Search Results (614)

Integrating geophysical techniques at two contrasting locations—fractured young lavas in southwestern Iceland and older layered basalts in eastern Iceland—constrains the structure and shear-wave velocity of the volcanic subsurface. The results show that relying on a single geophysical method often yields non-unique solutions that can obscure velocity profiles and overlook sharp structural contrasts. Findings from southwestern Iceland reveal that young, faulted ‘a‘ā flows have a complex architecture with shallow, eroded layers, resulting in a reduced V_s30. Conversely, older Miocene bedrock in eastern Iceland shows a well-layered, consolidated structure with a higher V_s30. We demonstrate that modelling Scholte waves from legacy marine seismic data can generate regional velocity models consistent with onshore measurements. Full article

Reliable and scalable landmine detection technologies are essential for humanitarian mine action (HMA), yet standardized benchmarks for Unmanned Aerial Vehicle (UAV)-based sensing in operationally relevant environments remain limited. This study presents a comprehensive evaluation of 34 multimodal datasets acquired over a standardized seeded test site for landmine and unexploded ordnance detection. Nine sensing modalities, including RGB, thermal, multispectral, hyperspectral, LiDAR, and Synthetic Aperture Radar (SAR), are evaluated using the Anomaly, Identifiable Anomaly, Unique Identifiable Anomaly (AIU) index to establish a unified framework for quantifying detection fidelity. Results indicate that RGB imagery achieves the highest surface detection rate (94.8%), with 45.4% of targets classified as uniquely identifiable, reducing false-positive risk. For sub-surface detection, handheld electromagnetic induction (EMI) and magnetometry exceed 95% detection for ferrous items but fall below 10% for plastic ordnance. Ground-penetrating radar (GPR) is the only modality capable of detecting buried plastic targets (55.6% for cart-based systems), whereas UAV-mounted GPR remains limited (18.2%) at current operational flight heights. Based on the comparative analysis, we discuss the gaps in current detection capabilities, compare false-positive rates across modalities, and perform a cost–benefit analysis fitting contamination scenarios with the most cost-effective detection method. All datasets are publicly released, along with an interactive web-map, to support reproducible benchmarking and cross-modality comparison in UAV-enabled explosive hazard detection. Full article

In this contribution, we analyze and discuss the recently published Active Faults Greece (AFG) database highlighting how poorly constrained and inaccurate practices could impact the overall results. The analysis of the 3814 fault traces and the 892 individual faults proposed in the AFG emphasizes several critical aspects (such as lacking major geomorphological evidence, fault length exaggeration, improper reporting of blind faults, mapping of fault traces without precision, tracing and characterization of faults without field control, proposal of fault traces differing from well-mapped historical earthquake ruptures, omission and misjudgment of the literature, etc.). All these issues effectively invalidate the AFG, discredit the results presented to the public, and introduce a strong bias in any possible estimate of seismic hazard. Furthermore, we outline the criticalities caused by misleading, uncertain, or disputed data transmitted to administrators, professionals, and the public in general, who do not have the capacity or sufficient knowledge and expertise for carefully verifying the applicability of the product for seismic hazard assessment analyses. For secure fault data definition, the remote sensing/geomorphological approach at the base of the AFG could certainly be useful, but definitely not sufficient. Indeed, for the compilation of internationally recognized databases of seismogenic sources and active fault traces, the systematic and critical analysis of historical and/or instrumental seismicity, palaeoseismological, morphotectonic, geodetic, remote sensing, shallow geophysical techniques, and structural investigations would be required. Full article

