Geophysical Journal International

SummaryThe Southern Apennines—Northern Calabrian boundary is a region marked by lithological heterogeneity, complex geodynamics and tectonics, and prone to significant seismic hazard. This sector is part of a complex geodynamic system, where Africa-Eurasia convergence, Ionian subduction, and slab retreat coexist. Its structure and seismic activity derive from extensive lithospheric heterogeneity and fluid-related processes, both of which are poorly constrained. Here, we present a novel application of seismic attenuation and scattering tomography of the area at a regional scale. We estimated seismic wave attenuation and scattering for the Southern Apennines—Northern Calabria region using a dataset of 1581 waveforms related to 95 M ≥ 3.0 earthquakes that occurred between 2004 and 2024 and were recorded at 32 stations. We constrained the heterogeneous properties and fluid saturation of the Southern Apennines—Northern Calabrian region by mapping P-wave Peak Delays and inverting coda-normalized energies for total attenuation (1/Q). Results consistently reveal different seismic energy dissipation mechanisms between the two domains, reflecting their different characteristics in terms of Peak Delay and attenuation patterns. The Southern Apennines exhibit high Peak Delay values at all depths and almost no remarkable total attenuation anomalies, consistent with weakly consolidated, fractured sedimentary sequences and limited fluid content. Nevertheless, at a depth of 5.4 km, a relatively high attenuation pattern is detectable, likely linked to the presence of less cohesive and potentially fluid-saturated units. Conversely, Northern Calabria shows low Peak Delay and high attenuation in the investigated depth range, reflecting wave propagation through coherent crystalline rocks with significant fluid circulation, likely favored by overpressurized materials or active migration pathways. The spatial correlation between high attenuation, low seismic velocities, and thermal anomalies shows that fluids modulate seismic wave behavior, providing new constraints on the crustal structure and seismotectonic segmentation of the region. The joint interpretation of our results with other geophysical models and responses highlights the complex interplay between lithology, tectonics, and fluid dynamics across this critical segment of the central Mediterranean.

SummaryThe earthquake fault as observed by seismic motion primarily manifests as a surface of displacement discontinuity within a linear elastic continuum. The displacement discontinuity and the surface normal vector (n-vector) of this idealized earthquake source are measured by the tensor of potency, which is seismic moment normalized by stiffness. We exploit this theoretical relation to formulate an inverse problem of reconstructing a smooth, three-dimensional fault surface from an areal density field of the potency tensor. In this problem, the surface is represented by an elevation field that parametrizes the vertical variation of the surface relative to a reference, and the nodal planes of a given potency-density-tensor field describe the n-vector field. The remaining subject is the n-vector-to-elevation transform, the operation inverse to defining the n-vector field on a given surface. Whereas this transform is a well-posed one-to-one mapping in two dimensions where the n-vector has one degree of freedom, the transform becomes overdetermined in three dimensions because the n-vector has two degrees of freedom while the scalar elevation has only one, generally admitting no solution. This overdetermination originates from a reduction in degrees of freedom from six to five upon modeling the source as a displacement discontinuity rather than general potency density, namely inelastic strain. The sixth degree of freedom unmodeled by displacement discontinuities and n-vectors manifests as a local violation of the determinant-free constraint in point potency sources; however, in areal sources of potency density, it raises a conflict with the global consistency of the n-vector field. Recognizing that this conflict derives from the capacity of the potency-density-tensor field to describe inelastic strain source incompatible with displacement discontinuity on a surface, we explicitly introduce an a priori constraint to define the fault surface as the smooth surface that best approximates the surface distribution of inelastic strain by displacement discontinuity. We derive an analytical solution for the surface reconstruction thus formulated and demonstrate its ability to reproduce smooth three-dimensional surfaces from synthetic noisy n-vector fields. Lastly, we integrate the derived formula into the potency density tensor inversion and validate it in an application to the 2013 Balochistan earthquake. The estimated fault geometry agrees better with the observed fault trace than that of the previously proposed quasi-two-dimensional surface reconstruction, highlighting the importance of accounting for three-dimensional fault geometry.

