Geophysical Journal International

SUMMARYNatural faults commonly contain fluid-saturated gouge layers, in which fluid injection can modify pore pressure and porosity evolution, thereby affecting slip stability and induced seismicity. Here we develop a spring-slider model based on rate-and-state friction (RSF) to investigate fault slip evolution under dry, fluid-saturated, and fluid injection conditions. Our model incorporates gouge dilatancy/compaction and fluid-related pore pressure effects. Our results show pronounced differences in the onset time of the first dynamic instability and the peak slip rate among these cases. Compared to the dry case, fluid saturation without injection delays instability and slightly lowers the peak slip rate, whereas rapid injection-induced pressurization triggers earlier dynamic slip and higher peak slip rates. Without injection, increasing the dilatancy coefficient systematically delays instability. Under rapid injection, however, the onset time becomes much less sensitive to dilatancy, indicating a gradual transition from a dilatancy-influenced to an injection-dominated nucleation regime as the injection-dilatancy competition number increases. Linear stability analysis further suggests that fault stability can be characterized by a generalized critical stiffness that combines the effects of effective normal stress, pressurization rate, and dilatancy/compaction feedback. These results indicate that fluid effects on fault rupture arise from the competition between stabilizing dilatancy hardening and destabilizing time-dependent pressurization, highlighting that injection-induced seismicity can be understood as an injection-rate-driven stability problem. Our findings provide a physical framework for understanding the transition from dilatancy-sensitive to injection-controlled fault slip within the explored net dilatant regime under different fluid environments.

SummaryThis study leverages a new, improved and densified GNSS velocity field of the western Aegean region to quantify slip rates, strain localisation, and interseismic loading within the upper plate of the Hellenic subduction zone, including the deformation systems associated with the subduction–collision transition around Cephalonia, the Hellenic forearc extension, and the southwestern termination of the North Anatolian Fault system. We examine several active tectonic domains, comprising four extensional regions (Corinth–Patras Rift, Evia Gulf, Argolic Gulf, southwestern Peloponnese) and three strike-slip systems (Cephalonia Transform Fault, Katouna–Stamna Fault System, Movri Fault Zone). Across the Corinth Rift, NS extension increases westward from ≈ 7 to ≈ 15 mm.yr$^{\hspace{1.0pt}\text{--}1}$, of which up to ≈ 6 mm.yr$^{\hspace{1.0pt}\text{--}1}$ is accommodated offshore. Velocity profiles indicate combined elastic loading and aseismic creep on a limited number of crustal-scale faults. The Evia–Boeotia sector undergoes NS extension at up to 8 mm.yr$^{\hspace{1.0pt}\text{--}1}$, but deformation is distributed across multiple structures, each accommodating creep or elastic loading at rates <2 mm.yr$^{\hspace{1.0pt}\text{--}1}$. In the southern Peloponnese, diffuse EW extension of up to 6 mm.yr$^{\hspace{1.0pt}\text{--}1}$ occurs alongside 1–2 mm.yr$^{\hspace{1.0pt}\text{--}1}$ of NS extension in the central Peloponnese. A portion of this EW deformation may be accumulating interseismically as elastic strain on prominent structures, such as the Sparti and East Messenia faults. No measurable strain is detected across the Argolic Gulf, suggesting substantially lower present-day loading rates on the Astros Fault than previously inferred. Strike-slip systems display contrasting behaviours. The Katouna segment accommodates transtensional left-lateral creep of ≈ 13 mm.yr$^{\hspace{1.0pt}\text{--}1}$ within a zone <6 km wide, whereas slip decreases to ≈ 8 mm.yr$^{\hspace{1.0pt}\text{--}1}$ on the Stamna segment, consistent with strain transfer through the Trichonida pull-apart basin and the Nafpaktia diffuse shear zone. In contrast, the Movri Fault appears locked down to at least 10 km depth, accumulating ≈ 4 mm.yr$^{\hspace{1.0pt}\text{--}1}$ of right-lateral strain. Onshore velocities near the Cephalonia Transform Fault indicate an onshore half-rate of elastic loading of ≈ 8 mm.yr$^{\hspace{1.0pt}\text{--}1}$, suggesting that the full transpressional right-lateral motion (≈ 16 mm.yr$^{\hspace{1.0pt}\text{--}1}$) accumulates interseismically, highlighting considerable seismic hazard potential.

