Geophysical Journal International

SummaryDistributed Acoustic Sensing (DAS) technology has gained widespread attention in seismic exploration due to its high spatial resolution and low deployment cost. However, the presence of coupling noise in DAS data significantly affects the accurate extraction and interpretation of seismic signals. Coupling noise typically appears as narrowband stripe-like or zigzag-like interference and shares similar characteristics with seismic signals in the time-space (T-S) domain, making it challenging for traditional denoising methods to achieve effective signal-noise separation without residual noise or signal leakage. To address these challenges, this paper proposes a deep learning-based dual-domain fusion approach that integrates both T-S and frequency-wavenumber (F-K) domain information to enhance the accuracy of coupling noise separation. The method leverages the narrowband characteristics of coupling noise in the F-K domain while incorporating spatiotemporal information from the T-S domain to achieve cross-domain feature fusion, thereby improving the separability between signals and coupling noise. Experimental results demonstrate that the proposed method significantly improves coupling noise suppression performance on both synthetic and field DAS vertical seismic profile (VSP) data while minimizing signal leakage. Furthermore, in corridor stacking experiments, the method effectively reduces the impact of coupling noise on seismic interpretation, improving the reliability of subsurface formation analysis. Compared to conventional F-K filtering, single-domain network and denoising diffusion model, the proposed approach achieves superior performance in terms of coupling noise suppression and signal amplitude preservation.

SummaryElectrical properties of porous media consisting of solid and fluid phases have been continuously investigated in the study of geomaterials given their strong link to pore space characteristics (e.g. pore size and connectivity). Over the past decades, numerous theoretical models have been developed to determine the electrical conductivity of the porous media as a function of conductivities of their constituents and their relative proportions. In this paper, we present a new theoretical model to calculate the electrical conductivity of a weakly transversely isotropic (TI) porous medium with two conducting phases. We first use the well-established series and parallel electrical connections, together with a newly introduced coefficient g, to construct a conductive cell that represents the porous medium’s microscopic structure. We then obtain the macroscopic weakly TI conductivity stacking these cells in one dimension. We innovatively introduce a normal probability distribution to simulate the distribution of porosities across cells. Good agreement between our theoretical predictions and literature data validates the model for weakly TI porous media. We also show that series and parallel connections of the solid and liquid phases provide reliable building blocks for more advanced models, and that using a normal distribution to simulate electrical anisotropy in quasi-isotropic or weakly TI porous media is viable. Finally, we use the model to study the effects of key variables on weakly TI conductivity. We find that increasing the coefficient g reduces electrical conductivity and that the Electrical Anisotropy Coefficient (EAC) attains its maximum at 50 per cent porosity in weakly TI porous media with two conducting phases.

AbstractSeismic observations reveal significant anisotropy in the D″ region, providing direct constraints on mantle flow and deformation. However, the global anisotropy pattern and its relationship with subduction history, mineral deformation, and rheology in the lower mantle remain unclear. We analyze published regional shear-wave splitting and null measurements, along with waveform inversions, which reveal rapid lateral variations in anisotropy near the edges of large low shear velocity provinces (LLSVPs). We combine mineral physics results of temperature- and pressure-dependent elastic tensors, slip systems, and phase transition mechanisms to explore potential deformation scenarios. We set up models that begin with dynamic thermochemical convection, tracking the deformation history driven by the subduction, evolving crystal fabrics, and cumulative seismic anisotropy. Models show that post-perovskite (pPv) with a (001)-dominant slip system, combined with viscosity changes and texture inheritance during the bridgmanite-post-perovskite (Br-pPv) phase transition and the reverse transition, best reproduces the distinct anisotropy patterns observed in upwelling regions such as plume roots and LLSVP edges. The nominal model is time-dependent, showing strong seismic anisotropy when slabs impinge on the CMB that diminishes toward the LLSVP, followed by plume development at the LLSVP edge with significant anisotropy. Within LLSVPs, internal convective upwellings and downwellings can explain the intermittent, spatially clustered anisotropy. We further demonstrate the potential for constraining LLSVP composition through the observed weaker anisotropy within these structures compared to the surrounding mantle, with our results favoring a Br-rich composition. Computations indicate that the bulk of the lower mantle remains nearly isotropic despite significant texture accumulation through dislocation glide, and that seismic anisotropy can extend several hundred kilometers above the core–mantle boundary.