SummarySimulating the behavior of geological materials represents a fundamental objective in geophysical research. To achieve this goal, various models have been developed for different scenarios. While continuum models based on continuum mechanics are most commonly employed, non-continuum approaches such as the discrete element model and the lattice model have also been developed to address the pervasive discontinuities inherent in geological materials. However, existing non-continuum models are predominantly limited to isotropic conditions, significantly constraining their applicability. The dynamic lattice method proposed in this study aims to overcome this limitation. By independently assigning elastic properties to lattice bonds based on their spatial orientation, we have successfully introduced anisotropy into a three-dimensional lattice model. The linear relationships between the lattice model parameters and their continuum counterparts are established in terms of elastic properties. This advanced three-dimensional lattice model has been effectively applied in elastic seismic wave simulations in arbitrary anisotropic media.

SummaryThe singularity points are very common in the low-symmetry anisotropic media. The presence of these points results in complications of the wave fronts (or group velocity images) for waves forming the singularity points. We show the effect of singularity points in multilayered anisotropic media with triclinic symmetry.

SummaryQuantification and control of the in situ mechanics of calcite precipitation in the subsurface are notorious problems often encountered in hydrogeological and engineering applications. Difficulties arise here due to the general inaccessibility and texture of pore spaces, as well as the precipitation reaction’s dependence on fluid chemistry and the composition of the pore surfaces. To mitigate the uncertainties introduced by these inaccessible variables, we propose the use of spectral induced polarization (SIP) as a non-invasive tool to gain insight into the textural and electrochemical parameters controlling the precipitation rate within confined pore spaces and incorporate the gained information into a reactive transport model for quantification. We present SIP monitoring data from three laboratory experiments on diffusive mixing, inducing CaCO3 precipitation in sandstone. During the experimental runs, we identify a clear pattern showing the onset of the chemical reaction in the low-frequency (< 0.1 Hz) response of the imaginary conductivity and the formation of an associated high-frequency peak (> 10 Hz) in the later stages of the experiment. The changes to pore space geometry and precipitation yield were estimated with multiple independent methods. Using information gained from the monitoring data, we predict the dynamics of the precipitation reaction by including textural information, the inner surface area, and the grain size of the precipitate, as well as constraints on the effective diffusivity. These parameters were determined for each sample, based on empirical relations to the polarization response, and incorporated into an accompanying reactive transport model (phreeqc). The experimental results highlight the benefits SIP monitoring can provide to reactive transport models, even if precipitation yield is close to the detection limit of commonly applied methods, such as X-ray powder diffraction or fluorescence.

SummaryPrevious studies of the 2021 Mw 7.4 Maduo earthquake have primarily focused on the early postseismic phase, while the dominant mechanisms driving postseismic processes and the seismic moment released by afterslip remain debated. Longer-term observational constraints are needed to address these issues. In this study, we integrate ~3.5 years of postseismic InSAR and GPS time series data to effectively separate the contributions of afterslip and viscoelastic relaxation. The results show that afterslip released a cumulative seismic moment of approximately 3.91 × 1019 N·m, accounting for ~23.3 per cent of the coseismic moment—equivalent to a new Mw 7.0 earthquake. The optimal steady-state and transient viscosities of the lower crust are estimated to be 1.35 × 1019 Pa·s and 1.5 × 1018 Pa·s, respectively. Afterslip remains the dominant mechanism driving near-field deformation throughout the observation period, while viscoelastic relaxation governed far-field deformation beginning about 4 months after the mainshock. The stress-driven afterslip is comparable with the inverted kinematic afterslip, and poroelastic rebound is negligible. These findings provide valuable insights into stress perturbations on surrounding faults induced by the coseismic rupture, afterslip, and viscoelastic relaxation, and offer new constraints on the recurrence interval of Mw 7.4 earthquake on the Jiangcuo Fault.

