Geophysical Journal International

SummaryFull waveform inversion (FWI) is a high-precision subsurface imaging technique that inverts subsurface parameter models by minimizing the discrepancy between observed and synthetic seismic data. However, complicated wave propagation mechanisms, non-convexity of the loss function, and limited seismic acquisition system necessitate the incorporation of sufficient prior and physical constraints to alleviate the ill-posedness and cycle-skipping. Although the implicit FWI (IFWI) can encode implicit spectral bias (i.e., inverting model parameters from low frequencies to high frequencies) to reduce the dependency on an accurate initial model, its limited high-frequency inversion capability results in thousands of iterations for the final results. In this paper, we indicate that the frequency hyperparameters of the sine activation function in IFWI modulate the spectral bias, making a trade-off between inversion accuracy and stability, i.e., lower frequencies yield robust FWI but lower accuracy, while higher frequencies achieve higher accuracy on the premise of an accurate initial model. To improve both the stability and accuracy of IFWI, we propose a novel implicit FWI method with an adaptive Fourier reparameterization strategy (termed FR-IFWI), which explicitly encodes multi-frequency information by reparameterizing the network weights using a learnable coefficient matrix and fixed Fourier frequency bases. The role of learnable matrices in neural networks can evolve from determining frequencies in IFWI to actively selecting frequencies from fixed frequency bases through FR-IFWI, which alleviates the dependence on activation function frequency and obtains more robust and accurate inversion results. Extensive numerical experiments on the modified Marmousi, 2D SEG/EAGE Salt and Overthrust models confirm that FR-IFWI successfully achieves superior inversion efficiency and accuracy compared with conventional FWI and IFWI methods.

SummaryA growing body of literature has contributed to linking the presence of bacteria with SIP signals. Yet, there are still unresolved questions concerning the contribution of cell density and microbial metabolic activity in porous media (soils and sediments) to SIP signals. Moreover, there is continued debate on whether cells themselves polarize or whether a cell-sediment interaction is a prerequisite for the measured responses. This study investigates the SIP response of Shewanella oneidensis MR-1 in isolation, that is, in the absence of a mineral porous medium using two setups (i) cells in aqueous suspension and (ii) alginate bead-packed reactors. Results from experiments conducted with static cell suspensions shed light on the strong control of cell settling that drives erratic, poorly reproducible and difficult to interpret SIP signals. However, incubating cells in bead packed reactors yielded reproducible trends in σ″, with strong (3 – 10 mrad) signals that followed the expected cell growth behaviour. Relating σ″ to measured cell density and metabolic activity (using ATP) highlighted the strongly linked contribution of both activity and cell density and SIP. Here, we report a lower frequency polarization peak between 0.01 and 0.1 Hz in the bead reactors, which we attribute to the polarization of cell colonies in the densely packed reactors. In summary, our findings shed light on the direct contribution of cells and their activity to polarization, in the absence of cell-sediment interactions and provide a novel approach for studying cell polarization in static incubation in a porous environment.

SummaryWe present DASPack, a high-performance, open-source compression tool specifically designed for distributed acoustic sensing (DAS) data. As DAS becomes a key technology for real-time, high-density, and long-range monitoring in fields such as geophysics, infrastructure surveillance, and environmental sensing, the volume of collected data is rapidly increasing. Large-scale DAS deployments already generate hundreds of terabytes and are expected to increase in the coming years, making long-term storage a major challenge. Despite this urgent need, few compression methods have proven to be both practical and scalable in real-world scenarios. DASPack is a fully operational solution that consistently outperforms existing techniques for DAS data. It enables both controlled lossy and lossless compression by allowing users to choose the maximum absolute difference per datum between the original and compressed data. The compression pipeline combines wavelet transforms, linear predictive coding, and entropy coding to optimise efficiency. Our method achieves up to 3 × file size reductions for strain and strain rate data in lossless mode across diverse datasets. In lossy mode, compression improves to 6 × with near-perfect signal fidelity, and up to 10 × is reached with acceptable signal degradation. It delivers fast throughput (100–200 MB s−1 using a single-thread and up to 750 MB s−1 using 8-threads), enabling real-time deployment even under high data rates. We validated its performance on 15 datasets from a variety of acquisition environments, demonstrating its speed, robustness, and broad applicability. DASPack provides a practical foundation for long-term, sustainable DAS data management in large-scale monitoring networks.

SummaryInitial stress exerts a crucial impact on the elastic properties and thus the wave reflection in the layered media. However, the stress effect on wave reflection characteristics in such media remain insufficiently understood. To address this issue, we develop a composite matrix reflectivity method incorporating initial overburden stress (CMRMS) by means of acoustoelasticity theory, enabling accurate modeling of seismic wave propagation in stressed layered media. The proposed method can better simulate multiple reflections, converted waves and transmission loss of seismic waves in layered media, compared to the classic stress-dependent reflection coefficient equation for a single interface. Moreover, our method can degenerate into the existing methods in the cases of no initial stress and single interface, which verifies its correctness. We further extended the CMRMS to elastic and viscoelastic non-welded interfaces using the linear-slip theory and standard linear solid model, respectively. The extended method is used to investigate the impacts of non-welded interface compliance, overburden stress, fluid viscosity and frequency on seismic reflection characteristics within layered model. It is shown that the stress effect magnitude on interface reflection significantly depends on the interface depth, due to cumulative transmission losses from overlying layers. Moreover, increasing either the compliance or the number of overlying non-welded interface significantly reduces the reflection amplitude at deeper interface. Our results show the potential of the proposed composite matrix reflectivity method to consider the joint effects of initial stress, multiple waves and transmission loss in both forward modelling and inverse applications.

AbstractThe low-velocity layer confined by surrounding rocks deep in the subsurface acts as a seismic waveguide. The compressional (P-) and shear (S-) waves propagate in the waveguide are reflected on the top and bottom interface, constructively interfered with to formulate the deep-guided wave. Deep-guided wave has high-frequency contents and notable dispersive features. The dispersion represents the kinematics information and can be used to image the low-velocity structures. The Earth media not only shows elasticity but also attenuates seismic waves. This article presents a theoretical study of deep-guided wave propagation and dispersion analysis in viscoelastic media. We utilize the Thomson-Haskell propagator matrix method to theoretically calculate the phase velocity dispersion and attenuation curves of the deep-guided wave in viscoelastic media. We apply the staggered-grid finite-difference scheme to numerically simulate the elastic wavefield propagation in the shale layer for validation. We have conducted a sensitivity analysis of the dispersion and attenuation curves of the deep-guided wave with respect to different media parameters. The theoretical calculation of dispersion and attenuation curves of deep-guided wave opens the doors for the simultaneous inversion of S-wave velocity and quality factor of the low-velocity layer in the future. Deep-guided waves hold the potential for high-resolution imaging of hydrocarbon reservoirs, geothermal reservoirs, coal seams, saline aquifers, and fault zones.

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.