AbstractReverse time migration based on geometric mean or cross-correlation is a powerful passive-source imaging technique that can produce high-resolution source images even under low signal-to-noise ratio conditions. When the velocity model is inaccurate, a hybrid method combining geometric-mean and arithmetic-mean reverse time migration is typically used to reduce sensitivity to model errors. Conventional hybrid methods usually employ a grouping strategy, in which receivers are divided into groups and multiplicative operations are performed between these groups. However, this strategy essentially utilizes only a subset of receiver combinations, which may compromise imaging quality when the number of receivers is insufficient. To overcome this limitation, a novel combinational autocorrelation reverse time migration imaging condition is proposed. Our method forms multiple combinations of receivers and conducts zero-lag autocorrelation on the extrapolated wavefields of these combinations. The cross terms generated by the autocorrelation operation correspond to all possible receiver combinations. Finally, these autocorrelation results are linearly stacked in order to eliminate interference terms while preserving the cross terms. By including more receiver combinations, the proposed method can provide improved imaging performance. Furthermore, due to the adoption of the autocorrelation algorithm, the new method achieves minimal memory usage among methods based on reverse time migration, which makes it especially suitable for three-dimensional problems. Acoustic numerical simulations verify the effectiveness and advantages of the new method in both two-dimensional and three-dimensional scenarios. Additionally, the mathematical relationship between our method and conventional methods is discussed, clarifying the applicable scope of the new method.

SummaryIn the previous paper of this series, a petrophysical model named the Dynamic Stern Layer (DSL) model was extended to describe induced polarization phenomena associated with permafrost by capturing direct and indirect effects associated with the presence of ice in porous media. In the present paper, time-domain induced polarization data obtained in field conditions are interpreted thanks to this updated DSL model. We selected three different test sites in order to apply the DSL model to very different conditions of low and high ice contents to see how ice content directly and indirectly affects geoelectrical measurements. A first survey is performed along a cross-section of a ridge in the Kangerlussuaq mountains of Greenland (Site I). In this area, the rock corresponds to a Precambrian granite characterized by a rather low (< 5%) porosity and therefore a low ice volumetric content on the North face of the ridge. We do not see any direct ice polarization contribution in the data obtained with a current injection period of 1 s. We also performed a field survey close to Col des Vés (2846 m a.s.l., Tignes, French Alps, Site II). This site corresponds to a complex ground ice body overlying a substratum made of a low-porosity marble, both having high resistivity values. The front of this body is characterized by a small amount of residual ice while the roots are ice-rich. Therefore the porosity at this site is high and the ice content highly variable. This case study showcases the role of ice in the induced polarization data in terms of high chargeability values (close to 1 as predicted by the theory in which ice behaves as a surfacic protonic semi-conductor) at the roots of the complex ground ice body. A third site (Site III) corresponds to a profile crossing the Aiguille du Midi (3842 m a.s.l., Chamonix), also in the French Alps in a low porosity granitic environment. Laboratory experiments are used to interpret the tomograms of the electrical conductivity and normalized chargeability using the DSL model and water content and Cation Exchange Capacity tomograms are reconstructed at these sites. This study demonstrates the ability of induced polarization to be an efficient tool to characterize permafrost in very different field conditions.

SummaryModelling induced polarization (IP) effects in electromagnetic (EM) data is increasingly becoming a standard tool in mineral exploration, but the industry standard is still based on one-dimensional (1D) forward and Jacobian modelling. We have developed a three-dimensional (3D) electromagnetic forward and inversion method within the EEMverter modelling platform, incorporating IP effects. The 3D computations are performed in the frequency domain using the vector finite element method and then transformed into the time domain via Hankel transformation. This approach enables modeling of any IP parameterization, ranging from the simple constant phase angle model to a full Debye decomposition. Furthermore, 3D forward modeling mesh and inversion mesh are built independently: an Octree forward mesh is designed for efficient spatial segmentation for single or multiple soundings, while the inversion parameters are defined on a structured model mesh, which is linked to the forward meshes via interpolation. In conjunction with the development of a full 3D EM-IP inversion, we introduce a novel 3D inversion workflow. This workflow allows for hybrid 1D-3D computations, both sequentially and spatially, enabling 3D modeling exclusively in the most significant and interesting areas of the survey. We tested the hybrid 1D-3D inversion workflow using airborne electromagnetic (AEM) data acquired by Xcalibur with the HeliTEM system in the Staré Ransko area (Czech Republic), known for its gabbro-peridotite rocks hosting nickel-copper±cobalt, platinum group element (Ni-Cu±Co, PGE) mineralization. The results demonstrate that the hybrid inversion effectively addresses the challenges of 3D modeling on large-scale datasets. It enhances interpretation reliability in regions with strong 3D effects and shows a significant spatial correlation between resistivity and chargeability phase anomalies and known mineral deposits. Moreover, both synthetic and field data indicate that the resistivity parameter is more sensitive to 3D effects than the chargeability phase parameter.

