Geophysical Journal International

SummaryA strong earthquake sequence in Storfjorden, south of Svalbard, was initiated by an Mw 6.1 event on 21 February 2008. Earthquake distribution and fault plane solutions indicate that seismic activity is controlled by unmapped NE-SW striking oblique-normal faults, contrasting with the major N-S oriented faults mapped onshore Svalbard. We present a geophysical model derived from an ocean bottom seismometer profile crossing the seismogenic zone to identify structures in the crust and uppermost mantle that potentially control the earthquake source mechanism. Travel-time forward modeling using raytracing, combined with travel-time tomography and gravity-magnetic modeling, reveal distinct crustal domains across the earthquake region. Crystalline crustal P-wave velocities range from 6.1 km/s to 6.7 km/s at the Moho depth in the eastern section. The western profile section exhibits a higher Vp velocity lower crust (6.6–7.0 km/s) with Vp/Vs ratios of 1.75–1.8 and high density (∼3100 kg/m³). Basement depth reaches 8 km in the west, forming a sedimentary basin, and shallows eastward. The Moho remains relatively flat at 29-32 km depth throughout the profile. The N-S oriented Caledonian suture, identified from deep seismic and potential field data, traverses the Storfjorden earthquake zone. The lithological contacts within the suture zone, inferred from the new OBS data, may facilitate seismic failure oblique to the N-S oriented structure, following the regional stress field.

SummaryWe developed a new amplitude correction method for receiver function imaging to analyze velocity contrasts along dipping interfaces. Because receiver function imaging typically assumes a horizontally layered structure, corrections are needed for amplitude and polarity variations of P-to-S converted phases when analyzing dipping interfaces. However, previous studies have not adequately addressed these effects, and improved receiver function analysis is required to better delineate dipping structures, such as subducting plate surfaces and the oceanic Moho. Therefore, we propose formulae that quantify converted S-wave amplitude variations between horizontal and dipping interfaces. This relationship is expressed as a function of the back azimuth, the ray parameter of an incident P wave, and the dip angle and dip direction of a dipping interface, and in this study, the geometry of the dipping interface (dip angle and dip direction) is assumed. We applied these formulae to receiver function imaging using synthetic and observed data and confirmed that the amplitude of seismic discontinuities was successfully reproduced. This method enables the use of numerous receiver functions regardless of the back azimuths of incident P waves, thereby providing more detailed amplitude estimations for dipping interfaces.

SummaryTo better understand the mechanics of injection-induced seismicity, we developed a two-dimensional numerical code to simulate both seismic and aseismic slip on non-planar faults and fault networks driven by fluid diffusion along permeable faults, in an impervious host rock. Our approach integrates a boundary element method to model fault slip governed by rate-and-state friction with a finite-volume method to simulate fluid diffusion along fault networks. We demonstrate the capabilities of the method with two illustrative examples: (1) fluid injection inducing slow slip on a primary rough, rate-strengthening fault, which subsequently triggers microseismicity on nearby secondary, smaller faults, and (2) fluid injection on a single fault in a network of intersecting faults, leading to fluid diffusion and reactivation of slip throughout the network. This work highlights the importance of distinguishing between mechanical and hydrological processes in the analysis of induced seismicity, providing a powerful tool for improving our understanding of fault behavior in response to fluid injection, in particular when a network of geometrically complex faults is involved.

SUMMARYIn mineral exploration, induced polarization and self-potential are two broadly used active and passive geophysical methods, respectively. In the case of ore bodies, both methods are associated with charge distributions associated with a secondary electrical field (induced polarization) and a source current density (self-potential). Both the chargeability and volumetric source current density distributions bring information regarding the shape of ore bodies. Therefore the joint inversion of these datasets is expected to better tomograms of ore bodies. A joint inversion approach is developed to combine both methods. The objective function to minimize includes two independent components plus a cross-gradient joint function. The use of the cross-gradient is justified from the underlying physics of the two geophysical problems at play. The structure of the cost function is tailored to overcome some problems like convergence and parameter determination in the inverse process. Two synthetic tests and a laboratory experiment are used to benchmark the proposed algorithm. We demonstrate that the joint inversion algorithm performs better than the localizations obtained from independent inversion approaches. To refine the interpretation of the shape of ores, we introduce an ore presence index using the chargeability and source current density resulting from the joint inversion algorithm. The K-Medoids clustering algorithm is used to automatically categorize the calculated ore presence index into different clusters. The cluster with larger values successfully identifies the ore bodies associated with strong chargeability and/or volumetric source current density.