SummaryMachine learning models offer powerful predictive capabilities for geoscientific applications but remain limited by their ”black-box” nature and lack of rigorous uncertainty quantification. We developed a comprehensive, generalizable uncertainty quantification framework that decomposes predictive uncertainty into aleatoric and epistemic components using Quantile Regression Forests. Additionally, we applied unsupervised k-means clustering to isolate homogeneous data regimes, thereby reducing aleatoric uncertainty across spatially heterogeneous geoscientific datasets. To facilitate interpretation and quality assessment, we introduced five spatial diagnostic tools: bandwidth, variance, robustness, confidence, and explainability maps that characterize prediction reliability and identify dominant uncertainty sources. To demonstrate the framework’s applicability, we tested it on three synthetic datasets varying in size and a real-world geothermal heat flow application with 14 geophysical observables across continental Africa. Results show that clustering substantially reduces aleatoric uncertainty while maintaining stable epistemic uncertainty. Clustering also improves predictive accuracy and sharpens prediction intervals, with gains most pronounced in homogeneous regions. Applied to the African geothermal heat flow, the framework reveals region-specific geological controls (lithospheric architecture dominates stable cratons, while tectonic proximity governs active rift zones) and guides targeted data collection by distinguishing high-epistemic regions requiring additional sampling from high-aleatoric zones needing improved observables. While theoretically applicable to other geographic regions and geophysical datasets, the framework’s performance in different geological settings requires validation. This interpretable, uncertainty-aware approach enhances trustworthiness of predictions in spatially heterogeneous, data-sparse geoscientific problems.

SummaryLower crustal high-velocity bodies (LCHBs) are key indicators of deep magmatic addition and lithospheric modification at rifted continental margins. Integrating 3D gravity modeling with regional geophysical and geological constraints, we identify a prominent LCHB beneath the Xihu Sag of the East China Sea (ECS) shelf basin. This body is NNE–SSW elongated, ~5–7 km thick, and spatially coincides with major depocenters and fault systems. We propose a two-stage mafic emplacement model linking its formation to the tectonic transition from fore-arc compression to back-arc extension. During the early–mid Cretaceous, compressional subduction of the Paleo-Pacific Plate facilitated arc-related underplating and accumulation of mafic material in the lower crust. In the early Cenozoic, slab rollback and asthenospheric upwelling during back-arc extension renewed melt supply, further thickening the lower crust. The absence of surface volcanism indicates that magmas were largely trapped and crystallized at depth, forming dense mafic cumulates. Present-day low shallow-mantle temperatures and high densities beneath the Xihu Sag suggest that preservation of these cumulates was sustained not solely by mantle thermal conditions, but also by prolonged subsidence, sedimentary insulation, and inherited compressional structures. These results underscore the need to integrate tectonic, thermal, and structural factors to fully understand deep magmatic processes in marginal basins.

SummaryWe develop a novel comprehensive theoretical framework, the Biot-patchy-spherical-squirt (BIPSSQ) model, for wave propagation in partially saturated dual-porosity media. This model simultaneously incorporates three key fluid flow mechanisms: macroscopic flow (Biot flow or global flow), mesoscopic flow, and microscopic flow (three-dimensional spherical squirt flow). The constitutive relations and fluid pressure expressions for the BIPSSQ model are first derived and then the governing wave equations are established using a Lagrangian approach based on the system’s kinetic energy, potential energy, and dissipation functions. Through plane wave analysis, we obtain the phase velocity and attenuation of the fast P-wave. Numerical examples demonstrate that the BIPSSQ model predicts multiple dispersion transition bands and corresponding attenuation peaks, attributed to two squirt flows and two Biot global flows from two immiscible fluids. Furthermore, the presence of squirt flow significantly suppresses the mesoscopic patchy saturation effect, leading to the disappear of mesoscopic dispersion transition band and attenuation peak. The influences of permeability, saturation, porosity, squirt-flow length and inclusion radius on velocity dispersion and attenuation are also analyzed. Finally, excellent agreement between theoretical predictions and experimental measurements from an Aksu outcrop rock sample (800 kHz), a gas-water-saturated Estaillades limestone (1 kHz), and an oil-brine-saturated Vosgian sandstone (350 kHz), validates the applicability and effectiveness of the BIPSSQ model. Moreover, the BIPSSQ model can degenerate to other theories (i.e. Biot, BISSQ, BR) under certain conditions. Our proposed model provides a unified and robust tool for interpreting wave propagation phenomena in complex, partially saturated reservoir rocks.