SummarySeismic reflection and transmission provide essential insights into the composition of reservoir solids and fluids. Reservoir media often consist of layered structures that contain solids, fluids, pores, and cracks. In such complex layered media, the stable and accurate modeling of seismic wave propagation is crucial for effective reservoir evaluation using seismic waves. By solving the cracked porous medium wave equation for layered structures using the propagator matrix method, we calculate the frequency-dependent oblique incident P-SV and SH wave reflection and transmission for the layered poroelastic media containing cracks. This approach accounts for the combined effects of impedance contrast and crack squirt flow on wave reflection and transmission. The newly developed model includes interlayer fluid flow, crack squirt flow, and global fluid flow. Among these mechanisms, interlayer fluid flow and crack squirt flow can both be prominent in the seismic frequency band. Then, the model was applied to simulate seismic reflection and transmission in cracked interlayer and interface geological structures. The results show that the pore-crack squirt flow mechanism plays a significant role in determining seismic reflection and transmission. Increased crack density and gas saturation significantly enhance P-wave reflection and generate seismic reflection bright spots, while for the S-wave reflection, the effect is largely controlled by crack density, and, when crack density is high, is moderately affected by fluid saturation. This fluid sensitivity results from the crack squirt flow mechanism, which is absent from the classical Biot-Gassmann theory. In all known limiting cases, the model predictions agree with those from the Biot-Gassmann theory.

SummaryIntermontane basins in active orogenic regions face significant seismic hazard due to their proximity to sustained tectonic activity. While the sediments deposited in these basins create a relatively flat topography suitable for urban and infrastructure developments, their unconsolidated sedimentary fill locally amplifies earthquake-induced ground motions, thereby increasing the seismic hazard and risk. Documented observations suggest that ground motion estimates in these basins are often poorly constrained due to oversight of surrounding surface topography and insufficient sub-surface information about deeper basin layering, leading to inaccurate hazard assessments. In this study, we systematically evaluate the implications of these two factors on ground motion characteristics up to 4.4 Hz, which is crucial for earthquake engineering practices. We conducted 3D simulations around the Kathmandu catchment area (Nepal) using hypothetical thrust-faulting moment tensor sources at various depths and locations. The results show a significant reduction, by an order of magnitude, in the peak ground velocities (PGV) at the catchment area due to surface topography. However, this effect is prominent only for very shallow earthquakes producing predominant surface waves; for deeper sources, the de-amplification may be negligible or even result in amplification due to scattered body waves converted into surface waves. To incorporate basin-specific material properties, we performed the analysis in a computationally-feasible 2D domain, which shows that the existence of topography can reduce the energy entering the basin, hence resulting in a reduced basin amplification. The deeper layers of the Kathmandu basin play a critical role in controlling the spatial variability of the observed amplification, with significant differences within the basin compared to scenarios that exclude these deeper layers. We conclude that neglecting topography in ground motion predictions may lead to an overestimation of ground motion amplification in the basin. Pronounced topographic features in the surrounding of intermontane basins can result in further scattering of the received energy content from earthquakes occurring outside of the basin, especially for the high-frequency motions. In addition, in order to provide site-specific measures of ground motion in intermontane basins, high spatial resolution of the underlying geological structure is deemed imperative.