The Jiaduoling area is located in the northern segment of the Southwest Sanjiang Metallogenic Belt, a region characterized by complex geological structures and abundant mineral resources. This study systematically identifies the spatial correlation between subsurface magnetic bodies and tectonic structures by utilizing 1:50,000 high-precision aeromagnetic data. Advanced processing techniques—including upward continuation, vertical derivatives, total gradient modulus, and Euler deconvolution—were integrated to refine the structural framework and clarify the mechanisms of fault-controlled mineralization. The results indicate that the aeromagnetic anomaly pattern is predominantly governed by NW-trending faults. Specifically, the deep-seated major fault F₁ (with a calculated depth exceeding 3 km) served as the primary migration channel for ore-forming fluids, while secondary faults created localized ore-hosting spaces. Physical property analysis reveals a significant magnetic contrast, where Mesozoic intermediate-acid magmatic rocks act as the essential source for mineralization, providing both material and thermal energy for the formation of porphyrite-type iron deposits. Based on these findings, a three-dimensional “aeromagnetic anomaly-structural framework-mineralization” correlation model was established. Finally, two high-potential metallogenic prospective zones (P1 and P2) were delineated, providing precise geophysical evidence and strategic guidance for regional mineral exploration and the targeting of concealed ore bodies. Full article

The growing need for sustainable wastewater treatment highlights the importance of low-energy solutions such as horizontal subsurface flow constructed wetlands (HSSF CWs). While effective, these systems often face clogging issues that reduce performance and lifespan. This study investigates clogging dynamics in a Water Treatment Plant (Lleida, Spain) using a multidisciplinary approach. Non-invasive geophysical methods such as Electrical Resistivity Tomography (ERT) and Induced Polarization (IP) were combined with high-resolution drone imagery to characterize surface and subsurface indicators of clogging. Drone data captured surface anomalies, while geophysical measurements revealed subsurface obstructions. The integrated analysis identifies clogged zones and shows a strong spatial correlation between surface features and geophysical anomalies. These results validate the use of drone imagery as a rapid, non-invasive diagnostic tool and demonstrate the effectiveness of combining remote sensing with geophysical techniques for wetland assessment. This approach supports improved monitoring, targeted maintenance, and optimized long-term performance of HSSF CWs. Full article

In characterizing unconventional reservoirs, conventional Digital Rock Physics (DRP) has long been constrained by three fundamental bottlenecks: the trade-off between imaging resolution and field of view, challenges in reconstructing multiscale pore topology, and the prohibitive computational cost of direct numerical simulation (DNS) at the pore scale. The deep integration of artificial intelligence and rock physics has given rise to a new paradigm—Intelligent Digital Rock Physics (IDRP). This paper provides a systematic review of the evolutionary trajectory of IDRP, with a focus on how machine learning is reshaping the end-to-end workflow from imaging and segmentation to reconstruction and simulation. First, we survey image super-resolution and 3D pore structure generation techniques based on convolutional neural networks (CNNs), generative adversarial networks (GANs), and diffusion models, elucidating their mechanisms for surpassing optical diffraction limits and incorporating macroscopic petrophysical constraints. Second, we outline algorithmic strategies for fusing multi-source heterogeneous data (e.g., Micro-CT and SEM) and representing dual-porosity or multi-continuum systems. Third, we critically examine the application of machine learning surrogates in single- and multiphase flow prediction, highlighting how physics-informed machine learning (PIML) and reinforcement learning (RL)—by embedding governing equations such as Navier–Stokes or Muskat–Leverett into loss functions—achieve both computational acceleration and physical consistency. We further identify key limitations of current IDRP approaches, including insufficient validation of generated topological realism, narrow generalization across lithologies, inadequate representation of dynamic wettability, and limited model interpretability. Finally, we propose a forward-looking roadmap centered on multimodal foundation models for rocks, coupled with neural operators and uncertainty quantification frameworks, emphasizing the critical pathways for translating IDRP into engineering digital twins for unconventional hydrocarbon development, coalbed methane production enhancement, Enhanced Geothermal Systems, and geological CO₂ storage. This review offers a comprehensive reference for researchers at the intersection of geophysics, rock mechanics, and artificial intelligence. Full article

