Geophysical Journal International

SummaryAccurate earthquake hypocentres are fundamental to a wide range of geophysical studies, yet source depth remains poorly constrained in teleseismic earthquake catalogues. Near source surface reflections such as pP, sP, and sS (known as depth phases) provide critical information for resolving hypocentral depth, particularly for intermediate-depth earthquakes. The number of depth phases reported by global earthquake monitoring agencies has declined significantly in recent decades, potentially reducing the precision of resolved earthquake depths. To address this, we automatically detect P, pP, sP, S and sS phase arrivals using teleseismic ad-hoc arrays. We detect these phases for earthquakes in the South American Subduction Zone (SASZ) at depths of 40–350 km and between mb 4.7 to 6.5. The identified phases are integrated with the phases reported to the ISC Bulletin, and used to relocate earthquakes with ISCloc. We assess the impact of incorporating automatically detected, ad-hoc array-derived depth phases on earthquake relocations across the SASZ, and find an improvement in depth resolution for 88.8% of earthquakes. Using this enhanced catalogue we investigate the structure of the Wadati-Benioff zone, focusing on two significant earthquakes: the 2005 Mw 7.7 Tarapacá and 2019 Mw 8.0 Peru events. Finally, we successfully apply our methodology to deep focus earthquakes (350-700 km), which further define the deepest portion of the seismogenic slab. Our results demonstrate the potential for automatically detected, ad-hoc array-derived depth phases to substantially improve the accuracy of teleseismic earthquake hypocentres, and offer further constraint upon slab geometry and seismogenic structure.

SummaryThis study aims to retrieve P waves from seismic ambient noise recorded by a dense local broadband network at the Chémery underground gas storage site, where anticline deformation was previously identified through wells and seismic reflection survey. To this end, we propose a new approach for reconstructing P waves from ambient noise. We process the passive seismic data to reconstruct the body wave component of the empirical Green’s functions (EGF). The retrieved P-wave arrivals were identified and analyzed, revealing that in this dataset, the picked arrival times likely correspond to non-physical head waves rather than direct or diving P-wave arrivals between virtual sources and receivers. Numerical simulations support this idea of non-unique interpretation of the passively reconstructed P-wave arrivals. The simulations suggest the potential for mapping lateral heterogeneities above the critical refractor as a cumulative time-delay, although for this dataset the anticline-induced time-delay is likely within the measurement uncertainties. It is found that the dominance of non-physical head waves over diving waves is primarily due to the large distance from the network to ambient noise sources.

SummaryOceanic subduction zone is the dominant pathway for transporting carbon into the interior of the Earth, and thus plays a critical role in deep carbon cycling. Despite being recognized as a key mechanism for carbon release in subduction zones, the metamorphic decarbonation outflux and efficiency remain subjects of ongoing debate. The thermal structure of subduction zone is widely recognized as a primary dynamic control on metamorphic decarbonation, however, the quantitative relationship between metamorphic carbon outflux and simplified thermal parameters of subduction zones (here defined as φ= slab age × subduction velocity/100 in kilometer) remains poorly constrained. On the other hand, previous studies on metamorphic decarbonation have been conducted within two distinct scenarios: the P-T-dependent decarbonation (PTD) system versus P-T-H2O-dependent decarbonation (PTHD) system, yet a quantitative comparison between these two scenarios remains lacking. In order to investigate the metamorphic decarbonation behavior of subducting slab in the PTD versus PTHD systems, we develop a coupled thermo-petrological model by integrating the thermodynamic dataset of temperature-pressure-(H2O)-dependent CO2 content into the thermal model of subduction zones. Systematic numerical models indicate that the metamorphic carbon outflux in the PTHD system is about 50 per cent lower than that predicted in the PTD system. Meanwhile, the quantitative functional relationship has been built between the metamorphic carbon outflux and φ, which reveals that the decarbonation outflux and efficiency decrease exponentially with increasing φ in both systems. Under present-day widespread subduction thermal conditions with the φ values of around 30 km, both PTD and PTHD system models yield low metamorphic decarbonation efficiency, suggesting that a substantial proportion of slab carbon is likely retained in the slab and transported into the deeper mantle.

