the phase differences. Recently, a method using an extended Kalman filter based on a state-space model was developed for reliable detection of temporal changes in the waveforms of ambient noise correlations, with the state-space model offering the advantage of flexible modelling of time-series data. In this study, we incorporated the time-shifts caused by clock time errors of the seismometer into the state-space model of the temporal changes in ambient noise correlations. We estimated seismic velocity changes, amplitude changes of noise correlations and clock time errors from 2010 April to 2021 September at seismic stations around the Shinmoe-dake volcano in Japan, which experienced eruptions in 2011 and 2018, respectively. Several stations exhibited clear clock time offsets, and the occurrence of clock time-shifts coincided with the dates when the data logger was turned off for seismic station maintenance or replacement of the seismometer. The proposed method provides stable estimations with respect to the signal-to-noise ratio of the waveform, and this stable estimation facilitates accurate timing of seismic recordings, enabling precise analysis of seismic phase arrival times. [ABSTRACT FROM AUTHOR]

When interpreting marine very high-resolution (VHR) single-channel seismic reflection data, the signal in the water column is generally considered as noise and is often eliminated by a water-mute application to focus on geological information under the seafloor. Alternatively, the signal in the water column can be used to study ocean currents or gas/fluid emissions. To provide images of the sedimentary formations and tectonic structures beneath the seafloor in shallow water regions, such as continental shelves and lakes, marine seismic reflection profiles are often acquired using a single-channel streamer and sparker-type source, providing VHR data, with limited penetration depth. To exploit the full potential of these single-channel data, we propose a simple algorithm, called REWARE (Recovery of Water-column Acoustic Reflectors). This algorithm allows to extract further geological information from the water-column data using open-source codes (Seismic Un*x), adding the coherent signal from the previous shots, recorded in the water column, to the previous traces. The record length becomes longer while maintaining a very high trace-to-trace consistency. To demonstrate its efficiency, we present two examples of the REWARE processing in two different geological contexts: the East Sardinia shelf (Italy) and the North Evia Gulf (Greece). This method provides deeper images than with original data for seismic data acquired across steep slopes, such as canyons or continental shelf breaks. Thus, depending on the seafloor geometry and subseafloor structures, it is possible to image or map sediment layers and tectonic structures at depth, keeping a very high structural resolution. [ABSTRACT FROM AUTHOR]

Oceanic transform faults (OTFs) facilitate hydrothermal circulation which can modify the fault zone materials and affect their rheological evolution. However, the depth extent and variability of fluid infiltration, degree of mineral alteration and their relationship with earthquake behaviour has only been characterized along a few OTFs globally. Here, we use first-overtone Rayleigh waves extracted from seismic ambient noise to estimate the shear-wave velocity structure beneath the Blanco Transform Fault Zone (BTFZ). Compared to the adjoining normal oceanic plates, relatively variable and slow velocities reduced by at least |$\sim$| 0.2–0.4 km s−1 (⁠|$\sim$| 4–8 per cent) are observed from the crust down to |$\sim$| 22 km depth along some segments of the BTFZ. The crustal slow velocities can be explained by enhanced fluid-filled porosity of |$\sim$| 0.4–10.9 per cent caused by intense fracturing associated with abundant seismicity. Slow uppermost mantle velocities are predominantly consistent with |$\sim$| 1.2–37 per cent serpentinization and |$\sim$| 9 per cent hydration, indicating variable and deep fluid infiltration that exceeds 15 km depth. For instance, shear-wave velocities (⁠|$\sim$| 4.3–4.4 km s−1) in the uppermost mantle beneath the Blanco Ridge suggest extensive serpentinization (⁠|$\sim$| 13–25 per cent), which might explain the recently documented earthquake swarms linked with aseismic creep. In comparison, within the vicinity of the ridge-transform intersections at depths |$\sim$| |$\gt $| 16 km, low velocities (⁠|$\sim$| 4.1–4.2 km s−1) that are consistent with the presence of up to |$\sim$| 1.6 per cent partial melt suggest intratransform magmatism which would contradict the long-held simple conservative strike-slip characterization of OTFs. [ABSTRACT FROM AUTHOR]