SummaryThe maximum possible earthquake magnitude (${{M}_{MAX}}$) is a consequential parameter that is difficult to quantify. In this paper, order statistics concepts are adapted to infer ${{M}_{MAX}}$ from an earthquake catalogue. Examining jumps in the ordered sequence of largest events significantly improves inferences of ${{M}_{MAX}}$ truncation; I continue this improvement by considering deeper metrics (i.e., jumps in the second, third, fourth, … largest events). I begin by providing a theoretical foundation for these deeper metrics, while highlighting special cases. Synthetic tests are performed to quantify the improvements gained. While the largest information gains arise from the largest event sequence, appreciable gains are found to depths of ten. This approach is also validated on real-data cases, such as Groningen and FORGE, demonstrating their utility. Overall, this approach will contribute to better understanding earthquake hazards and discerning the physical processes that allow earthquakes to grow large.

SummaryThe Ojos del Salado Volcano, the highest active volcano in the world, is located at the southern end of the Puna plateau in central Chile. Here, the subduction angle of the down-going Nazca plate shallows, causing volcanism to move inland marking the southern end of the Central Andean Volcanic Zone (CAVZ). Little is known about the current volcanic activity at this southern edge or the dominant crustal stresses at these volcanic centres. In this study, we use a temporary network of 29 geophones to record local seismicity at the Ojos del Salado volcano. The type of seismic event, number of events per day, location, and magnitudes of events all provide insight into the structure, material properties, and activity level of the volcano. Between February 6th and 28th 2024, this network recorded 93 events with local magnitudes larger than 0, the largest having local magnitude 2.8. The events formed two main clusters, one on the western flank of Ojos del Salado itself near the summit, and a smaller cluster to the north. Most events in the northern cluster occurred within a 35 minute seismic swarm on February 8th. Twenty-one fault plane solutions were determined for events within the network. Six of these occurred during the northern swarm and showed steep oblique faulting and fifteen in the summit cluster, which mainly show normal faulting with strikes comparable to E-W oriented mapped faults in the area. Fault plane solutions at both clusters indicate a north-south extensional stress state. This agrees with the regional stress axes of the southern Puna plateau found in other studies, suggesting that the local crustal stresses at the Ojos del Salado volcano mainly follow the regional stresses with some variation in fault planes near the summit and in the northern swarm that could be due to locally high magmatic or geothermal fluid stresses. Heavy rain in the days preceding the northern swarm may have increased the amount of fluid available, potentially inducing the swarm on February 8th. No seismicity was observed near the Laguna Verde, or the two smaller volcanoes within the network: the Barrancas Blancas and Mulas Muertas. Ojos del Salado is therefore the main source of seismic activity and likely heat source within the study area. The level of seismicity and the occurrence of a seismic swarm to the north and five small seismic swarms near the summit suggest that there is still volcanic activity at Ojos del Salado and it could benefit from monitoring.

SummaryThe eastwards extrusion of Tibetan Plateau (TP) materials has led to complex tectonic deformation and frequent seismicity in the western Sichuan Basin (SCB). To elucidate crustal deformation mechanisms and seismogenic structures, we inverted broadband (3–60 s) Rayleigh wave dispersion curves using ambient noise tomography from 448 stations and constructed a 3-D S-wave velocity (Vs) structure for the upper to middle crust beneath the SCB and adjacent regions. Our model revealed a thick, low-velocity sedimentary layer within the SCB that extends to 15 km depth along its northwestern margin, likely resulting from the accumulation of eroded materials from surrounding orogenic belts. The three-dimensional velocity model resolved sedimentary cover thicknesses ranging from 6 to 13 km within the basin and yielded average Vs values of 3.08, 3.17, and 3.25 km/s for Mesozoic, Palaeozoic, and Proterozoic strata, respectively, thereby calibrating the basement burial depths of major geological units in the sedimentary layers. Notably, this study identified deep low-velocity anomalies beneath the Dayi seismic gap (DSG) and segmented velocity structures along the Kangding–Shimian section, providing crucial deep structural constraints for evaluating the seismogenic environment and future earthquake hazards of major seismic gaps in the Sichuan–Yunnan region. The velocity structure clearly delineates the formation and evolutionary characteristics of multiple foreland basin development episodes since the Late Triassic, offering important constraints for understanding the deep structure of the SCB, assessing seismic hazard risks, and guiding petroleum resource exploration.