SummaryInterpreting geophysical inversion results across diverse applications presents significant challenges, particularly when the resulting images lack distinct, sharp interfaces. Incorporating prior information to constrain the inversion process introduces additional complexity, especially when this prior information itself contains uncertainties. This work explores methods for improving the geometric representation of geologic structures using integrated geophysical and geologic models. While many existing approaches are either data-driven or model-driven techniques, they often fail to fully integrate available data into a dynamic, unified geomodel. We present an approach that integrates geologic models and geophysical data through structure-based inversion. Our approach preserves geological realism through an implicit model while imaging sharp contrasts within the geophysical inversion models. To address the ambiguities of solving for both the geometry and physical parameters, we adopt a sequential inversion process, first resolving shifts of geologic interfaces, then inverting for geophysical parameters using the updated geometry as a structural constraint. The method’s efficacy is demonstrated through cross-hole travel-time tomography using two synthetic and one field data set from the Mont Terri Rock Laboratory (MTRL). The field data results validate the capability of our approach to recover subsurface interface geometries from geophysical data that are comparable to the interpolated interfaces from borehole data. While we demonstrate the method for seismic travel time data in cross-hole geometry, the flexible open-source implementation allows application to 3D scenarios and other geophysical methods.

SummaryWe efficiently extract high-quality Pn wave arrival times from seismograms recorded at recently deployed 120 portable seismic stations of TanluArrays and 317 stations of the Chinese provincial seismic network for 7231 local earthquakes (M >2.0) using the PickNet automatic picking method. Then we use the Pn data to determine 2-D P-wave velocity and anisotropic tomography of the uppermost mantle in and around the Tanlu Fault Zone. Our Pn tomography reveals segmented features of the fault zone, which are well consistent with geological structural features. A continuous low-velocity anomaly parallel to the fault zone is revealed along the Bohai Bay-Weifang, Weifang-Tancheng, and Tancheng-Mingguang segments, whereas the Mingguang-Wuxue segment exhibits a bead-like alternating high and low velocity belt. A similar segmented characteristic also appears in the Pn wave anisotropy in and around the fault zone. A majority of strong earthquakes are located in transitional zones between high and low Pn velocities, suggesting that structural heterogeneities in the uppermost mantle may affect crustal seismogenesis. The low Pn velocities may reflect upwelling of hot and wet upwelling flows in the big mantle wedge due to mantle convection and dehydration of the flat Pacific slab in the mantle transition zone, which cause seismic anisotropy in the upper mantle in and around the Tanlu fault zone.

SummaryEarthquake monitoring plays a critical role in disaster warning and geophysical research, including earthquake phase picking and source parameter estimation. However, traditional methods suffer from cumbersome workflow and challenges in parameter selection during multi-parameter joint estimation. Here, we propose a multitask network for earthquake monitoring that reduces computational complexity by replacing the self-attention mechanism with fast Fourier transform. Through the integration of a fusion module and an enhancement module, the interaction between tasks is strengthened to optimize network performance. Additionally, a dynamic adaptive weight allocation strategy is introduced to achieve a balance among different tasks. The proposed method was trained and tested on the STEAD and INSTANCE datasets and compared with advanced approaches. The results demonstrate that this method outperforms other deep learning methods in earthquake phase picking and source parameter estimation, achieving lower errors and higher evaluation metrics, thus showing potential for practical application in earthquake monitoring.

AbstractMeasurements of the propagation of teleseismic fundamental-mode surface waves are essential for studies of Earth structure and earthquake source processes. Understanding sources of noise and error in these measurements can help improve the accuracy and precision of analyses that use these measurements. One prominent source of noise is interference of overtones with the fundamental mode, which is well-studied in the context of surface wave phase observations. In this work, we show that overtone interference also has a substantial impact on group measurements and has uniquely different characteristics when compared with the analogous interference in phase measurements. We illustrate these characteristics using measurements on both synthetic and real data. Importantly, our experiments suggest that group measurements are more vulnerable than phase measurements to interference from overtones; both synthetic data and published datasets show larger and more variable interference in group measurements than in phase measurements. This interference leads to significant errors in group velocity estimates made using regional or array-based approaches. We show that some quality control measures designed to eliminate overtone interference in phase measurements may not be applicable for group measurements. Our results emphasize the need for careful monitoring of group velocity overtone interference in tomographic imaging, as well as the need for accurate uncertainty quantification when group velocity maps are used in further studies.

