Geophysical Journal International

SummaryAn 18-layer, U-shaped convolutional neural network (CNN) was trained to predict Vs models and identify near-surface void locations. To enhance seismic inversion accuracy for real world applications, the model is trained on synthetic datasets augmented with field noise. While models trained on noise-augmented data showed poorer performance on synthetic testing datasets, they achieved lower root mean square error values and the best results on field data. The velocity model resulting from full-waveform inversion based on noise-augmented model accurately detected a void-like low velocity zone near the known void location. This approach shows that training with field-noise-augmented data allows machine learning models to generalize better to real-world conditions, increasing their reliability for velocity inversion in noisy environments. The results highlight the strong potential of this strategy, particularly if a diverse range of real noise samples is incorporated during training.

SummaryCoseismic slip models for large (Mw > 7) strike-slip earthquakes present a variety of shallow slip deficit (SSD). Accurate estimate of SSD is difficult, and it has been suggested that SSD are to some degree associated with fault-zone characteristics, incompleteness of data coverage as well as simplified model assumptions. Furthermore, SSD can also be sensitive to the amount of model smoothness adopted. Since phase gradient are sensitive to the missing shallow slip from our simulated data, we performed a synthetic test and presented a case study of the 2019 Ridgecrest earthquake sequence to validate that phase gradient from radar interferometry could help reveal the actual SSD for kinematic slip models even without enough near-fault observation. Our results indicate that even in the presence of a greater degree of observational gaps, the phase gradient can still nearly substitute for near-fault observations in constraining the shallow slip. Lastly, we provide a preferred coseismic slip model constrained by all available observations including phase gradient, but with 4-km data gap near the fault trace. This model results in ∼35% SSD for the Ridgecrest earthquakes, matching previous estimates that incorporate near-field data. Considering the phase gradient approach is a straightforward mathematical operation, this approach may be applicable to other types of earthquakes. Notably, due to the smaller amplitude and lower signal-to-noise ratio for the phase gradient data, one needs to carefully balance the trade-offs among weights of different datasets and model smoothness.

SummaryElectrokinetic signals, such as surface self-potential (SP) variations, offer a unique window into coupled fluid–electrical processes in the Earth’s crust, yet their quantitative interpretation remains challenging in complex geological settings. In this study, we develop an electrokinetic modeling framework by extending the modified Luco-Apsel-Chen generalized reflection and transmission method to simulate SP responses due to a fluid-injection source in layered geological media. After simulating electric signals, we apply location-specific amplification factors—derived from prior numerical investigations—that account for the effects of steel well casings. This post-processing step enables rigorous comparison with field observations. Using the well-documented deep fluid injection experiment at the Soultz-sous-Forêts geothermal site, we calibrate simulated pore pressure against downhole measurements to derive a realistic source function for direct comparison between modeled and observed SP signals. The model reproduces key spatiotemporal features of the mV-scale SP anomalies and, importantly, captures the observed slower decay of surface SP signals after shut-in despite the rapid decrease in deep pore pressure. Previous field-scale studies have qualitatively attributed this phenomenon to sustained ionic transport; here, our simulation results provide a quantitative demonstration that this process—driven by continued pore-fluid movement—is responsible for the slower SP decay, a mechanism not captured in earlier electrokinetic simulations. These findings provide new mechanistic insight into SP generation in stratified media, demonstrate the essential role of casing effects in field-scale interpretation, and establish a transferable framework for monitoring subsurface fluid flow in geothermal, hydrocarbon, and groundwater systems.

SummaryTsunami warning systems implemented worldwide rely on the fast characterization of earthquake sources, in particular on the estimation of the moment magnitude Mw. Reliable estimation of Mw typically takes 10 to 20 minutes for large events based on conventional seismic signals. A promising alternative is the use of Prompt Elasto-Gravity Signals (PEGS), which are very low-amplitude gravitational perturbations induced by earthquakes that travel at the speed of light and can be recorded by broadband seismometers at time scales of a few minutes after origin time. We propose here a first implementation of real-time PEGS analysis to enhance the Peruvian earthquake monitoring system by enabling rapid magnitude estimation for large and potentially tsunamigenic earthquakes. We train a graph neural network to recognize the space-time structure of PEGS over a large international set of broadband seismic stations, even when their amplitudes are smaller than the noise level, and to rapidly estimate the magnitude and location of the source. Our results indicate that the PEGS-based system can estimate the magnitude of Mw ≥ 8.2 earthquakes, within 5 minutes after the event’s initiation, with sufficient accuracy for tsunami warning purposes. Simulated real-time tests confirm the viability of the PEGS-based approach for operational early warning, providing robust source estimations of large magnitude events to the Peruvian earthquake monitoring system that are valuable for tsunami warning.