SummaryDistributed Acoustic Sensing (DAS) data often contain various types of noise, including random noise, coherent noise (e.g., coupling or linear noise), and common mode noise, which significantly degrade seismic signal quality. Conventional denoising methods struggle to effectively suppress diverse noise components while preserving important seismic signals. To address this issue, we propose a denoising self-supervised cascade network (DAS-DSCnet), a multi-stage neural network designed to progressively denoise DAS data without requiring external labels or synthetic training data generation. The network consists of three stages: Stage 1 targets random noise using a Noise2Noise-based approach; Stage 2 suppresses dataset-specific coherent noise using a denoising convolutional neural network (DnCNN)-based network trained with internally extracted noise patches; and Stage 3 predicts and removes common mode noise through trace shuffling and a Noise2Noise-based model. Training data for each stage are generated directly from the input DAS data by exploiting the data’s inherent characteristics, enabling efficient learning that reflects field-specific noise features. The model was evaluated using two distinct field DAS datasets with different noise patterns. The results demonstrate that DAS-DSCnet achieves superior noise suppression compared to conventional approaches, enhancing signal continuity while minimizing leakage. The denoising performance remains stable across different stacking configurations and hyperparameters, confirming the model’s robustness. Therefore, DAS-DSCnet offers a scalable and practical framework for improving seismic data quality in DAS applications, demonstrating the potential for fully automated, data-driven denoising in large-scale seismic monitoring.

SUMMARYWe present a comprehensive dataset of 920 coordinates and 509 velocities for geodetic points in central Greece and the Peloponnese, an area characterised by intense tectonic deformation. The points, with observation periods within the 1990–2024 range, are organised into three categories: permanent stations, triangulation pillars, and markers. The latter two categories are subdivided according to whether or not they feature self-centring. Most of the triangulation pillars belong to the Greek national network originally surveyed in the 1960s–70s. The GNSS data were processed using the GIPSY 6.4 software. To assess the secular velocities, we corrected for co-seismic and post-seismic displacements using earthquake parameters constrained by the time series of the permanent stations. Self-centring systems improve precision, reducing the average horizontal coordinate residual variability from 6.15 to 4.45 mm. The velocity uncertainties stabilise below 0.15 mm yr−1 when the time series exceed twenty years. Points with self-centring achieve 0.2 mm yr−1 accuracy after twelve years of data, compared to twenty years for those without self-centring. After twenty-five years, campaign points observed eight to ten times match the precision of permanent stations. The velocities at the campaign points further validate the HELVEL model previously developed using permanent stations only. We calculate a seven-parameter transformation from the original coordinates of 424 triangulation pillars to their GNSS-based ITRF2020 coordinates at epoch 2020.0. The lowest mean scatter after the transformation is 0.134 m when 1965 is used as the mean epoch for the triangulation data. We then apply this transformation to all 9,729 pillars of the study area. At the 424 resurveyed pillars, the GNSS ellipsoidal heights agree with the sum of the levelled heights and the official HG2023 geoid heights to within 0.184 m root-mean-square. Our dataset is entirely referenced to ITRF2020 at epoch 2020.0, which enables interoperability with previous and future geodetic studies. Dense campaign point arrays are critical for resolving the strain distribution at the scale of individual active faults, beyond the reach of arrays of permanent stations alone.