SummaryThe Sichuan Basin in China has experienced a number of devasting earthquakes in the past 20 years, particularly on the Longmen Shan fault (LMSFZ) with the 2008 Wenchan and 2013 Luschan events. This study employs a hierarchical, four-dimensional (latitude, longitude, depth, time) clustering framework to characterize seismic activity in the Sichuan Basin. After the identification of spatial features of the region (e.g., faults), we then apply two cluster algorithms on the Longmen Shan fault data and compare the identification of the 2008 and 2013 events. In particular, we apply and compare Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Bayesian Gaussian Mixture Model (BGMM) on the identification of mainshock-aftershock sequence (as well as any foreshock events). By applying temporal clustering to the dataset and comparing DBSCAN and BGMM methods, we find distinct differences between the results. Specifically, we find that DBSCAN identifies a simple mainshock-aftershock sequence, while BGMM produces a more complex foreshock-mainshock-aftershock sequence. However, both scenarios have been identified within previous work on these events, highlighting that additional analysis is required and that single cluster algorithms should be applied with caution. The work here in comparing machine learning techniques within an integrated clustering framework is timely and will serve as a guide for more in-depth analysis on earthquake patterns and fault dynamics using these methods.

SummarySurface fibre-optic distributed acoustic sensing (S-DAS) typically requires trenching to achieve adequate coupling, which can be challenging and costly in hardrock environments. As an alternative, untrenched S-DAS offers significant time and cost savings, though at the expense of data quality. In this study, we systematically evaluated the impact of untrenched deployment on DAS data quality through a multi-method comparison with conventional sensors, including three-component geophones and vertical-component accelerometers. All recorded data were converted to particle velocity to enable direct amplitude comparisons across arrays. Phase fidelity was assessed using the surface-wave method, cross-power spectral analysis, and ambient noise interferometry. Untrenched S-DAS recorded amplitude levels that differed from those of conventional sensors, particularly above 50 Hz. However, within the surface-wave band (up to 35 Hz), the data quality was sufficient to derive reliable shear-wave velocity profiles, especially when the data were resorted to common-receiver gathers. Sensitivity and coherence decreased significantly at higher frequencies and larger offsets, and a systematic time delay was observed for DAS in the surface-wave band. Ambient noise interferometry was ineffective for the untrenched DAS array, largely due to variable channel coupling and system-specific noise. This study provides a systematic field comparison of untrenched S-DAS and conventional sensors in hardrock settings, outlining both the limitations and the practical potential of this cost-effective deployment method.

SummaryFaults and fractures heal and seal over time, decreasing along-fault permeability, and increasing reactivation stress. This presents a dilemma in geothermal reservoirs as maintaining permeability is crucial for reservoir longevity, but the reactivation of faults to increase permeability can also cause hazardous seismicity. The healing rate of faults is temperature-dependent and shows significant differences under wet and dry conditions. We investigate the healing behavior of a bare, water-saturated fault surface at temperatures up to 163°C through slide-hold-slide experiments. The gneiss sample from the UtahFORGE geothermal demonstration project, is continuously actively probed with P-waves and monitored for passive acoustic emissions radiating from the fault. Our data show that with increased temperatures, the fault surface friction decreases, healing rate increases and the fault becomes more prone to unstable slip. The decrease in friction and increase in healing rate we measure are larger and occur at lower temperatures than previously demonstrated. P-wave amplitudes and P-wave velocities increase during healing, with amplitudes sensitive to temperature but velocities conversely insensitive. We attribute this to a sensitivity of the P-wave amplitude to changes in contact area with P-wave velocity correlating with mechanical compaction, off-fault microcracks, and the formation of wear products during sliding. The sample continues to creep throughout holds during our hotter experiments, but the creep motion does not erase continuous healing. Acoustic emissions spike upon slip reactivation, where higher event rates and higher slip velocities occur as healing progresses—after longer hold times and at higher temperatures. The amplitude of the P-wave, as well as the acoustic emission rate, show precursory signs of spontaneous reactivation and therefore might have potential in forewarning slip.