Slowness extraction via Slowness Time Coherence (STC) serves as a fundamental technique for formation evaluation in oil and gas geophysics. Conventional amplitude-dependent peak selection methods often exhibit limitations in complex logging scenarios, including weak wave arrivals, high noise floors, and spurious local maxima. To address these challenges, this paper proposes Neighborhood Width Transform (NWT), an unsupervised data-driven mathematical framework that distinguishes genuine peaks from noise by quantifying local neighborhood structural stability rather than relying on amplitude magnitude. The core of NWT lies in a bilateral neighborhood width metric and a minimum-pooling fusion strategy, which suppresses narrow pseudo-peaks effectively. Experimental validation demonstrates that the proposed method outperforms seven representative peak-selection baseline methods (CWT Ridge Analysis, Gaussian Mixture Fitting, AMPD, SG Derivative Crossing, NMS, Random Forest, and 1D-Unet) in terms of detection reliability and accuracy on the tested challenging logging datasets. The proposed method provides an interpretable, high-throughput mathematical solution for automated geophysical signal processing. Full article

Radio occultation (RO) has become a key technique for monitoring the ionosphere by deriving electron density (Ne) profiles and total electron content (TEC) from GNSS signals. This study assesses the newly deployed PlanetiQ GNOMES constellation by validating its ionospheric Ne profiles and profile-based TEC against collocated measurements from ionosondes and the COSMIC-2 mission under both quiet and disturbed geomagnetic conditions. Data matching for the statistical validation uses conservative spatial thresholds of less than 1° in latitude and longitude and temporal limits of 30 min for ionosondes and 1 h for COSMIC-2, supported by a dedicated sensitivity analysis, whereas storm-time case studies apply tighter temporal collocation and explicit control of the ray path geometry. Quantitative agreement is evaluated using root mean square error (RMSE), mean and absolute mean differences, correlation coefficients, regression analysis, and normalized percentage differences for key F-layer parameters, including the maximum Ne of the F2 layer (NmF2), the peak height of the F2 layer (hmF2), and the critical frequency of the F2 layer (foF2), along with altitude-dependent Ne profiles. PlanetiQ shows strong consistency with ionosonde profiles, with RMSE ranging from 2.94 × 10⁴ to 2.76 × 10⁵ el/cm³, correlations typically exceeding 0.90, and normalized absolute mean differences often near or below about 10–20%, although lower correlations of about 0.31 and 0.69 are found at Poker Flat and Awase, respectively, reflecting complex local structures and regional variability. Comparisons with COSMIC-2 during quiet conditions yield RMSE values between 7.06 × 10⁴ and 2.16 × 10⁵ el/cm³, correlations from 0.94 to 0.99, and percentage differences that generally remain within a few tens of percent, while storm-time analyses show RMSE between 1.12 × 10⁵ and 3.70 × 10⁵ el/cm³ with correlations from 0.80 to 0.99, confirming robust agreement across a wide range of geophysical conditions. Regression results demonstrate slopes near 1.00 and correlation coefficients above 0.90 for NmF2 and foF2 between PlanetiQ and both ionosondes and COSMIC-2, whereas hmF2 exhibits larger scatter, particularly during geomagnetic disturbances; additional binning by spatial and temporal separation indicates that temporal mismatches generally have a stronger impact on discrepancies than horizontal distance. Overall, the results demonstrate that PlanetiQ ionospheric RO data provide accurate and consistent measurements of key ionospheric parameters, comparable to those from COSMIC-2 and ionosondes, and can reliably complement existing observing systems for monitoring ionospheric variability and space-weather impacts. Full article

Recent technological advances and the reinvigoration of NASA’s Artemis program have increased the feasibility of lunar habitats and supporting infrastructure, necessitating the development of specialized foundation systems capable of maintaining stability under transferred structured loads. Site investigation techniques, including in situ testing, sampling, and geophysical mapping, must therefore be adapted for lunar conditions, while construction using regolith requires an improved understanding of lunar soil mechanics. Foundations must also endure extreme thermal fluctuations, reduced gravity, radiation exposure, micrometeoroid impacts, and lunar seismicity to ensure long-term performance. Consequently, enhanced knowledge of the monotonic and cyclic geotechnical behavior of lunar soils is essential. Owing to the limited availability of in situ testing opportunities and returned lunar materials, high-fidelity simulants that replicate regolith behavior are required for experimental studies. This research investigates the static behavior of several contemporary lunar simulants and compares their responses with terrestrial benchmark soils. The results indicate that the overall stress–strain trends of lunar simulants broadly resemble those of terrestrial soils; however, the particle morphology and distinctive mineralogical compositions, including basaltic and anorthositic constituents, yield higher values of certain geomechanical parameters. Comparison with terrestrial datasets further suggests that carefully selected benchmark soils may facilitate the development of a next generation of lunar simulants with improved fidelity to lunar regolith. Full article

