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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]

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]

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]

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]

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]

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 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]

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]

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]

The M w 7.8 earthquake in Turkey on 6 February 2023 was extraordinary for various reasons. It originated in depth of only 10 km, ruptured along a fault plane around 300 km long and the surface was covered by an extensive network of high-quality seismic instruments. The strong motions resulted in a vast number of tragic casualties and huge material losses in Turkey and Syria. However, abundant and proximate seismic observations of this event and numerous aftershocks give an opportunity to deepen the understanding of earthquake processes. In this study, we carried out an assessment of coseismic changes of seismic velocity using passive image interferometry. We used data from one strong-motion and twenty-four broad-band sensors. We observed coseismic drops of seismic velocity, which reached up to −1.79 per cent at a location directly at the ruptured East Anatolian Fault Zone. Along the M w 7.8 earthquake fault, we observe frequency dependence of the velocity changes. At frequencies above 0.5 Hz, the velocity drops seem to be higher at locations close to the ruptured faults than in the more distant areas. [ABSTRACT FROM AUTHOR]

Einstein Telescope (ET) is a proposed underground infrastructure in Europe to host future generations of gravitational-wave (GW) detectors. One of its design goals is to extend the observation band of terrestrial GW detectors from currently about 20 Hz down to 3 Hz. The coupling of a detector to its environment becomes stronger at lower frequencies, which makes it important to carefully analyse environmental disturbances at ET candidate sites. Seismic disturbances pose the greatest challenge since there are several important mechanisms for seismic vibrations to produce noise in ET, for example, through gravitational coupling, stray light, or through harmful constraints on the design of ET's control system. In this paper, we present an analysis of the time-variant properties of the seismic field at the Sardinia candidate site of ET connected to anthropogenic as well as natural phenomena. We find that temporal variations of source distributions and of the noise spectra generally follow predictable trends in the form of diurnal, weekly, or seasonal cycles. Specific seismic sources were identified such as road bridges, which produce observable disturbances underground. This information can be used to adapt a detector's seismic isolation and control system. [ABSTRACT FROM AUTHOR]

Ambient seismic interferometry of distributed acoustic sensing (DAS) data acquired on optical fibre arrays is an increasingly common approach for subsurface investigation. The fixed infrastructure and low maintenance costs of commodity telecommunications fibre also supports cost-effective DAS-based seismic monitoring solutions over extended periods of time—especially when using repurposed telecommunication fibre infrastructure in urban settings. To investigate whether ambient waveform data acquired on such an urban DAS array are sensitive to seasonal subsurface variations, we present a case study using 'semi-continuous' DAS time-series data with hourly 150 s sampling windows that were acquired over a 10-month interval in the central business district of Perth, Australia. We apply a cross-coherence analysis to transform pre-processed ambient waveform data into sliding-window weekly interferometric virtual shot gathers (VSGs). We then use these data volumes to compute time-lapse velocity–dispersion panels, which we input to a multichannel analysis of surface waves (MASWs) to generate depth-averaged S -wave velocity estimates of the top 30 m (⁠|$V_{S_{30}}$|). Our time-lapse analyses show that weekly stacked interferometric VSGs exhibit up to 5.8 per cent variations in observed surface wave traveltimes whereas the MASW inversion results capture up to 9.4 per cent variations in |$V_{S_{30}}$| estimates between the winter and spring months. We note that these observations are inversely correlated with time-averaged rainfall patterns in the Perth Metro region and are likely attributable to the associated seasonal variations in near-surface groundwater content. Overall, our analysis suggests that semi-continuous ambient seismic monitoring on urban DAS fibre arrays is a computational tractable acquisition strategy that records data volumes useful for monitoring the seasonal variability of groundwater resources beneath urban centres as well as potentially other time-lapse subsurface behaviour occurring over calendar time. [ABSTRACT FROM AUTHOR]

The Lonar impact crater in the Deccan Volcanic Province of India is an excellent analogue for impact-induced structures on the Moon and other terrestrial planets. We present a detailed architecture of the crater using a high-resolution 3-D seismic velocity image to a depth of 1.5 km through the inversion of high-frequency ambient noise data recorded over 20 broad-band seismographs operating around the crater. The ambient noise waveform is dominated by cultural noise in the 1–10 Hz band. The shear wave velocity (Vs) model is created from Rayleigh wave group velocity data with a horizontal resolution of 0.5–1 km in the period range of 0.1–1.2 s. A key feature of the model is a velocity reduction of 10–15 per cent below the crater compared to outside the ejecta zone. The low-velocity zone below the crater is nearly circular and extends to a depth of ∼500 m. This estimated crater's depth is consistent with global depth–diameter scaling relations for simple craters. The basement, with a Vs of more than 2.5 km s−1, lies beneath the Deccan basalt, which has a Vs of ∼2.4 km s−1. These results are consistent with laboratory-measured data from the Lonar crater and borehole data in the western Deccan trap. This study opens a new window for exploring impact craters and sub-basalt structures using high-frequency ambient noise tomography. [ABSTRACT FROM AUTHOR]

Most of water reservoirs are underground and therefore challenging to monitor. This is particularly the case of karst aquifers which knowledge is mostly based on sparse spatial and temporal observations. In this study, we propose a new approach, based on a supervised machine learning algorithm, the Random Forests, and continuous seismic noise records, that allows the prediction of the underground river water height. The study site is a karst aquifer in the Jura Mountains (France). An underground river is accessible through an artificial shaft and is instrumented by a hydrological probe. The seismic noise generated by the river is recorded by two broadband seismometers, located underground (20 m depth) and at the surface. The algorithm succeeds in predicting water height thanks to signal energy features. Even weak river-induced noise such as recorded at the surface can be detected and used by the algorithm. Its efficiency, expressed by the Nash–Sutcliffe criterion, is above 95 per cent and 53 per cent for data from the underground and surface seismic stations, respectively. [ABSTRACT FROM AUTHOR]

We present a method for estimating seismic ambient noise sources by acoustic full waveform inversion (FWI) of interstation cross-correlations. The method is valid at local scales for laterally heterogeneous media, and ambient noise sources confined to the Earth's surface. Synthetic tests performed using an actual field array geometry, are used to illustrate three unique aspects of our work. First: the method is able to recover noise sources of arbitrary spatial distribution, both within and outside the receiver array, with high fidelity. This holds true for complex velocity models and does not require a good initial guess for inversion, thereby addressing an outstanding issue in the existing research literature. Second: we analyse the extent of biases in source inversion that arise due to inaccurate velocity models. Our findings indicate that source inversion using simplified (e.g. homogeneous) velocity models may work reliably when lateral variations in velocity structure are limited to 5 or 10 per cent in magnitude, but is vitiated by strong variations of 20 per cent or higher, wherein the effect of strong scattering and/or phase distortions become significant. Finally, our technique is implemented without the adjoint method, which is usually inextricably linked to FWI. Inversions are performed using source kernels computed for each receiver pair, and this approach is computationally tractable for real-world problems with small aperture seismic arrays. [ABSTRACT FROM AUTHOR]

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.