SummaryWe present a new, variational, fully nonlinear, probabilistic ambient noise tomography method, which estimates subsurface structure and quantifies the corresponding uncertainties directly in three dimensions (3D) from inter-receiver seismic surface wave dispersion data. We use the method to invert for high resolution 3D seismic velocity models of the upper crust beneath Great Britain using seismic ambient noise data recorded around the region – a task that proved too high-dimensional and hence computationally demanding for Monte Carlo sampling to converge to a stable solution. We compare the inversion results from the new method to those obtained from two standard, indirect inversion methods, in which 2D (geographical) surface wave velocity maps and 1D (depth) shear velocity profiles are estimated in two separate, consecutive steps. The results show that the direct-3D scheme preserves better lateral continuity and produces better data fit than the two-step methods, and provides information about lateral correlations that is absent from the two-step solutions. The inversion results are consistent with large-scale geology of Great Britain, and for the first time provide seismologically-imaged evidence of the Great Glen Fault and other major tectonic faults. We therefore propose that direct-3D inversion schemes should be used where possible for surface wave inversion as they provide improved results at little additional computational cost.

SummaryAccurate three-dimensional coseismic deformation fields are critical for fault mechanics analysis and hazard assessment, but the sparse distribution of Global Navigation Satellite System (GNSS) stations often limits reconstruction accuracy. This study proposes Integrated Dislocation and Strain Models (IDSM) that seamlessly integrate GNSS and Interferometric Synthetic Aperture Radar (InSAR) data. This is achieved by combining a surface-constrained strain model and a subsurface-constrained dislocation model, which adaptively optimizes multi-source data weights through Variance Component Estimation (VCE), challenging the traditional reliance on uniformly distributed observations. Simulation experiments demonstrate that under insufficient GNSS coverage, this method improves deformation recovery accuracy by 10 per cent to 70 per cent in the vertical, north, and east components compared to the ESISTEM-VCE (Extended Simultaneous and Integrated Strain Tensor Estimation from Geodetic and Satellite Deformation Measurements-VCE) method, with particularly significant enhancement in the north component. Applied to the 2021 Yangbi MW6.4 and Maduo MW7.4 earthquakes, the study reveals distinct deformation patterns: the Yangbi event exhibits right-lateral strike-slip rupture with a maximum east-west extensional displacement of 87 mm and vertical subsidence of 59.8 mm, showing antisymmetric horizontal deformation around the epicenter. In contrast, the Maduo earthquake is dominated by left-lateral strike-slip motion, with east-west displacement reaching 1.4 m, while north-south and vertical deformations display patchy distributions along the fault. Error analysis confirms accuracy improvements over the ESISTEM‑VCE method. For the Yangbi earthquake, the Root Mean Square Error (RMSE) decreased by 50 per cent (east), 64 per cent (north), and 44 per cent (vertical) at GNSS validation points. Corresponding improvements of 6.1 per cent (east) and 53.5 per cent (north) were achieved for the Maduo earthquake.

SummaryOceanic transform faults (OTFs) have long been viewed exclusively as vertical, strike-slip structures offsetting mid-ocean ridges, yet their deep geometry and structural complexity remain poorly constrained. Thus, key questions persist, including whether OTFs are single-stranded and continuous, whether they maintain vertical dip angles, if they accommodate mixed-mode slip, and what factors control their geometry. This study addresses these questions through a global statistical analysis of teleseismic earthquake focal mechanisms from 150 OTFs across diverse tectonic settings. We introduce stack maps, a novel method that quantifies fault dip and rake, providing a graphical representation of average focal mechanisms. Our findings reveal that while OTFs tend to conform to the standard vertical, strike-slip model, nearly half exhibit deviations, either in dip or motion, challenging the classical view of these plate boundaries. We identify four distinct OTF categories: (1) those adhering to the standard model, (2) non-vertical faults with transtensive/transpressive components, (3) non-vertical faults accommodating strike-slip motion, and (4) vertical faults with a vertical component of motion. Tectonic regime shifts emerge as a primary driver of structural changes, with non-vertical geometries persisting even after the regime reverts to pure strike-slip motion. This structural memory suggests that fault geometry, once established, remains stable over geological timescales of several tens of Myr. By reconciling previously ’unusual’ focal mechanisms with fault structure and dynamics, this work demonstrates that global seismic catalogues, when analysed statistically, offer robust insights into OTF geometry and tectonic regimes.