SummaryMagnetotelluric (MT) data inversion seeks to recover resistivity models of the subsurface. Solving the inversion problem is a non-trivial task, as multiple plausible solutions can be recovered due to the non-linearity of the problem. To reduce this non-linearity, we propose a data-driven approach where a 1D cumulative resistance model is estimated from MT data via a direct data transformation. We define the cumulative representation of layered models as the weighted sum of layer thickness divided by resistivity from surface to any depth level, which is the cumulative conductance. Its inverse, cumulative resistance, is directly related to the real part of the impedance computed from MT data. We train a neural network to transform the MT impedance into a resistance model. The corresponding 1D resistivity model is obtained without a priori information. We validate our approach using synthetic and real data, opening the discussion for future developments of this new perspective.

SummaryIn this work, we address the characterization of porosity and water saturation in a synthetic model of a shallow alluvial subsurface using frequency electromagnetic and seismic data. The inversion method employs a Gauss-Newton scheme, where the Jacobian of the merged seismic and electromagnetic data is formulated with respect to the spatially heterogeneous petrophysical parameters. This is made possible by introducing realistic petrophysical relationships, which significantly reduce the number of unknowns in the inverse problem and incorporate a strong prior correlation between the information contained in both data types regarding the subsurface composition. The results obtained show that this Simultaneous Joint Petrophysical Inversion (SiJPI) produces reconstructions with clear improvements compared to Independent Petrophysical Inversion (IPI). Indeed, it greatly enhances the spatial resolution of subsurface mapping, as well as the quantitative estimation of porosity and saturation.

SummaryThe Xiaojiang fault system (XJFS) is located in the southeastern margin of the Tibetan Plateau, which has been considered as an ideal site to explore the traces and effects of past tectonic activity. In this study, we obtain a high-resolution P-wave velocity and azimuthal anisotropy model of the upper crust beneath the XJFS, utilizing the 2D Pg wave tomography method including both station and event depth corrections. The upper crust displays obvious heterogeneity of both azimuthal anisotropy and P-wave velocity underlying the XJFS. The large azimuthal anisotropy beneath the XJFS, especially the regions where several faults interact, suggests the cracks are widely distributed. Generally, the upper crust is featured by several high-velocity bodies separated by low-velocity anomalies. The high-velocity bodies are speculated to be related to the remnant magmatic rocks of the Emeishan large igneous province. The low-velocity anomalies are interpreted to represent fault damage zones which could be attributed to the strike-slip faulting/shearing along the faults and upwelling of deeply-sourced partial melts and fluids. The present tectonic activity in the XJFS is characterized by rigid block extrusion along strike-slip faults in the upper crust, which is consistent with the rigid block extrusion model. We further propose a tectonic model to display the evolution of the upper crust beneath the XJFS, in which the faults and fluids activity plays an essential role.

AbstractGeophysical measurements such as induced polarization (IP) are invaluable for understanding the physical properties of rocks, including pore structure, hydraulic properties, and mineral content. However, collecting reliable IP measurements from low-permeability rocks poses substantial challenges due to the difficulty of saturating their tight pore spaces. Additionally, IP measurements on rocks that are not cored to fit conventional sample holders, or are irregularly shaped, are particularly difficult to obtain. In this work, we address these challenges through (1) the use of reliable saturation procedures developed for low-permeability samples, and (2) a molding procedure designed to overcome the difficulties of measuring IP on irregularly shaped or broken rock cores. Core-scale gravimetric porosity measurements closely match values obtained from destructive mercury intrusion porosimetry (MICP) on rock fragments, confirming the effectiveness of the saturation procedure. Direct comparisons of IP measurements between molded and unmolded cores demonstrate that the molding process does not significantly alter the intrinsic electrical response of the samples. Fully saturated mudstones exhibit strong statistically significant relationships between the mean relaxation time (τmean) and permeability (k), and between effective porosity (1/formation factor, F) and interconnected porosity (ϕ) (Archie’s law). Conversely, partial saturation due to ineffective saturation methods introduces substantial scatter to these petrophysical correlations. Overall, these findings underscore the potential of these methods to enhance the reliability and accuracy of SIP measurements on challenging rock samples.