AbstractMantle viscosity remains one of the largest outstanding uncertainties in global geodynamics. Time-dependent mantle circulation models that assimilate tectonic histories (MCMs) provide a way to test viscosity by assessing their present-day predictions against observations. This approach allows for the influence of viscosity on mantle density structure to be accounted for, which is not possible using instantaneous modelling approaches. Here we present the first systematic test of lower mantle viscosity against dynamic topography, the geoid, and seismic heterogeneity using high-resolution MCMs. Model density structure depends strongly on the assumed viscosity profile, which in turn controls the fit to seismic heterogeneity. The fit to dynamic topography and the geoid is further influenced by the instantaneous transmission of stresses to the surface. These two effects can either reinforce or counteract each other at different depths, which must be considered when attempting to match dynamic topography and geoid amplitudes. MCMs typically overestimate dynamic topography amplitudes. We find that it is possible to reduce these amplitudes by lowering viscosity in the upper lower mantle (≈660-2000 km), though this comes at the expense of a reduced fit to the geoid and/or seismic heterogeneity. Our preferred viscosity profile provides an excellent fit to observed geoid amplitudes and the seismic heterogeneity of S40RTS. We also tested an alternate tectonic reconstruction with tomography-based refinements around the Pacific which improved the correlation with the observed geoid by ≈20%. Our results show that MCMs can now reach a level of resolution and realism sufficient for comparison to multiple independent data sets, opening the door to systematic assessment of uncertain parameters which govern convection in the mantle.

SUMMARYThe excitation and propagation of multiple wave types, including seismic waves, ocean acoustic waves, and tsunamis triggered by earthquakes within the oceanic wavefield, constitute a problem of substantial scientific and practical challenge. This phenomenon involves complex interactions of waves within a fluid-solid coupled system, which is critical for both fundamental geophysical understanding and enhancing hazard assessment. While several numerical methods have been developed to simulate the full wavefield, few studies have systematically explored the crucial influence of complex seafloor topography on coupled wave dynamics. This study introduces a novel earthquake-tsunami coupling simulation method within a 2-D spectral-element method (SEM) framework, leveraging its flexibility to handle complex geometries and accuracy for long-range wave propagation. To validate the accuracy of the simulated seismic waves, ocean acoustic waves, and tsunamis, we quantitatively evaluate the permanent seafloor displacement, yielding a high correlation coefficient of 0.997 and a negligible error of 5 × 10−3 compared with the analytical solution. The mean relative error of the calculated tsunami phase velocities of the proposed method with those from the propagator matrix method is only 0.12%. Furthermore, we establish two distinct numerical models—one incorporating irregular bathymetry and another with an idealized flat bathymetry—to systematically investigate the effects of bathymetry on the oceanic wavefield. Our results demonstrate that the irregular bathymetry significantly influences the propagation characteristics of both seismic waves and tsunamis, altering wave amplitudes, travel times, and spatial patterns. We further decompose the contributions of seawater and seafloor geometry, highlighting their respective roles in shaping the overall wavefield. Additionally, we examine the influence of varying earthquake source locations on wave propagation paths, emphasizing the importance of accurately modelling bathymetry for offshore seismic events. Overall, our proposed 2-D earthquake-tsunami coupling simulation framework provides a powerful tool for comprehensively understanding the oceanic wavefield under gravity and offers significant potential for improved earthquake and tsunami hazard assessment, particularly when combined with seismological and oceanographic observations.