SummaryHigh-resolution P-wave velocity tomography of the Japan subduction zone down to 700 km depth is determined by conducting a joint inversion of arrival-time data of local earthquakes and teleseismic events, which were recorded at land-based Hi-net seismic stations and seafloor S-net stations. Our inversion results show the high‐velocity subducting Pacific slab and low‐velocity zones in the mantle wedge beneath active arc volcanoes. Subslab low-velocity anomalies (SLVAs) are revealed in the mantle below the Pacific slab, which may reflect hot and wet mantle upwelling derived from return flow associated with the slab deep subduction. The SLVAs at depths of ~150-260 km exhibit a bimodal distribution, where interplate slow earthquakes occur. There is a SLVA gap below the mainshock hypocenter and rupture zone of the great 2011 Tohoku-oki earthquake (Mw 9.0). The SLVAs may influence the megathrust segmentation by their buoyancy, heat, and melt, and so affect the generation of megathrust and intraslab earthquakes. These results shed new light on the structural heterogeneity and mantle dynamics of the Japan subduction zone.

SummaryThe cycle-skipping problem that plagues full waveform inversion (FWI) can be at least partially mitigated if low frequencies (which encode the kinematics of wave propagation in seismic data) are recorded. However, seismic sources and receivers are band-limited, so seismic data doesn’t generally include signals down to 0 Hz. To improve our ability to solve the seismic inverse problem, one can synthesize this missing low-frequency (LF) content from the recorded high-frequency (HF) data using machine learning (ML) models. Deep learning models such as convolutional neural networks (CNNs) demonstrate impressive ability to perform low frequency extrapolation. However, such models require powerful hardware (GPU machines) and careful training. We assess the extrapolation capabilities of three different ML models that do not require GPU machines, namely, random forest, Gaussian process regression, and gradient boosting, on both synthetic and real data. Experimental results on two synthetic datasets (generated from a low velocity lens embedded in a homogeneous medium, and the Marmousi model) demonstrate that FWI applied to the extrapolated data consistently improves inversion accuracy relative to FWI applied to the original datasets that do not contain low frequencies. Application of low-frequency extrapolation to real data from the Northwest Shelf of Australia demonstrates that tree-based ML models such as gradient boosting can outperform CNNs in terms of both accuracy and computational cost on non-GPU architectures.

SummaryThis study quantifies the spatial heterogeneity of nonlinear signals, background noise, and vertical velocities in GNSS vertical time series across the Tibetan Plateau (TP), using multi-source loading corrections to isolate tectonic deformation. We analyzed 20 years of GNSS data (2002–2021) from CMONOC and NGL networks, processed via GipsyX and referenced to ITRF2014. Non-tidal atmospheric (NTAL), oceanic (NTOL), and hydrological (HYDL) loading effects were applied utilizing operational models from GFZ and GRACE mascon data (CSR/JPL/GSFC), followed by common mode error (CME) filtering. The findings highlight significant spatial heterogeneity: Monsoon-dominated southern TP exhibits 10–20 per cent RMS reduction after non-tidal atmospheric-oceanic (AO) loading corrections, while northern TP shows minimal improvement (<10 per cent), highlighting non-atmospheric noise dominance. Integration of AO and GRACE-modeled hydrological (AOG) loading corrections outperform soil moisture-based models (AOH), achieving 25–35 per cent RMS reduction in glacier-covered Himalayas by resolving cryospheric mass loss. Spectral and principal component analysis (PCA) analyses confirm AOG’s superiority in suppressing interannual signals (PC1 variance: 62.7 per cent vs. AOH’s 60.3 per cent), particularly in monsoon-ENSO-affected regions. Noise modeling demonstrates high spatiotemporal correlations (63.1 per cent WN + FN in raw data), with flicker noise (FN > 5.2 mm) linked to seismic activity in southeastern TP and power-law noise (PL > 3.5 mm) to permafrost dynamics in the north. Post-AOG_CME processing simplifies noise structures (WN + GGM dominance: 32.9 per cent), reducing velocity uncertainties by 26.9 per cent and revealing a residual + 1.2 mm/yr uplift in the southern inner TP, indicative of mid-crustal flow. Persistent uncertainties (>0.55 mm/yr) along the Himalayan thrust front correlate with deep lithospheric boundaries. Our findings demonstrate the necessity of integrating GRACE-derived corrections with CME filtering to accurately delineate tectonic signals within the intricate suture zones of the TP, offering crucial insights into plateau-wide geodynamic processes.