SummaryOn January 18, 2021, a blind mid-crustal Mw ∼6.4 earthquake occurred near San Juan, Argentina. The observation of associated ground deformation with single interferograms is obscured by strong tropospheric signals. We apply appropriate corrections to the data and reconstruct the deformation field associated to the event through InSAR time series approach. We show it is possible to retrieve this signal to invert the fault parameters. The observed ground deformation is consistent with a high angle NW-dipping fault plane at a centroid depth of ∼19 km. The geometry of this fault supports the reactivation of pre-existing structures within the Cuyania Terrane, suggesting a direct structural connection and strain transfer to the actively deforming, east-vergent Precordillera front. We analyze our findings to deduce a static friction coefficient ≤0.3 for mid-crustal faults of the region.

SummaryWe refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

SummaryMetallic infrastructure, such as steel sheet situated within landfills, poses significant challenges to accurate tracking of leachate using induced polarization (IP) methods. The application of IP method is efficient to delineate leakage; however, the presence of metallic structures can cause an interference on the survey and generate high-chargeability anomalies as observed in field survey. To comprehensively validate the interference caused by steel sheets, both numerical and empirical field tests were conducted. As expected, both results demonstrate that interference diminishes as the distance between survey line and metallic structure increases. Additionally, at consistent intervals, the chargeability values inverted using integral chargeability (IC) exhibit a monotonic increase with depth. Moreover, the interference induced by metallic structures is also affected by the controlling factors (i.e. depth, width and thickness) of the structure alongside the intrinsic resistivity and chargeability. Strategic utilization of the size, chargeability, and spatial positioning of metallic structures relative to survey lines can significantly enhance background polarization. This approach offers a promising framework for improving the spatial resolution of subsurface targets exhibiting low polarization effects. The optimization of survey line placement, which must consider the dimensions and electrical properties of metallic structures such as steel sheets, is essential for accurately characterizing landfill leachate using the IP method.

SummaryNorthern Europe experiences vertical land motion and sea level changes that deviate from the average as a consequence of past changes in ice sheet cover in Fennoscandia and the British Isles. The process, called Glacial Isostatic Adjustment (GIA), is controlled by the subsurface structure. Numerical models of GIA can be compared to observations of uplift or past sea level changes to constrain the subsurface structure, and such models can also be used to correct present-day sea level observations to reveal sea level changes due to climate change. GIA models for northern Europe usually adopt a homogeneous upper mantle viscosity even though seismic studies indicate contrasting elastic lithosphere thickness and upper mantle structure between Northwestern Europe and Eastern Europe. This raises the question whether the effect of lateral variations in structure (3D viscosity) can be detected in observations of GIA and whether including such variations can improve GIA model predictions. In this study we compare model output from a finite element GIA model with 3D viscosity to observations of paleo sea level and current vertical land motion. We use two different methods to derive 3D viscosities, based on seismic velocity anomalies and upper mantle temperature estimates. We use three different reconstructions of the Eurasian ice sheet, one based on an inversion using a 1D model, and two others based on glacial geology and modelling. When we use these two reconstructions, we find that the data are fit better using 3D viscosity models. Models with two separate 1D viscosities for Fennoscandia and for the British Isles cannot replicate a 3D model because a 3D model redistributes GIA-induced stresses differently from a combination of models with separate 2D viscosities. The fit to data across Fennoscandia is improved when, as indicated by seismic models, the upper mantle viscosity is higher than for the rest of Northern Europe. The best fit is obtained with a model with dry olivine rheology, in agreement with other evidence from Fennoscandia.

SummaryIn both onshore and offshore seismic exploration, seismic source localization plays a crucial role in ensuring operational safety and environmental protection. With the continuous advancement of the Marchenko method in the fields of seismic migration and internal multiple elimination, this paper investigates a seismic source localization method based on the Marchenko method, aiming to further extend application domain of this method. The key to this method lies in the data reconstruction based on convolution operations. The conventional Marchenko method is then applied to obtain a seismic profile, which includes the location of the seismic source. In the experiments, this study first uses an anticline model to simulate seismic source localization in onshore seismic exploration. The results show that the proposed method can accurately estimate both the distance to the seismic source and its depth. Furthermore, in large-scale marine model experiments, the method is also able to reliably determine the distance between the seismic source and the observation stations.

SummaryFor the interpretation of Spectral Induced Polarization spectra, the determination of the Relaxation Time Distributions (RTD) can be useful, for instance to extract the grain size distribution. However, this is an ill-posed problem, and retrieving the RTD often requires regularization during the inversion process. In this note, we use Bézier curves and simulated annealing to determine the RTD. The procedure that does not require any regularization nor smoothing, by reducing the number of parameters thanks to Bézier curves which are intrinsically continuous and infinitely derivable. We successfully applied our methodology to three examples (Cole-Cole model, Davidson-Cole model, and an experimental spectrum), demonstrating its interest and efficiency.