AbstractSeismicity rates in west Texas and southeast New Mexico have increased over the last nine years and are in large part driven by subsurface wastewater disposal associated with oil-gas operations. Injection-induced seismicity is often explained as the result of fault weakening from fluid pressurization. However, fluid injection also induces poroelastic stresses from fluid-rock coupling, which in some cases are larger than the perturbations induced from pore pressure alone. In this work, we model in-zone changes in pore pressure and poroelastic stressing along four major fault zones that have hosted moderate-large ML 4 – 5 earthquakes in the Delaware Basin (DB) of west Texas. We leverage high-quality downhole pore-pressure measurements to constrain the in-situ hydraulic diffusivity and storativity. The data show that the deep injection interval has a storativity of ∼ 5×10−5 and a diffusivity between 23-65 m2/s, suggesting that this interval can pressurize rapidly and transmit fluid pressure efficiently. We view these as local hydraulic properties and use an ensemble modeling approach that accounts for a large range in diffusivities and storativities to model changes in Coulomb Failure Stresses (CFS). Our 2D fully coupled poroelastic models show that deep subsurface fluid injection can induce between ∼1-1000 kPa in CFS along basement rooted faults that penetrate the injection interval, with the largest values occurring in models that use the hydraulic properties inferred from our in-situ measurements. However, the induced changes in CFS are much smaller (∼ 20-30 kPa) when averaging over a large range in hydraulic properties. Irrespective of the model parameterization, the in-zone perturbations in CFS are dominated by changes in pore pressure, even at distances as far as 20-30 km from the nearest injection source. Our results highlight the importance of obtaining in-situ poromechanical measurements and indicate that such high-resolution measurements are critical to understanding subsurface stressing associated with fluid injection.

AbstractThe northern Adriatic Sea provides an exceptional setting for investigating tidal processes because of its shallow bathymetry, elongated basin geometry, and semi-enclosed configuration. These characteristics produce some of the largest tidal amplitudes in the Mediterranean and favor the amplification of both diurnal and semidiurnal constituents, leading to complex sea-level variability and episodic extreme events such as high stands along the coastal cities. We analyze tidal dynamics and ocean tidal loading (OTL) in the northern Adriatic using a multi-technique approach that combines tide gauge (TG) observations, interferometric reflectometry (GNSS-IR) sea-level retrievals, and GNSS precise point positioning (PPP) solutions describing crustal deformation. Tide gauge records confirm the progressive increase of semidiurnal tidal energy toward the northern end of the basin, with the M2 and S2 constituents dominating over the diurnal band. These observations broadly agree with the FES2014b ocean tide model, although local amplitude and phase deviations are observed in shallow and geometrically complex coastal environments. Sea-level time series derived from GNSS-IR at several coastal sites show a high degree of agreement with nearby tide gauges, with correlations exceeding 90%. Both diurnal and semidiurnal constituents are well resolved, and amplitude differences remain within 4-5 cm, demonstrating the potential of GNSS-IR as an effective and low-cost complement to traditional TG networks. GNSS PPP solutions further allow the estimation of three-dimensional OTL displacements at hourly temporal resolution. The vertical component is primarily controlled by the semidiurnal M2 tide and closely matches model predictions in both amplitude and phase. Larger discrepancies are observed for diurnal constituents, particularly K1, likely related to interactions with GNSS orbital periods and remaining systematic effects in the processing. Overall, this work presents the first high-temporal-resolution GNSS-based assessment of ocean tidal loading in the northern Adriatic. The strong consistency among GNSS, GNSS-IR, and TG observations highlights the capability of integrated GNSS approaches to simultaneously capture oceanographic variability and solid Earth tidal deformation, opening new perspectives for coastal sea-level monitoring, geodetic stability studies, and hazard assessment in a changing climate.

SummaryThe horizontal magnetic inter-station transfer function (M) offers distinct advantages in magnetotelluric (MT) studies due to its reduced susceptibility to shallow galvanic distortions. While its utility in constraining subsurface conductivity through 2D inversions is established, its resolution characteristics in three-dimensional (3D) scenarios—particularly regarding depth sensitivity and lateral recovery—remain poorly quantified. Here, we conduct a systematic investigation of M through 3D forward modelling, sensitivity analysis, and inversion of synthetic models, followed by a validation using long-period MT array data from the Eastern Pamir. Key findings reveal: (1) M exhibits response patterns analogous to the impedance tensor (Z), with an inverse component correspondence where diagonal elements of Z align with off-diagonal elements of M; (2) Reference station placement critically controls the inversion performance of M—locations above conductive anomalies distort anomalous currents and degrade data fit, whereas resistive homogeneous backgrounds enhance lateral resolution; (3) M resolves shallow anomalies with lateral boundary definition and resistivity contrast recovery superior to those of Z and the tipper (T) in sparse arrays; (4) Sensitivity tests indicate that M provides limited resolution for deep structures beyond the effective inductive scale, where its recovery capability diminishes significantly compared to Z; (5) Application to field data demonstrates that incorporating M improves the resolution of complex shallow structures and enhances the fit of Z data, with the joint inversion of Z + M + T yielding the most robust electrical model. We recommend using multiple reference stations for field data inversion to mitigate the impact of variations in reference site locations. This work establishes a quantitative framework for deploying M in field surveys and 3D inversions.