AbstractCompared to first-arrival traveltime tomography (FATT), first-arrival traveltime and slope tomography (FASTT) integrates both traveltimes and local slopes of first arrivals at sources and/or receivers to construct more accurate subsurface velocity models. Local slopes serve as additional constraints, helping to mitigate the ill-posedness of tomography by better constraining ray directions. This is particularly beneficial in regions with complex topography, where shadow zones arise due to strong velocity contrasts. However, representing complex topography or bathymetry can be less accurate when using classical rectangular grid discretization. To address these complexities with greater versatility and accuracy, we compute traveltimes of locally coherent events using a factored topography-dependent eikonal solver on curvilinear grids. Slopes are then estimated by finite differences in the traveltime maps after a back-and-forth coordinate transform from the curvilinear grid to a rectangular computational grid. Additionally, we solve the inverse problem with the matrix-free approach, where the data misfit gradient is computed with the adjoint-state method. This adjoint—state formulation avoids the explicit construction and storage of large Fréchet derivative matrices and does not require a tedious posterior ray tracing on curvilinear grids. A land synthetic example first illustrates the sensitivity of slopes to topography and the more accurate velocity models with FASTT than with FATT in the presence of topography. We then perform a first application of the topography-dependent FASTT method on a real redatumed ocean-bottom node dataset, where the bathymetry exhibits a steep scarp. We show that the topography-dependent FASTT generates a velocity model that matches more closely a legacy reflection tomography model than conventional FATT. We conclude that the topography-dependent FASTT provides a versatile approach for handling complex surfaces during velocity model building in both marine and land environments.

SummaryMagma transport in dikes is usually modelled by means of lubrication theory, assuming that magma properties are uniform across the dike. We explore the influence of cross-dike temperature heterogeneity on the dynamics of dike propagation using a quasi-2D model, derived from a full 2D model with an assumption of small width to length ratio. The model couples elastic fracture mechanics with multiphase magma flow, solving the governing equations using a hybrid numerical approach that combines the Displacement Discontinuity Method for elasticity with finite volume discretization for fluid flow and heat transfer. The model includes heat exchange with wall rocks, shear heating and latent heat release. It accounts for non-equilibrium magma crystallization, implementing temperature-dependent crystallization kinetics using an Arrhenius formulation for the relaxation timescale. As a case study, we simulate the ascent of a volatile-rich dacite from a source at 30 km depth. The distribution of temperature, crystallinity, and, thus, viscosity across the dike leads to a plug-like velocity profile with magma stagnation near the walls, substantially different from the parabolic Poiseuille flow assumed in classical lubrication theory. With temperature-dependent crystallization rate, rapid cooling of magma near the dike walls can generate a glassy chilled margin. The adjacent magma has higher crystallinity due to intermediate cooling rates, while the hotter core remains depleted in crystals throughout dike propagation. The dike propagates further and is thinner than predicted by (1D) lubrication theory because the low-viscosity core continues to facilitate vertical transport while the wall zones become progressively more viscous due to cooling and crystallization. The latent heat of crystallization can have a substantial impact in slowing down cooling and prolonging propagation. Other important factors include the characteristic crystal growth time, initial magma temperature and water content. Our quasi-2D approach bridges the gap between oversimplified 1D models and computationally expensive 3D simulations, providing a practical framework for investigating magma transport in silicic dikes.