3-D shear wave velocity and density models are important for understanding the structures, material composition, tectonic deformations and dynamical mechanisms of the Earth's crust. Such models are usually based on surface wave tomography and gravity inversion, which provide high resolution in the vertical and horizontal directions, respectively. The joint inversion of surface wave and gravity methods can promote the mutual constraints and complementary advantages of seismic and gravity information, improving the imaging resolution and reducing the uncertainty in the individual methods. However, the traditional joint inversion methods directly construct only the shear wave velocity model, excluding density models. We present a joint inversion method of surface wave and gravity data that simultaneously constructs both crustal shear wave velocity and density models. Unlike the previous studies, we reconfigure the seismic kernels of surface wave tomography to preserve the seismic kernel of density. Moreover, the gravity kernel of density is combined with the seismic kernels to establish an objective function of simultaneous joint inversion. Consequently, the imaging resolution of density structure is improved. Our method is validated on the northeastern Tibetan plateau. The inversion results show that the Dingxi, Jiuzhaigou and Jishishan earthquakes occurred in the high–low-anomaly transition zones of shear wave velocity or density, implying that they were induced by accumulation of strain energy in the upper crust of the northeastern Tibetan plateau when the surrounding harder blocks extruded during the tectonic deformation process. [ABSTRACT FROM AUTHOR]

The Pannonian Basin, situated in Central Europe, is surrounded by the Alpine, Carpathian and Dinaric orogens. To understand its tectonic characteristics and evolution, we determine a shear wave velocity model of its crust, mantle lithosphere and asthenosphere consistently by jointly inverting Rayleigh wave phase velocities measured consistently from earthquake (EQ) and ambient noise (AN) data. For the AN data, continuous waveform data were collected from 1254 stations, covering an area within 9° from the centre of the Pannonian Basin during the time period from 2006 to 2018. This data set enabled the extraction of over 164 464 interstation Rayleigh phase-velocity curves, after applying a strict quality control workflow. For the EQ data set more than 2000 seismic events and about 1350 seismic stations were used in the broader Central and Eastern European region between the time-span of 1990 to 2015, allowing us to extract 139 987 quality controlled Rayleigh wave phase-velocity curve. Using the combined data set, a small period- and distance-dependent bias between ambient noise and earthquake measurements, mostly below 1 per cent but becoming larger towards longer periods has been found. After applying a period and distance dependent correction, we generated phase-velocity maps, spanning periods from 5 to 250 s. 33 981 local dispersion curves were extracted and a new approach is introduced to link their period-dependent roughness to the standard deviation. Using a non-linear stochastic particle swarm optimization, a consistent 3-D shear wave velocity model (PanREA2023) encompassing the crust and upper mantle down to 300 km depth was obtained with a lateral resolution reaching about 50 km at the centre of the study area for shorter periods. The crust beneath the Carpathian orogen exhibits a distinct low-velocity anomaly extending down to the Moho. It is referred to as Peri-Carpathian anomaly. Similar anomalies were observed in the Northern Apennines, while the Eastern Alps and Dinarides, as collisional orogens, generally demonstrate higher velocities in the upper crust. High crustal shear wave velocities are also evident in the Bohemian Massif and the East European Craton. The brittle upper crust of the Pannonian Basin is characterized by alternating NE–SW trending high- and low-velocity anomalies: the western and central Pannonian low-velocity anomalies and the Transdanubian and Apuseni high-velocity anomalies related to Miocene sedimentary basins and intervening intervening interbasinal highs exposing Pre-Cenozoic rocks including crystalline basement rocks. Beneath the Southeastern Carpathians, a NE-dipping slab was identified, extending to depths of at least 200 km, while a slab gap is evident beneath the Western Carpathians. A short south-dipping Eurasian slab was imaged beneath the Eastern Alps down to only 150–200 km depth. The Adriatic lithosphere is subducting near-vertically dipping beneath the Northern Apennines, and a slab gap was observed beneath the Central Apennines. In the Northern Dinarides, a short slab was evident, reaching depths of around 150 km. The Southern Dinarides featured a thinned but possibly incompletely detached slab. [ABSTRACT FROM AUTHOR]