SummaryOceanic transform faults (TFs) are fundamental elements of plate tectonics and have traditionally been viewed as conservative strike-slip boundaries. Seafloor observations and numerical modelling suggest the existence of extensional stress, however how it manifest at depth remains unknown. Moreover, slow-slipping TFs are often associated with thin crust and possible exposures of serpentinised peridotite near the seafloor. Here we apply full waveform inversion (FWI) to a 12-km offset seismic dataset across the Romanche TF, the largest TF on the Earth. We use source-receiver reciprocity and downward continuation to emulate a split-spread ocean bottom cable survey geometry from one-sided surface streamer data, bringing the refracted waves ahead of reflections while accounting for rough seafloor topography. We then perform travel time tomography followed by FWI to the downward-continued data to derive a high-resolution crustal model. The resolution is about 0.7 km horizontally and 0.4 km vertically, down to 3.5–4 km depth from the seafloor. Our results reveal low P-wave velocity in the upper 3 km, suggestive of basaltic origin, and no evidence for high velocities characteristic of serpentinised peridotite on the valley floor. Moreover, we image inward dipping normal faults extending to ∼4 km depth, forming a flower-like structure. Regional earthquake data reveal strike-slip mechanisms along the transform and normal-faulting near the RTI, with strike-slip hypocenters aligning with interpreted faults. These features suggest that the Romanche TF resembles a trans-tensional regime with a deep-rooted strike-slip fault in the middle, accommodating local strain deformation.

SummaryAdvances in satellite gravimetry technologies have enabled the integration of increasingly diverse mission datasets for high-resolution static gravity field modeling. However, during the construction of regularization matrices for stabilizing Spherical Harmonic Coefficients (SHCs), conventional regularization methods generally neglect significant correlations among SHCs, primarily due to heterogeneous noise characteristics of observations from different missions. To address this limitation, we propose a Full Signal Variance-Covariance (FSVC) regularization method by constructing a full regularization matrix based on a priori gravity anomaly signal amplitudes. Applying this method to combined normal equations integrating GOCE SGG, GRACE, and Swarm observations yield three solutions under different constraint strategies: a Kaula diagonal constrained solution (Tongji-GMMG2025S-KLA), a Diagonal Signal Variance-Covariance (DSVC) regularized solution (Tongji-GMMG2025S-DSVC) derived from the diagonal elements of the FSVC matrix, and the FSVC-regularized solution (Tongji-GMMG2025S-FSVC). Our analyses demonstrate that: Based on FSVC analysis, the proposed FSVC regularization method exhibits overall superior performance compared to the diagonal regularization approach, particularly when the prior model incorporates terrestrial gravity data. Even when using the Kaula-constraint solution as the prior model, quantitative evaluations in both spectral and spatial domains demonstrate that the FSVC-regularized solution still exhibits significantly improved performance relative to diagonal regularization schemes. In the degree range 151–300, the Tongji-GMMG2025S-FSVC model reduces cumulative geoid error degree variances by 9.28 per cent and 9.58 per cent compared to the Tongji-GMMG2025S-KLA and Tongji-GMMG2025S-DSVC solutions, respectively, indicating more effective suppression of medium- to high-degree noise. Spatial comparisons with the XGM2019 model further show reduced gravity anomaly discrepancies, with the FSVC solution achieving the lowest global standard deviation (4.94 mGal). Notably, this improvement is particularly evident in the Indonesia region, which is characterized by complex land-sea distributions. Independent validation using GNSS/Leveling data demonstrates that the FSVC-regularized solution overall higher accuracy than the diagonal-constrained solutions. In particular, the Tongji-GMMG2025S-FSVC model exhibits a distinct advantage, achieving noise reductions of 9.15 per cent and 8.53 per cent relative to the Tongji-GMMG2025S-KLA and Tongji-GMMG2025S-DSVC solutions in the Canadian region, respectively. In conclusion, the proposed FSVC regularization approach proves highly effective in suppressing high-degree noise and enhancing the accuracy of satellite-only static gravity field solutions. This improvement highlights the potential applicability of the proposed approach for future multi-satellite gravity mission integration.