SummaryThe extension of direct current resistivity methods to induced polarization methods has enriched the tools available for subsurface exploration. This enrichment involves an increase in the number of parameters used in the models, as well as addressing different physical phenomena than those observed with direct current. Accounting for non-linearities, if they exist, can further enhance the sophistication of our models. Non-linearities are often observed, particularly in laboratory experiments. However, we question their origin, and the experiment described here suggests that the non-linearities observed under typical experimental conditions may be artifacts related to the electrodes, rather than reflecting the actual response of the subsurface. Indeed, we first replaced the polarizable injection electrodes with non-polarizable electrodes. The non-linearities observed due to the presence of harmonics were significantly reduced. Then, we replaced the voltage control with a current control, which completely eliminated the non-linearities still present.We know that it is impossible to prove the non-existence of a phenomenon that does not exist. This fundamental epistemological principle (as pointed out by Russell and Popper) means that we are not claiming that nonlinearity does not exist. We are simply describing an experiment that can raise doubts about its existence.

SummaryWe present and validate an efficient GPU-accelerated solver for seismic wave propagation in three-dimensional elastic media. The solver achieves up to a 372× speedup relative to a CPU implementation and supports forward simulations on grids ranging from 100 million to 1 billion cells. It is based on a velocity-stress, first-order formulation of the elastodynamic wave equation and supports kilometer-scale models with layered isotropic and anisotropic structure. We validate the solver by comparing synthetic seismograms to analytical solutions from a propagator matrix method in axisymmetric media. Simulations include moment-tensor sources for a 2017 nuclear explosion and collapse in North Korea, and a magnitude ∼4 earthquake near Linthal, Switzerland (6 March 2017). Anisotropic effects for the Swiss event are modeled using rotated orthorhombic stiffness tensors derived from laboratory measurements of gneiss. Projection onto orthorhombic symmetry enables solver compatibility. We find that anisotropy changes waveform polarity, amplitude, and phase at near-source stations. Unscaled laboratory values produce polarity reversals, while velocity-rescaled tensors correct them. These results demonstrate the impact of anisotropy on waveform modeling and indicate that simplified 1D isotropic models may be insufficient for complex crustal settings. We review how structural effects, including anisotropy and 3D heterogeneity, contribute to transverse-component energy in the 2017 DPRK explosion and discuss implications for seismic source classification.

AbstractTransient stress changes from seismic waves of distant earthquakes can promote local fault slip, a phenomenon referred to as remote dynamic triggering. This study examines the remote triggering susceptibility of faults in the Lower Rhine Embayment (LRE) in the Weisweiler region, Germany, a proposed site for geothermal energy production. Assessment of remote triggering can guide industrial operations to assess seismic hazard and mitigate risks associated with fault reactivation caused by small stress perturbations. We select a set of 23 candidate mainshocks from global earthquake catalogs that produce peak ground velocities (PGVs) that exceed 0.02 cm/s in the LRE. The magnitude of these mainshocks ranges from 5.4 to 9.1, epicentral distances range from 50 to 12,300 km, and back azimuth ranges from 16○ to 350○ with a maximum azimuthal gap of 91○. The candidate mainshocks generated PGVs locally from 0.02 to 0.28 cm/s (compared to typical threshold values ranging from 0.02 to 6 cm/s), corresponding to dynamic stress (σpd) values of 1.4 to 26 kPa. We use P-statistics and waveform data from local seismic stations to identify seismicity rate changes and uncatalogued earthquakes that were potentially triggered by the passing mainshock waves. The analysis reveals a statistically significant increase in seismicity rates following four mainshocks: the 1992 Mw5.4 Roermond, Netherlands, 2021 Mw8.2 Chignik, Alsaka, USA, 2023 Mw7.6 Kahramanmaraş, Republic of Türkiye, and 2025 Mw8.8 Kamchatka, Russia earthquakes. The 1992 Roermond mainshock triggered earthquakes within 50 km of its epicenter that were clustered between the Feldbiss and Sandgewand faults. The same area experienced a triggered earthquake sequence following the Chignik mainshock, suggesting that future detailed monitoring in this area may be warranted. The Roermond aftershock distribution can be divided two groups of events, including 61 that occur on the fault and in the near-field, which can be explained by static-stress increase and fluid diffusion. Another 32 remote aftershocks occurred that are consistent with secondary triggering promoted by aseismic slip propagation. The alignment of triggering mainshock back azimuths with the dominant strike direction of regional faults suggests that the orientation of incoming seismic waves is an important factor influencing susceptibility. Despite evidence of triggering, the majority of mainshocks (19 out of 23) were not followed by detectable seismicity-rate changes in the LRE, highlighting the complexity of conditions that lead to remote dynamic triggering. The study area does not respond to a triggering stress threshold, suggesting that non-linear, or a combination of linear and non-linear effects, dominate possible triggering mechanisms. Although the LRE does not respond to a clear triggering threshold, this study demonstrates that peak dynamic stress perturbations of approximately 1.4 kPa or greater can still trigger earthquakes. But, susceptibility is modulated by additional factors such as fault orientation, earthquake fault-zone properties, their state in the seismic cycle, and pre-existing stress state.