The complete catalogue of moment tensor (MT) solutions is essential for a wide range of research in solid earth science. However, the number of reliable MT solutions for small to moderate earthquakes (3.0 ≤ M  ≤ 5.5) is limited due to uncertainties arising from data and theoretical errors. In this study, we develop a new procedure to enhance the resolvability of MT solutions and provide more reliable uncertainty estimates for these smaller to moderate earthquakes. This procedure is fully automatic and efficiently accounts for both data and theoretical errors through two sets of hybrid linear–non-linear Bayesian inversions. In the inversion process, the covariance matrix is estimated using an empirical approach: the data covariance matrix is derived from the pre-event noise and the theoretical covariance matrix is derived from the residuals of the initial solution. We conducted tests using synthetic data generated from the 3-D velocity model and interference from background seismic noise. The tests found that using a combination of the non-Toeplitz data covariance matrix and the Toeplitz theoretical covariance matrix improves the solution and its uncertainties. Test results also suggest that including a theoretical covariance matrix when analysing MT in complex tectonic regions is essential, even if we have the best 1D velocity model. The application to earthquakes in the northern region of the Banda Arc resulted in the first published Regional Moment Tensor (RMT) catalogue, containing more than three times the number of trusted solutions compared to the Global Centroid Moment Tensor (GCMT) and the Indonesian Agency for Meteorology Climatology and Geophysics Moment Tensor (BMKG-MT) catalogue. The comparison shows that the trusted solutions align well with the focal mechanism of the GCMT and BMKG-MT, as well as with the maximum horizontal stress of the World Stress Map, and tectonic conditions in the study area. The newly obtained focal mechanisms provide several key findings: (i) they confirm that the deformation in the northern and eastern parts of Seram Island is influenced by oblique intraplate convergence rather than by the subduction process; (ii) they validate the newly identified Amahai Fault with a greater number of focal mechanisms and (iii) they reveal an earthquake M w 4.7 with the same location and source mechanism 6 yr before the 2019 Ambon-Kairatu earthquake (M w 6.5) which occurred on a previously unidentified fault. [ABSTRACT FROM AUTHOR]

In the past two decades or so, ambient noise tomography (ANT) has emerged as a powerful tool for investigating high-resolution crustal and upper-mantle structures. A crucial step in the ANT involves extracting phase velocities from cross-correlation functions (CCFs). However, obtaining precise phase velocities can be a formidable challenge, particularly when significant lateral velocity variations exist in shallow subsurface imaging that relies on short-period surface waves from ambient noise. To address this challenge, we propose an unwrapping correction method that enables the accurate extraction of short-period dispersion curves. Our method relies on the examination of the continuity of phase velocities extracted from CCFs between a common station and other neighbouring stations along a linear array. We demonstrate the effectiveness of our approach by applying our method to both synthetic and field data. Both applications suggest our unwrapping correction method can identify and correct unwrapping errors in phase velocity measurements, ensuring the extraction of accurate and reliable dispersion curves at short periods from ambient noise, which is essential for subsequent inversion for subsurface structures. [ABSTRACT FROM AUTHOR]

Taiwan, one of the most active orogenic belts in the world, undergoes orogenic processes that can be elucidated by the doubly vergent wedge model, explaining the extensive island-wide geological deformation. To provide a clearer depiction of its cross-island orogenic architecture, we apply ambient noise tomography across an east–west linear seismic array in central Taiwan, constructing the first high-resolution 2-D shear velocity model of the upper crust in the region. We observe robust fundamental- and higher-mode Rayleigh waves, with the latter being mainly present in the western Coastal Plain. We develop a multimode double-beamforming method to determine local phase velocities across the array between 2- and 5-s periods. For each location, we jointly invert all available fundamental- and higher-mode phase velocities using a Bayesian-based inversion method to obtain a 1-D model. All 1-D models are then combined to form a final 2-D model from the surface to ∼10 km depth. Our newly developed 2-D model clearly delineates major structural boundaries and fault geometries across central Taiwan, thereby corroborating the previously proposed pro-wedge and retro-wedge models while offering insight into regional seismic hazards. [ABSTRACT FROM AUTHOR]

This study focuses on improving the seafloor compliance noise removal method, which relies on estimates of the compliance transfer function frequency response (the deformation of the seafloor under long-period pressure waves). We first propose a new multiscale deviation analysis of broad-band ocean–bottom seismometer data to evaluate stationarity properties that are key to the subsequent analysis. We then propose a new approach to removing the compliance noise from the vertical channel data, by stacking daily estimated transfer function frequency responses over a period of time. We also propose an automated transient event detection and data selection method based on a cross-correlation criterion. As an example, we apply the method to data from the Cascadia Initiative (network 7D2011). We find that the spectral extent of long-period forcing waves varies significantly over time so that standard daily transfer function calculation techniques poorly estimate the transfer function frequency response at the lowest frequencies, resulting in poor denoising performance. The proposed method more accurately removes noise at these lower frequencies, especially where coherence is low, reducing the mean deviation of the signal in our test case by 27 per cent or more. We also show that our calculated transfer functions can be transferred across time periods. The method should allow better estimates of seafloor compliance and help to remove compliance noise at stations with low pressure-acceleration coherence. Our results can be reproduced using the BRUIT-FM Python toolbox, available at https://gitlab.ifremer.fr/anr-bruitfm/bruit-fm-toolbox. [ABSTRACT FROM AUTHOR]