SummaryMachine learning offers new opportunities for geophysical inverse problems, yet conventional regularized inversions of potential field data remain limited by global smoothing constraints and low structural resolution. We propose a locally adaptive, data-driven framework that combines synthetic Earth model generation and ensemble learning for joint gravity and magnetic interpretation. Training models are generated using geologically informed Voronoi-based geometries and planar structures, and a random forest classifier is trained on local statistical features of gravity and magnetic anomalies. The method yields geologically consistent subsurface models that reproduce observed anomaly characteristics without explicit regularization or iterative inversion. Compared with nonlinear Bayesian and traditional regularized inversions applied to the same dataset, the approach provides a substantial reduction in computational cost while preserving key structural features. The performance of the method is inherently linked to how representative the training ensemble is with respect to the target structure, and the results should be interpreted within this context. This framework demonstrates a practical and efficient alternative for potential field inversion using machine learning.

SummaryThis paper describes the implementation of the direct solution method (DSM) using radial spectral elements for the calculation of synthetic seismograms in self-gravitating, spherically symmetric, non-rotating, anelastic, and transversely isotropic Earth models. In contrast to previous implementations of the DSM that used a potential formulation within fluid regions, we use a displacement formulation throughout. It is this feature that allows us to extend the DSM to account fully for self-gravitation along with arbitrary fluid stratification. Our code, DSpecM1D, is benchmarked against the normal mode summation code specnm as well as the direct radial integration code YSpec. Agreement between the codes is excellent for both elastic and anelastic models.

SummaryCarbonate dissolution represents a key mechanism for slab carbon release in oceanic subduction zones. However, the magnitude and controlling factors of carbonate dissolution remain unclear. Here, we develop a coupled thermo-petrological modeling method that integrates slab dehydration, carbonate mineral abundances and their solubilities into subduction-zone thermal models. Systematic model results establish a quantitative relationship between the dissolved CO2 outflux and the subduction-zone thermal parameter (here defined as φ = slab age × subduction velocity/100 in kilometers), which reveals a peak outflux at φ ≈ 13 km, corresponding to warm subduction zones. The dissolved CO2 outflux exhibits a sublinear increase at φ < 13 km and an exponential decline at higher φ. This indicates that warm subduction zones with moderate thermal parameters provide the favorable thermal conditions for carbonate dissolution. The style of aqueous fluid migration strongly influences both the pattern and magnitude of carbonate dissolution. In the pervasive-flow system, fluid infiltration substantially enhances the dissolved CO2 outflux, producing magnitudes approximately three times higher than those in the channelized-flow system. The specific model results for three representative subduction zones—hot Cascadia, warm Nicaragua, and cold Hokkaido—confirm that warm Nicaragua exhibits higher dissolved CO2 outflux, potentially explaining its high arc CO2 degassing outflux.