SummaryEarthquake ground motion is strongly influenced by near-surface geology, which governs its amplification, duration, and spatial variability. Under intense shaking and depending on the material strength, sediments often exhibit nonlinear behaviour, producing large deformations that reduce shear-wave velocity, shift resonance frequencies, and increase damping. We analyse over two decades of borehole-surface recordings from 28 stations in Iwate Prefecture, Japan, collected by the Kiban Kyoshin network (KiK-net), to quantify these effects. Frequency-domain analysis (stacked Stockwell power spectral density) and time-domain interferometric methods (multitaper deconvolution and phase cross-correlation) provide consistent results, revealing systematic decreases in both resonance frequency and seismic velocity with increasing peak ground acceleration (PGA). Frequency shifts inferred from the surface data mainly reflect the shallowest layers, whereas velocity changes estimated with borehole-referenced methods capture a path-averaged perturbation between the surface and borehole sensors and therefore depend on borehole depth. The data set is divided into seven PGA bins based on surface recordings, with the 1-5 cm s−2 bin serving as a baseline for comparison, representing linear site conditions. Across all stations, relative velocity reductions average ∼ 12 per cent in the 200-400 cm s−2 PGA range, corresponding to a shear modulus reduction (μ/μ0) of about 23 per cent. Nonlinear effects are most pronounced at sites with thicker sedimentary deposits, which are mainly found in the central valley and northern foothills of Iwate Prefecture. In contrast, VS30 shows no clear correlation with the observed nonlinearity, as its averaging effect masks thin low-velocity layers near the surface that are prone to nonlinear response during strong shaking. These results underline that nonlinear site response is highly site-specific, and that large observational data sets are crucial for robust characterisation across a seismic network.

SummaryThe Xianshuihe-Xiaojiang Fault System (XXFS), with slip rates of centimeters per year, is a major tectonic boundary accommodating southeastward extrusion of the Tibetan Plateau. Stretching over ~1,000 km through the densely populated Sichuan and Yunnan provinces in western China, it is particularly important to evaluate its potential for generating destructive earthquakes. This study systematically evaluates the XXFS within a physically grounded probabilistic framework by integrating geodetically modeled interseismic coupling, seismicity, empirical magnitude-area scaling laws, and barrier effects of creeping zones during dynamic rupture. We assess a range of rupture scenarios and obtain most probable maximum magnitudes of Mw 7.4 for the Xianshuihe fault, Mw 7.3 for the Anninghe-Zemuhe Fault, and Mw 7.2 for the Xiaojiang Fault, with corresponding fault-level recurrence of ~300, ~1 500 and ~170 years. The probabilities of occurrences of Mw 7.0 earthquake are higher along the northern and southern Xianshuihe, southern Anninghe, northern Zemuhe, and southern Xiaojiang segments. By assimilating geodetic and seismic data into a probabilistic framework that incorporates moment balance and rupture dynamics, our study provides a physics-based foundation for assessing regional seismic hazard in this tectonically active area. The approach is generalizable and can be applied to other fault systems where seismicity, basic geometry and geodetic coupling are constrained.