SummaryInversion of geomagnetic anomaly data poses an ill-posed problem, and extremal models such as equivalent source layers or point-source distributions can explain observations to the same degree as volumetric magnetisation distributions. However, the spectral characteristics of magnetic anomalies provide fundamental constraints for magnetic source-depth estimation. Specifically, the maximum detectable depth of crustal magnetic sources is dictated by the longest wavelengths present in the field, which correspond to the low-wavenumber bands of the spectrum. This relationship is often analysed through the log power spectrum versus wave number plot, using the slopes of the linear segment for depth estimation. Methods aiming at reconstructing the depth to the bottom of magnetisation from spectral field characteristics are commonly referred to as spectral methods. However, these methods are based on assumptions about the statistical properties of the source distribution and are prone to misinterpretations. Here, we apply sparsity-constrained 3D inversion of magnetic data using an elastic net regularisation to recover the susceptibility distribution and the bottom of magnetisation. We claim that the elastic net (ℓ2ℓ1 norm) regularisation, when properly tuned to balance the solution’s smoothness with sparsity, stabilises the inversion, avoiding extremal magnetisation distributions and generating a geologically plausible source depth distribution that is consistent with the expected source distribution. The ℓ1 norm brings sparsity and high resolution, while the ℓ2 norm brings inversion stability and structural continuity to the final model. From the recovered 3D elastic net sparse inversion model, we extract the depths of all the deepest non-zero susceptibility values and suggest this to be an alternative estimate to the base of magnetisation. Moreover, we suggest that the resulting 3D model has a value in itself and may aid geological interpretation.

SummaryGaining insight into the centennial evolution of the geomagnetic field over the past 2000 years requires the acquisition of reliable palaeomagnetic data from the study of well-dated archaeological materials or rocks. However, despite previous efforts, palaeointensity data from regions south of 30°S are still underrepresented, potentially limiting the accuracy of global geomagnetic field models and their applications. In addition, a comprehensive understanding of the geomagnetic field evolution in South America is particularly relevant, as the recent geomagnetic secular variation has been mainly characterised by the significant growth of the South Atlantic Anomaly over the past three centuries. The evolution of this low-intensity region, currently centered over central South America, is well understood in detail only during the last few centuries, thanks to the availability of direct measurements. For both the geomagnetic and palaeomagnetic communities, understanding its evolution prior to this period remains a challenge. This study presents new palaeointensity estimates from San Juan Province, central western Argentina, based on the analysis of 23 pottery samples dated between the 3rd and 17th centuries CE using radiocarbon and archaeological constraints. We employed the Thellier-Thellier method, incorporating partial thermoremanent magnetisation (pTRM) checks, TRM anisotropy corrections, and cooling rate adjustments, and obtained 11 mean palaeointensity values of good technical quality for central South America. The results are consistent with the limited number of previously reported high-quality palaeointensity data within an area 900 km in radius centered on San Juan, all showing intensity values ranging from approximately 40 to 55 μT. The new data, combined with these previously published high-quality intensities, do not show anomalously low values in intensity in the region between 200 and 1750 CE, suggesting no significant impact of the South Atlantic Anomaly in the region before the past three centuries. Furthermore, the findings suggest the presence of rapid multidecadal variations between 800 and 1100 CE, a behaviour also observed in other regions worldwide, which may point to a global or dipolar origin for these variations. By enhancing the dataset for this latitude range, this work provides new constraints on the geomagnetic field’s past behaviour south of 30°S over South America and contributes to improving future global geomagnetic reconstructions.

SummaryAbsence of traces tends to reduce the quality and reliability of Ground Penetrating Radar (GPR) data due to equipment, sensor coverage, and acquisition limitations. This is a significant limitation to Full Waveform Inversion (FWI) and Reverse Time Migration (RTM) advanced imaging techniques, which rely on dense and continuous data. To address this challenge, we propose an effective interpolation method using the Projection onto Convex Sets (POCS) algorithm, originally developed for seismic data reconstruction. The algorithm is formulated in a compressed sensing framework, taking advantage of Fourier sparsity and iterative thresholding in the time domain to iteratively update spectral coefficients during reconstruction. We compare its performance on synthetic and real GPR data with various percentages of missing data. Results indicate that the POCS algorithm, in addition to reconstructing missing traces at high precision, significantly improves subsequent RTM imaging structural resolution. We also compare POCS with conventional Kriging and a deep learning-based interpolation model (DL-Net) to benchmark its performance. The proposed method achieves superior reconstruction quality and stability, particularly under high sparsity conditions. This study highlights the practical potential of POCS in enhancing GPR image fidelity and interpretation under real-world acquisition limitations.