AbstractPhysics-informed neural networks (PINNs) face significant challenges in modeling multi-frequency wavefields in complex velocity models due to their slow convergence, difficulty in representing high-frequency details, and lack of generalization to varying frequencies and velocity scenarios. To address these issues, we propose Meta-LRPINN, a novel framework that combines low-rank parameterization using singular value decomposition (SVD) with meta-learning and frequency embedding. Specifically, we decompose the weights of PINN’s hidden layers using SVD and introduce an innovative frequency embedding hypernetwork (FEH) that links input frequencies with the singular values, enabling efficient and frequency-adaptive wavefield representation. Meta-learning is employed to provide robust initialization, improving optimization stability and reducing training time. Additionally, we implement adaptive rank reduction and FEH pruning during the meta-testing phase to further enhance efficiency. Numerical experiments, which are presented on multi-frequency scattered wavefields for different velocity models, demonstrate that Meta-LRPINN achieves much faster convergence speed and much higher accuracy compared to baseline methods such as Meta-PINN and vanilla PINN. Also, the proposed framework shows strong generalization to out-of-distribution frequencies while maintaining computational efficiency. These results highlight the potential of our Meta-LRPINN for scalable and adaptable seismic wavefield modeling.

AbstractP-wave reflections from the 410- and 660-km mantle discontinuities are visible in stacks of ambient noise cross-correlation functions of USArray stations spanning the contiguous United States. The reflections are most visible on the vertical components at frequencies between 0.1 and 0.3 Hz during low-noise periods, which generally occur during the summer months in the northern hemisphere. Common reflection point stacking can be used to resolve apparent lateral differences in discontinuity structure across the continent and suggests the possible existence of sporadic reflectors at other depths. Visibility of the 660-km reflector is correlated with faster P-wave velocities at similar depth in a tomographic model for North America. However, the lack of clear agreement between these P-wave ambient noise features and prior mantle-transition-zone imaging studies using other methods suggests caution should be applied in their interpretation. Ambient noise sources from the southern oceans may not be distributed uniformly enough for cross-correlation stacks to provide unbiased estimates of the true station-to-station P-wave Green’s functions. However, the clear presence of 410- and 660-km reflections in the ambient noise data suggests that it should be possible to unravel the complexities associated with varying noise source locations to produce reliable P-wave reflection profiles, providing new insights into mantle structure under the contiguous United States.

AbstractSeismic wave propagation in poro-viscoelastic anisotropic media is of practical importance for exploration geophysics and global seismology. Existing theories generally utilize homogeneous plane wave theory, which considers only velocity anisotropy but neglects attenuation anisotropy and wave inhomogeneity arising from attenuation. As a result, it poses significant challenges to accurately analyze seismic wave dispersion and attenuation in poro-viscoelastic anisotropic media. In this paper, we investigate the propagation of inhomogeneous plane waves in poro-viscoelastic media, explicitly incorporating both velocity and attenuation anisotropy. Starting from classical Biot theory, we present a fractional differential equation describing wave propagation in attenuative anisotropic porous media that accommodates arbitrary anisotropy in both velocity and attenuation. Then, instead of relying on the traditional complex wave vector approach, we derive new Christoffel and energy balance equations for general inhomogeneous waves by employing an alternative formulation based on the complex slowness vector. The phase velocities and complex slownesses of inhomogeneous fast and slow quasi-compressional (qP1 and qP2) and quasi-shear (qS1 and qS2) waves are determined by solving an eighth-degree algebraic equation. By invoking the derived energy balance equation along with the computed complex slowness, we present explicit and concise expressions for energy velocities. Additionally, we analyze dissipation factors defined by two alternative measures: the ratio of average dissipated energy density to either average strain energy density or average stored energy density. We clarify and discuss the implications of these definitional differences in the context of general poro-viscoelastic anisotropic media. Finally, our expressions are reduced to give their counterparts of the homogeneous waves as a special case, and the reduced forms are identical to those presented by the existing poro-viscoelastic theory. Several examples are provided to illustrate the propagation characteristics of inhomogeneous plane waves in unbounded attenuative vertical transversely isotropic porous media.