SummaryAs a critical category of geophysical data, magnetic anomalies play vital roles in geological interpretation, resource exploration and target detection. For most applications involving magnetic anomaly data, the ideal dataset should have uniformly distributed data points, high resolution and completeness without gaps. However, because of the environmental constraints and measurement limitations, magnetic anomaly data obtained from real-world measurements often fail to meet these requirements. Thus, interpolation techniques present effective and cost-efficient technical approaches for processing measured magnetic anomaly data to meet the aforementioned criteria. To our knowledge, current research on magnetic anomaly data interpolation has primarily focused on gridding methods for interpolating irregularly sampled data into gridded data and super-resolution interpolation methods aimed at enhancing spatial resolution. Meanwhile, studies on interpolation methods specifically designed to fill large-area data gaps remain relatively scarce. To address the challenge of reconstructing large-area missing magnetic anomaly data, we propose a data-driven method for magnetic anomaly data gap filling. First, based on the analysis of the characteristics of magnetic anomaly data, we construct an open-source magnetic anomaly interpolation dataset (MAID) specifically designed for magnetic anomaly data interpolation tasks. Subsequently, we develop a magnetic anomaly data gap-filling generative adversarial network (MADGF-GAN) tailored for magnetic anomaly data gap filling. Upon sufficient training on the MAID training set, MADGF-GAN can directly fill gaps in given magnetic anomaly data. Finally, the effectiveness of MADGF-GAN is validated using four test samples from the MAID test set and Afghan aeromagnetic data. Compared with four existing interpolation methods, MADGF-GAN demonstrates considerable advantages in terms of interpolation accuracy, computational efficiency and practicality. This study demonstrates the potential of data-driven approaches in magnetic anomaly data processing, providing crucial technical support for related geoscientific applications.

SummaryBioleaching is a biologically facilitated process that helps to dissolve valuable metals in order to extract them from the mineral gangue. Applied in the field to heap ores, its efficiency mainly depends on solution flow inside the heterogeneous heaps, which is often tortuous and can remain stagnant in the pores and crevices between the particles. Methodologies that can help to monitor the bioleaching processes are therefore needed to improve operational efficiency. In this article, we present for the first time preliminary laboratory-scale investigations on spectral induced polarization (SIP) during the bioleaching of chalcopyrite (CuFeS2) containing ore material from a mine in Chile. Two column experiments representing different stages of the bioleaching process were monitored under un-saturated and highly acidic environment (pH ~2). Our objective was to explore the feasibility of SIP for detecting changes in electrical properties potentially associated with bioleaching-induced mineral dissolution and alteration. The results show a rapid decrease in SIP phase shift and imaginary conductivity during the early stage of bioleaching, while the real conductivity remains relatively stable. At a more advanced stage of bioleaching, the phase response is weaker and more stable. A relaxation time distribution (RTD) analysis was applied to further investigate changes in polarization mechanisms. Prior to bioleaching, the RTD exhibits a well-defined peak consistent with polarization controlled by sulfide mineral grains, whereas after one month of bioleaching the RTD broadens and shifts toward larger relaxation times, accompanied by a decrease in chargeability. This combined evolution suggests bioleaching-induced modifications of electrochemically active surfaces, potentially related to mineral dissolution and the formation of passivation layers. Estimated particle sizes derived from the RTD analysis are consistent with scanning electron microscopy observations. Although, the absence of a dedicated abiotic control column prevents us from attributing these changes unambiguously to bioleaching alone, these results highlight the potential of SIP as a non-invasive, real-time and integrative tool to monitor leaching processes and to identify zones that may remain weakly affected by leaching.