SummaryThe 1957 Andreanof, Aleutian Is., earthquake (1957 March 9, 51.53°N, 175.63°W, d=25 km) is among the most enigmatic great earthquakes instrumentally recorded. The length of the aftershock area is very long (about 1,200 km), and tsunami excitation has been recently confirmed to be very extensive, yet its instrumental seismic magnitude Ms is only about 8.1 to 8.3. Detailed analyses of long-period surface waves in the past gave an Mw=8.4, and the seismic-tsunami disparity remains unresolved. The main difficulty in seismic studies is the absence of high-quality seismic data. Here we investigate the cause of this disparity by carefully analyzing some historical seismograms with modern digitization methods. We also take advantage of the 1996 Aleutian Is. earthquake (Mw=7.87) that occurred very close to the 1957 event. For the 1996 event, high-quality modern broad-band seismograms are available which can be effectively used as empirical Green’s functions for the analysis of the 1957 event. Using the Wiechert (Strasbourg, Uppsala), Milne-Shaw (Wellington), and Benioff (Uppsala, Pasadena) seismograms of the 1957 event, we could determine that the 1957 event had significant secondary excitation of long-period (150 s) waves during about 1,000 s following the first event. The Mw of the combined source is approximately 8.4. Because of the limited bandwidth of the old instruments, we cannot detect long-period energy beyond 150 s. However, the unusually long-lasting excitation over nearly 1,000 s suggests that the event had significant excitation at periods longer than 150 s with a much larger Mw for the total event. Although we cannot address this question quantitatively because of our band-limited data, our numerical experiment using a source with a slow component shows that if the time scale of the slow source is longer than 500 s, our data can be made compatible with an Mw =8.8 to 8.9 event, thereby reconciling the results from seismic and tsunami data.

AbstractThe rheological properties of the mantle govern plate tectonics and mantle convection, yet constraining the rheological parameters remains a significant challenge. Laboratory experiments are usually performed under different temperature-pressure-strain-rate conditions than those of natural environments, leading to substantial uncertainties when extrapolating the parameters to real-world conditions. While traditional Bayesian inversion with Monte Carlo sampling methods offers sufficient exploration of the parameter space and accurate inversion results, the excessive computational cost limits its practical application to complex nonlinear problems. To address these limitations, we integrate finite-difference-based geodynamic forward modeling with Automatic Differentiation (AD) to build a framework to invert non-linear rheological parameters. By incorporating multisource observational data, including surface velocities and topography, we are able to invert critical rheological parameters of the lithosphere and mantle, including the viscosity pre-exponential factor, activation energy, stress exponent, yield stress, and plate-interface viscosity. To validate the method, a series of models with different levels of complexity from single- to multiple-subduction systems and consideration of data noises are designed to generate synthetic data that are further used for inversion. Our method can successfully restore the rheological parameters under various conditions, with minimal errors between predicted and true values, underscoring its stability and broad applicability. In general, this study introduces a highly efficient and practical geodynamic forward and inverse modeling approach that can be used to infer the rheology of the mantle.

AbstractSeismic waveforms are essential for deciphering the subsurface structures of the Earth. Traditional methods for seismic waveform selection rely heavily on manual identification by experienced seismologists, which can be inconsistent and challenging when complex structures or huge amount of seismic data volumes are involved. Recent advancements in machine learning, particularly supervised learning techniques, have shown promising progress in addressing these challenges; however, their dependence on large labeled datasets limits their application to weak or rare seismic phases. In this study, we propose a new strategy using hierarchical clustering for seismic waveform identification, which does not need labeled dataset and minimizes extensive parameter settings. Our strategy is especially powerful when dealing with multiple waveform phases that may shift according to epicentral distance or may be distorted due to attenuation or other factors. We apply our strategy to identify various seismic wave of both P and S phases, especially those sampling deep Earth such as SKS-SKPdS and ScP phases. The results show that the strategy performs excellently and can identify different anomalous signals. Our approach empowers researchers to conduct more detailed studies in previously overlooked regions or datasets, thereby leading to a better understanding of deep Earth’s structures.

SUMMARYRock glaciers are specific landforms consisting of a mixture of rock debris, ice, liquid water, and air. In the Alps, active rock glaciers are generally found at high elevations above 2500 m. Active rock glaciers creep and can develop anomalous slide-like behaviors called destabilization. Induced polarization is a non-intrusive geophysical method that has proven to be sensitive to the hydrogeological properties of porous media. In August 2023, we performed four induced polarization profiles at Plan-du-Lac (Vanoise, France), on a multi-unit rock glacier complex with a front located at a low altitude of 2200 m). Our goal was to determine its architecture and its water and ice contents in relation with its activity rate. The survey included two transverse high-resolution profiles with a 5 m spacing between the electrodes and two other longitudinal profiles with a 20 m spacing between the electrodes allowing a depth of investigation of roughly 200 m to image the rock glacier from its terminal front up to its root. The conductivity and normalized chargeability tomograms were inverted and then used to get the water content and cation exchange capacity (a proxy for the clay content) tomograms. In most of the units, ice has disappeared and the landforms associated with the former rock glacier were characterized by low water and clay contents with respect to the basement. This was consistent with these units being mostly formed by rock debris with a low water saturation except at their bases, which are water-saturated. Ice remains were found at the roots of the rock glacier, with a volume content up to ∼10 per cent (vol. per cent) for profile P2 and 16 per cent for profile P4. The roots of the rock glacier complex were still creeping as shown by InSAR data. This case study demonstrates the usefulness of the induced polarization method to quantitatively characterize gravitational instabilities associated with coarse materials and transitional rock glaciers.