Cross-correlations of seismic ambient noise are frequently used to image Earth structure. Usually, tomographic studies assume that noise sources are uniformly distributed and interpret noise correlations as empirical Green's functions. However, previous research suggests that this assumption can introduce errors in the estimated models, especially when noise correlation waveforms are inverted. In this paper, we investigate changes in subsurface models inferred from noise correlation waveforms depending on whether the noise source distribution is considered to be uniform. To this end, we set up numerical experiments that mimic a tomographic study in Southern California exploiting ambient noise generated in the Pacific Ocean. Our results show that if the distribution of noise sources is deemed uniform instead of being numerically represented in the wave simulations, the misfit of the estimated models increases. In our experiments, the model misfit increase ranges between 5 and 21 per cent, depending on the heterogeneity of the noise source distribution. This indicates that assuming uniform noise sources introduces source-dependent model errors. Since the location of noise sources may change over time, these errors are also time-dependent. In order to mitigate these errors, it is necessary to account for the noise source distribution. The spatial extent to which noise sources must be considered depends on the propagation distance of the ambient noise wavefield. If only sources near the study area are considered, model errors may arise. [ABSTRACT FROM AUTHOR]

Large-scale ocean-bottom node (OBN) arrays of 1000s of multicomponent instruments deployed over 1000s of square kilometres have been used successfully for active-source seismic exploration activities including full waveform inversion (FWI) at exploration frequencies above about 2.0 Hz. The analysis of concurrently recorded lower-frequency ambient wavefield data, though, is only just beginning. A key long-term objective of such ambient wavefield analyses is to exploit the sensitivity of sub-2.0 Hz energy to build long-wavelength initial elastic models, thus facilitating FWI applications. However, doing so requires a more detailed understanding of ambient wavefield information recorded on the seafloor, the types, frequency structure and effective source distribution of recorded surface-wave modes, the near-seafloor elastic model structure, and the sensitivity of recorded wave modes to subsurface model structure. To this end, we present a wavefield analysis of low- and ultra-low-frequency ambient data (defined as <1.0 and <0.1 Hz, respectively) acquired on 2712 OBN stations in the Amendment Phase 1 survey covering 2750 km2 of the Gulf of Mexico. After applying ambient data conditioning prior to cross-correlation and seismic cross-coherence interferometry workflows, we demonstrate that the resulting virtual shot gather (VSG) volumes contain evidence for surface-wave and guided P -wave mode propagation between the 0.01 and 1.0 Hz that remains coherent to distances of at least 80 km. Evidence for surface-wave scattering from near-surface salt-body structure between 0.35 and 0.85 Hz is also present in a wide spatial distribution of VSG data. Finally, the interferometric VSG volumes clearly show waveform repetition at 20 s intervals in sub-0.3 Hz surface-wave arrivals, a periodicity consistent with the mean active-source shot interval. This suggests that the dominant contribution of surface-wave energy acquired in this VSG frequency band is likely predominantly related to air-gun excitation rather than by naturally occurring energy sources. Overall, these observations may have important consequences for the early stages of initial model building for elastic FWI analysis. [ABSTRACT FROM AUTHOR]

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]

The Northwest Seismic Network of Mexico (RESNOM) is operated by personnel from the Center for Scientific Research and Higher Education of Ensenada, Baja California (CICESE), which supervises station installation, improvement, and maintenance. We employed seismic noise and the Horizontal to Vertical Spectral Ratio (HVSR) method to determine, for each station, the following site condition parameters: the depth of the rock layer (Heng_bed), and the geotechnical parameter VS30, obtained from 1D shear wave velocity models. Other parameters as the fundamental frequency (f0) and the average amplitude at the fundamental frequency (A0) were also estimated. Our results show clear differences between the values obtained for the Mexicali Valley and the Peninsular ranges regions. The VS30 obtained for stations of the Mexicali Valley region falls in the range from 173 m/s to 535 m/s, while for the Peninsular Ranges region is between 213 m/s and 958 m/s. Regarding the Heng_bed parameter, the values are similar between both regions, from 23 m to 850 m for the Peninsular and from 42 m to 926 m for the Mexicali Valley. Additionally, from the VS30 values, we propose the site classification according to the U.S. National Earthquake Hazards Reduction Program (NEHRP).

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]

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.

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]