SummaryDistributed Acoustic Sensing (DAS) using metropolitan telecom fibre-optic cables provides an unprecedented opportunity for seismic monitoring in sedimentary basins, exemplified by Mexico City. In this study, we analyze 15 months of nearly continuous DAS measurements to identify previously undetectable details of wave propagation, thereby enabling the precise localization of local earthquakes. Using real seismic velocity models, we overcome the inaccuracies of traditional constant ${{V}_P}/{{V}_S}$ approaches, highlighting significant limitations of Wadati diagrams in sedimentary environments. Our results reveal clear hydro-seismic coupling, where intense early-season rainfall, coinciding with low aquifer levels, generates sufficient stress perturbations to trigger moderate-magnitude earthquakes (Mw ∼ 3.5). These main events subsequently induce slow slip along local faults and secondary seismicity on a perpendicular plane, driven primarily by stress imbalance rather than fluid involvement along faults. We further identify basin-converted and conical phases as dominant sources of ground shaking, underscoring the urgent need to integrate these secondary seismic phases into urban seismic hazard assessments and building codes. Our findings underscore the crucial role of continuous DAS measurements in comprehending urban seismic risk and managing aquifer resources, thereby establishing a robust monitoring framework with global applicability in sediment-filled megacities.

SummarySeismic reflections from mantle discontinuities provide critical constraints on the structure and dynamics of Earth’s interior, but their extraction remains challenging due to low signal-to-noise ratios (SNR), interference from other seismic phases and uneven spatial distributions. In this study, we propose an array-based extraction strategy that integrates data reconstruction with subsequent denoising for enhancing the extraction of weak mantle reflections. This proposed strategy is independently implemented using the Curvelet-, F–K, and Radon transforms, and the performance of the three implementations is systematically evaluated. Compared with the time-space domain, coherent signals and noise are more easily separated in the transformed domain. We apply these methods to synthetic waveforms generated using a modified ak135 Earth model and test their effectiveness in retrieving reflections from the mantle transition zone (SS/PP precursors) and the D″ discontinuity (ScS/PcP precursors), including cases with random noise and missing traces. All three methods effectively isolate weak mantle reflections, with the Curvelet transform demonstrates the highest robustness and SNR improvement, particularly under conditions of sparse or noisy data. Field applications to data sampling the Central Pacific and Central America further confirm the methods’ ability to recover weak mantle reflections and expand the distance range of usable data. These results demonstrate the potential of array-based extraction strategy to advance deep Earth seismic imaging.

SummaryThe Earth’s figure axis is the axis of maximum inertia for the deformed (oblate) Earth, as described by the degree-two, order-one geopotential coefficients C21 and S21. An extended mean-pole model is presented for evaluating solid-Earth and ocean-pole tides. 50-year Satellite Laser Ranging (SLR) data and 24-year GRACE/GRACE-FO data were analyzed to determine variations in Earth’s figure axis, as reflected in changes in the C21 and S21 coefficients. This study reveals that a significant atmosphere-ocean motion induced a variation in C21 that is captured by SLR data but does not appear in the GRACE solution. The current glacial isostatic adjustment (GIA) ICE-6G model requires improvement to account for the observed linear rates of C21 and S21. A significant 30-year and 60-year signal with an amplitude of ∼ 3×10−11 in the Earth’s figure axis is observed using SLR and a ∼10 mas in the PM (polar-motion), which could be predominantly driven by a 0.05-degree tilt of the inner-core figure axis relative to the figure axis of the entire core and is linked to partial electromagnetic core-mantle coupling.

