Surveys in Geophysics最新文献

Accurate estimation of permeability (κ) and gas saturation (S_g) is critical for identifying productive intervals in volcanic reservoirs, yet severe heterogeneity in rock matrix and fluid distribution poses significant challenges to reliable prediction. This study presents a physics-based seismic petrophysical inversion framework that integrates log-scale rock physics modeling with seismic-scale stochastic nonlinear inversion to quantitatively estimate κ and S_g. A rock physics model is formulated with a parameter α that modulates the permeability-dependent effective fluid modulus (K_f), providing a physically interpretable mechanism that allows K_f to vary continuously between relaxed and unrelaxed fluid mixing regimes. The parameter α is estimated from well logs using a model-based approach, and its strong correlation with κ demonstrates its utility as a permeability proxy. Two seismic indicators, I_α and I_G, are derived from rock physics relationships linking α and fluid properties to κ and S_g measurements. The calibrated rock physics regressions provide quantitative estimates of κ and S_g from I_α and I_G. A PP-wave reflectivity formulation parameterized by I_α and I_G is derived, benchmarked against conventional expressions, and incorporated into the stochastic nonlinear inversion scheme to retrieve I_α and I_G from seismic data. Synthetic tests confirm the robustness and accuracy of the proposed approach. For field data applications, stratigraphic complexity is addressed through seismic waveform-constrained prior construction, enabling reliable inversion of I_α and I_G, which are then converted into κ and S_g via calibrated regressions. This framework provides a physics-based strategy for quantitative characterization of permeability and gas saturation in complex volcanic formations.

Marine controlled-source electromagnetic (CSEM) inversion is a widely used technique for imaging subsurface structures beneath the seafloor and exploring hydrocarbon or mineral resources. Although essential for data interpretation, the inversion process is computationally intensive, particularly due to the high memory demands and time consumption associated with sensitivity calculations, even in 2D cases. This paper presents recent advances in frequency-domain marine CSEM inversion algorithms, including a novel method for approximating sensitivities that significantly accelerates 2D inversion without relying on exact sensitivity matrices. A 2.5D frequency-domain CSEM forward modeling solver is employed as a testbed, where the secondary-field formulation is adopted to mitigate source singularities and enhance numerical accuracy. In the developed 2D inversion routine, the sensitivity matrix is computed via the adjoint-state method, integrating the inner product of the adjoint and forward electric fields over each cell during each iteration. The inversion is performed using the Gauss–Newton optimization scheme. To improve computational efficiency, adjoint fields are evaluated over a simplified layered model rather than the full multidimensional true model. Numerical experiments demonstrate that the proposed sensitivity approximation achieves nearly identical inversion performance to that of the exact sensitivities. Results from both synthetic and experimental datasets confirm that the approximate sensitivities are sufficiently accurate to ensure convergence toward geologically meaningful solutions.

Irregularly sampled geophysical time series are common in practice due to data gaps caused by sensor outages, environmental disturbances, or quality control procedures. Conventional digital filters, such as Fourier filters, require complete time series data and therefore cannot be directly applied to unevenly spaced noisy data without prior interpolation. In this study, we demonstrate that filtering unevenly spaced time series using Fourier filtering is inherently an ill-posed problem, manifested as rank deficiency in the associated parametric model. Building on this insight, we propose a minimum norm least squares Fourier filtering (MFF) that processes unevenly spaced time series without the need for preliminary data interpolation. Additionally, the prior covariance matrix of the time series is incorporated to further improve the filtering performance. We first apply the proposed method to extract deformation signals from daily position time series of 27 global navigation satellite system (GNSS) monitoring stations across the mainland China spanning from 1999 to 2024. The performance of MFF is compared with conventional Fourier filtering (CFF) with interpolation. The results demonstrate that MFF outperforms CFF, especially when prior precision is considered, as evidenced by a smaller fitting error of the extracted signals. Simulations confirm that signals recovered by MFF are closer to the true signals, with root mean square error (RMSE) reductions of 12.3 to 19.4% across the 27 stations, depending on the percentage of missing data. Incorporating formal errors provides an additional average RMSE reduction of 2.9%. Finally, we apply MFF to retrieve mass change signals from monthly gravity recovery and climate experiment (GRACE) and GRACE-FO gravity field solutions. The results agree with those from GNSS time series and show that MFF outperforms CFF in extracting components within desired frequency bands.

South America is known as a long-lived and extensive subduction zone where the Nazca and Antarctic Plates are subducting beneath the South American Plate from the west. This subduction is considered to significantly influence the tectonics, seismicity, and volcanic activity in and around the continent. However, its relationship with the Mid-Atlantic Ridge on the other side of the continent remains poorly understood. The eruption mechanism of the Robledo caldera in the Andes of Argentina, which experienced a Volcanic Explosivity Index 7 eruption around 2300 BCE, is not well constrained either. To resolve these issues, we apply a global tomography method to reveal the 3-D P-wave velocity (V_P) structure of the whole mantle beneath this region. We used ~7.2 million arrival times of 21,897 earthquakes recorded at 14,236 seismograph stations worldwide. The resulting ({V}_{P}) tomography clearly shows high-V_P subducted slabs and low-V_P anomalies above and below the slabs, which may reflect corner flow in the mantle wedge and subslab hot mantle upwelling (SHMU), respectively. A slab window is revealed beneath the Robledo caldera. Given the development of SHMU beneath this region, the huge eruption of the Robledo caldera might be powered by a mixture of the SHMU and magma in the mantle wedge through the slab window. Our tomography also suggests that the Mid-Atlantic Ridge had been opened due to hot mantle return flow associated with the subsidence of slab remnants into the lower mantle. Although such a mechanism was noted beneath North America, it is firstly confirmed in South America.

The Lousal Mine (Iberian Pyrite Belt, Portugal) was operated from 1900 to 1988 for the extraction of massive sulphides and was later rehabilitated as a science museum. It was selected as a test site for underground muon tomography applied to geophysical surveys, as part of the LouMu project. This study focuses on seismic tomography to analyse the subsurface above the mine gallery, primarily surveyed by a muography telescope, which was developed specifically for this site by the Laboratory of Instrumentation and Experimental Particle Physics. To validate the muon tomography results, an initial approach using conventional 2D seismic refraction failed to reach the Waldemar gallery depth, due to limited seismic ray coverage. Therefore, an innovative setup using surface shots and in-gallery geophones was implemented, providing full ray coverage. A 3D velocity model was then produced using the ATOM3D code, which enabled the integration of this configuration and performed travel-time inversion for velocity calculation. A regional dextral strike-slip fault, the Corona Fault (CF), crosses the surveyed area, and served as the main focus of this investigation. The 3D velocity model successfully detected this structure, that corresponded to the boundary between positive anomalies of the Volcano-Sedimentary Complex (VSC) and negative anomalies of the Phyllite-Quartzite Group (PQG). The absolute velocity distribution showed a distinct offset around the Corona Fault (CF), indicating a dextral strike-slip mechanism. A subvertical extension of secondary faults was observed, reflecting deformation similar to that of the main tectonic context. Previous data from the gallery confirmed that these results are consistent with the known geology and can serve as a reference for the muon tomography interpretations.