SummaryFrom late-December 2024 to mid-March 2025, a 50-km-long dyke intrusion triggered over 300 earthquakes (magnitude 4 to 5.9) between Fentale and Dofen volcanoes along the Northern Main Ethiopian Rift. Dyke intrusions periodically occur along the Fentale-Dofen magmatic segment and are an expression of ongoing rift extension. Preliminary analyses using interferometric synthetic aperture radar revealed extensive ground deformation (up to 60 cm), which closely matched the temporal and spatial evolution of surface manifestations and earthquake locations from global catalogs. While global catalogs are critical for real-time monitoring, the precision of locations in remote and or sparsely instrumented regions can be low. In this investigation, we present surface-wave relocation results of the dyking episode that began near Fentale volcano in December 2024. We estimate relative locations using differential travel times measured from regional-to-teleseismic distance surface-wave observations of earthquakes reported by the U.S. Geological Survey. Relative relocations reduce the initial region of diffuse seismicity to a 50-km-long narrow band bounding the strike of surface manifestations and the zone of maximum surface deformation. We demonstrate the precision of surface-wave relocations over incremental time periods, capturing the progression of dyking from seismic onset through seismic migration and caldera subsidence. Results showcase the utility of surface-wave relocations in the characterization of dyking episodes and provide complementary insights into the current understanding of the Fentale-Dofen volcanic plumbing system.

SummaryTraditional bathymetry inversion methods often fail to capture the complex nonlinear relationship between gravity data and bathymetry and lack the capability to quantify prediction uncertainty. To address these limitations, we investigated deep learning and Bayesian methods that enhance prediction accuracy and provide estimates of prediction uncertainty. Three methods—the Fully Connected Neural Network (FCNN), normalizing Flow model (Flow) and FCNN-Markov Chain Monte Carlo (FCNN-MCMC)—were developed to construct high-resolution (1′×1′) bathymetry models (FCNN, Flow, and FCNN-MCMC models) of the South China Sea (113°E-119°E, 12°N-19°N). The input data included positional, topographic, and gravity information from 4′×4′ grid points surrounding each training, validation and prediction point, while the output data corresponded to the measured bathymetry at training and validation points. At the check points, the standard deviation (STD) of the FCNN, Flow, and FCNN-MCMC models decreased by 7.13 m, 14.24 m, and 15.51 m, respectively, compared with topo_27.1, and by 18.19 m, 25.30 m, and 26.57 m, respectively, compared with ETOPO2022. The distribution of prediction uncertainties (STD) showed that over 90 per cent of the area exhibited an STD below 130 m. The prediction uncertainties exhibited a spatial distribution similar to the predicted results, with higher uncertainties mainly concentrated in shallow waters and steep areas.

SummaryHydraulic shear stimulation is a method to enhance permeability and heat extraction efficiency of geothermal systems. However, such reservoir treatments can have the risk of injection-induced seismicity. To address this issue, a novel Traffic Light System (TLS) is proposed based on the change of the seismic injection efficiency rate which is the ratio between seismic energy and hydraulic energy. In a first step, we numerically investigate the behavior of a naturally rough, slowly slipping, velocity-strengthening fracture in a granite at laboratory scale. The model is formulated on an evolution law for fractures within a rate-and-state friction framework, with fracture aperture varying as a function of both slip displacement and slip velocity. We compare the effects of the proposed Energy-based Traffic Light System (ETLS) injection protocol against those of modeled monotonic and cyclic injection, focusing particularly on aperture evolution and slip velocity. We show how implementing the ETLS criteria can reduce slip velocity by 30% compared to monotonic injection, while it was increased by 51% for cyclic injection. Even with lower slip velocity, the ETLS injection scheme sustains a similar aperture per injected volume as the monotonic scheme once larger volumes are reached. Overall, our simulations suggest that an ETLS approach could provide a safer hydraulic shear stimulation strategy for enhanced geothermal systems by minimizing slip velocity while maximizing permeability, compared to monotonic or cyclic injection.