SummaryContinuous, high-density strain and strain-rate distributed acoustic sensing (DAS) recordings are valuable for resolving the shallow Earth’s structure at a low cost, especially in environments that are otherwise difficult to access, such as continental shelves and near-coastal oceanic crust. In this study, we apply seismic ambient-noise methods to extract high-quality empirical Green’s functions (EGFs) from natural noise sources and model the velocity structure along a 30-km-long dark fiber-optic cable connecting the offshore CASTOR gas storage field in the Gulf of Valencia (Spain) with the associated land facility. We extract broadband EGFs containing a rich variety of seismic waves using wavelet phase cross-correlation and time-scale phase-weighted stacking methods. In the common-source EGF gathers, clean fundamental and first-overtone Scholte waves dominate the marine channel pairs, while the fundamental Rayleigh mode appears in the land channel pairs. In addition, weak wavefields reflected from the basin edge follow the main surface waves. We then construct a 2-D Vs model from local phase-velocity observations of the fundamental and first-overtone Scholte waves by solving pointwise depth inversions using Markov chain Monte Carlo methods. The model resolves the marine sedimentary basin from very shallow water-saturated sediments to depths exceeding 1 km, identifying the Amposta Central Fault and the basement bedrock west of this fault at roughly 1 km depth. These results help refine the offshore velocity model along the cable in a region where induced seismic activity has been observed, improving the accuracy of seismic monitoring and seismic hazard characterization.

SummaryThe conductive and capacitive properties of rocks are influenced by the type and concentration of the electrolyte present in the pore water. Sodium (Na⁺) and potassium (K⁺) are common pore water cations in saturated sedimentary rocks. Their distinct physicochemical properties are expected to produce different frequency-dependent electrical dispersion when adsorbed onto mineral surfaces. We tested this expectation by using spectral induced polarization (SIP), a method sensitive to interfacial processes. Complex conductivity spectra (10–2 to 105 Hz) were measured on two clayey, opal-A-rich diatomite samples, saturated with either NaCl or KCl solutions. One sample was tested over a stepwise increase in molar concentration (5.4–53 mM), while the other was tested over a stepwise increase in bulk water conductivity (0.050–0.48 S/m). At equivalent molar concentration, the in-phase conductivity of a sample was ~20 per cent higher when KCl saturated than when NaCl saturated, reflecting the greater molar conductivity of K⁺. At matched bulk water conductivity, which required a ~20 per cent higher NaCl molarity than KCl molarity, in-phase conductivity was ~10 per cent higher when NaCl saturated. In both tests, the quadrature conductivity and normalized chargeability followed a lower trend in the KCl-saturated state than in the NaCl-saturated state. This relatively low polarization for the K+ saturated state can be attributed to a weaker hydration and more compact adsorption of K⁺ within the inner layer of the electrical double layer. Additionally, time-lapse monitoring of complex conductivity spectra indicates that chemical equilibration via diffusion is achieved within 72 hours for both electrolyte types. This relatively rapid ionic diffusion is consistent with estimates based on the intrinsic formation factor and probably reflects the high porosity of the diatomite (~0.7). These findings establish that pore-water cation identity (Na⁺ vs. K⁺) is a primary control on SIP-derived polarization parameters, and cation identity must therefore be incorporated into petrophysical models to avoid biased estimates of surface area, permeability, and hydrogeochemical state.

SummaryImages of the Earth’s interior can provide us with insight into the underlying properties of the Earth, such as how seismic activity might emerge and the interplay between seismic and volcanic activity. Understanding these systems requires reliable high-resolution images to understand mechanisms and estimate physical quantities. However, reliable images are often difficult to obtain due to the non-linear nature of seismic wave propagation and the ill-posedness of the related inverse problem. Reconstructions rely on good initial estimates as well as hand-crafted priors, which can ultimately bias solutions. In our work, we present a 3D reconstruction of Kilauea’s magmatic system at a previously unattained resolution. Our eikonal tomography procedure improves upon prior imaging results of Kilauea through increased resolution and per-pixel uncertainties estimated through variational inference. In particular, solving eikonal imaging using variational inference with stochastic gradient descent enables stable inversion and uncertainty quantification in the absence of strong prior knowledge of the velocity structure. Our work makes two key contributions: developing a stochastic eikonal tomography scheme with uncertainty quantification and illuminating the structure and melt quantity of the magmatic system that underlies Kilauea.