SUMMARYIn October 2023, an earthquake sequence comprising four ∼ MW 6.0 events struck Herat Province in northwestern Afghanistan, causing severe casualties and property losses. The geometry of seismogenic faults and the mechanisms of the earthquake sequence are essential for regional seismic hazard assessment, but still remain poorly constrained. With Interferometric Synthetic Aperture Radar (InSAR) techniques, we extracted high-resolution co- and early post-seismic deformations of the events. Through a two-step inversion method, we inferred the geometry of the causative faults and the distributed slip models. The earthquake sequence ruptured two intersecting low-dip thrust faults, indicating that the complex geometry may have played a key role in controlling the propagation of the events. The ruptures of the four major events are clearly imaged at depths of 1-10 km without reaching the surface, showing a pattern of first spreading westwards, then jumping eastwards to the bend segment, and finally rupturing an adjacent fault. Post-seismic deformation further reveals reactivation of a secondary fault splay which underwent afterslip. Shallow afterslip up-dip of the co-seismic rupture dominates post-seismic deformation during 10 months following the earthquake sequence. Relying on the evolution of afterslip, we infer that significant rate-strengthening property in the shallow bend section may have hindered further co-seismic rupture propagation. Combining obtained results and the complex geological setting of the Herat region, we suggest that the earthquake sequence reflects N-S crustal shortening between two branches of the western Herat Fault System.

SUMMARYIn the last decade, the Dynamic Stern Layer (DSL) model has proven to be a reliable petrophysical model to comprehend induced polarization data at various scales from the representative elementary volume of a porous rock to the interpretation of field data. Preliminary works have demonstrated that such model can be extended to understand the induced polarization properties of ice-bearing rocks and to interpret field-acquired induced polarization data in the context of permafrost. That being said, the direct effect of ice was let aside. We first review the DSL model in presence of ice and discuss the role of ice as an interfacial protonic dirty semi-conductor in the complex conductivity spectra with an emphasis on the role of the complex-valued surface conductivity of ice crystals above 1 Hz. We propose a new combined polarization model including indirect and direct ice effects. By direct effects, we mean the effects associated with change in the liquid water content and salinity of the pore water. By direct effect, we mean the role of the interfacial properties of the ice surface and liquid water is still present in the pore space of the porous composite. In this case, the electrical current is not expected to cross the ice crystals. Instead, it would polarize the surface of the ice crystals and generate a very high chargeability that can reach one depending on the value of the volumetric content of ice. We apply the DSL model to a new set of complex conductivity spectra obtained in the frequency range 10 mHz-45 kHz using a collection of 25 rock samples including metamorphic and sedimentary rocks in the temperature range + 15/+20°C to -10/-15°C. We observe that the model explains very well the observed data in the low-frequency range (10 mHz-1 Hz) without any direct contribution of ice. In the high frequency range (above 1 Hz), we observe a weak contribution possibly associated with the contribution of ice crystals. We establish under what conditions the direct contribution of ice can be neglected. We also investigate the role of porosity, cation exchange capacity, and freezing curve parameters on the complex conductivity spectra of crystalline and non-crystalline rocks during freezing. Laboratory experiments demonstrate that in most field conditions including permafrost conditions, surface conductivity associated with conduction on the surface of clay minerals (and alumino-silicates in general) is expected to dominate the overall conductivity response. Therefore Archie’s law cannot be used as a conductivity equation in this context because of the contribution of surface conductivity. A large experimental and field dataset at the Aiguille du Midi (3842 m a.s.l., French Alps) for the resistivity versus temperature data of granitic rocks demonstrates the role of surface conductivity in the overall conductivity of the rock.