Reinforced concrete structures, once considered very durable and capable of withstanding a variety of adverse environmental conditions, often suffer from premature reinforcement corrosion, compromising their safety and serviceability. Ensuring the safety of bridges and buildings requires effective, non-destructive inspection and monitoring techniques to assess the state of degradation without damaging the integrity of the asset. Although a wide range of non-destructive testing (NDT) methods is currently available, few are capable of identifying durability issues during the initial stages before the damage becomes critical. To address this gap, this paper describes an innovative laboratory experiment based on an integrated approach that combines Ground-Penetrating Radar (GPR) and electrochemical methods. This research represents an advanced step in our ongoing projects, merging geophysical and electrochemical expertise to enhance diagnostic precision. A reinforced cement mortar specimen was subjected to free corrosion via partial immersion in sodium chloride solutions of varying concentrations (1, 10, and 35 g/L), followed by an accelerated corrosion phase. The phenomenon was monitored simultaneously using GPR and electrochemical tests. Each technique provided specific information, but a data integration method used in the operating system will further improve the overall quality of diagnosis. Specifically, the application of the Hilbert Transform to GPR signals allowed for a correlation between envelope amplitude variations and the electrochemical behavior of the rebars. These laboratory results highlighted that an integrated observation was useful to indirectly observe the evolution of the phenomenon of corrosion in the steel reinforcement embedded in the mortar specimens. Full article

In this paper, the results of several geophysical surveys developed with a Sub-Bottom Profiler in different regions of Spain are presented. This research forms part of a broader project aimed at developing innovative non-invasive methodologies for documenting Underwater Cultural Heritage (UCH). The 2001 UNESCO Convention on the Protection of the Underwater Heritage recommends the use of non-destructive techniques, in situ conservation, and prioritising exploration over recovery. Geophysical techniques allow the non-invasive documentation of UCH without altering archaeological remains. The Sub-Bottom Profiler was tested in several underwater archaeological surveys under different objectives, depths, and environmental conditions. The research questions addressed the amount of information obtainable without intrusion and the optimal use of the equipment for methodological innovation. Based on the results, methodological conclusions are drawn regarding the influence of seabed composition on acoustic performance, the importance of controlling navigation speed and vessel stability, and the strong impact of sea state on data quality. The need for frequency and motion-correction optimisation to balance resolution and penetration is also highlighted, as well as the usefulness of SBP for anomaly detection, site monitoring, and palaeolandscape reconstruction. These findings contribute to establishing a transferable methodological framework applicable to other case studies. Full article

A thorough understanding of the resistivity response characteristics of ethanol-contaminated soil is of great significance for the development of non-destructive geophysical detection techniques and for supporting contaminated site investigation and assessment. This experimental study aims to systematically investigate the resistivity behavior of ethanol-contaminated sandy soils, with a focus on the coupled mechanisms of multiple factors, including water content, ethanol concentration, particle size distribution, and contamination time. It is hypothesized that water content serves as the dominant factor controlling resistivity, whereas ethanol concentration and contamination time regulate resistivity by altering the physicochemical properties of the pore fluid. Under laboratory conditions, silt, fine sand, and medium sand were selected as the test materials. Resistivity was systematically measured using a Miller Soil Box with increasing water content, Wenner array configuration across varying water contents (3–24%), ethanol concentrations (40–98%), and contamination durations (0–144 h). The experimental results indicate the following: (1) Regardless of the presence of ethanol contamination, the resistivity of sandy soil decreases with increasing water content following a power-law relationship. The decrease is most pronounced at low water contents (3–9%), and gradually stabilizes at higher water contents. The results show that, at a constant water content, resistivity systematically and consistently follows the order: silt > medium sand > fine sand. (2) The influence of ethanol concentration on resistivity is constrained by water content levels, and the overall increase in resistivity is primarily attributed to ion dilution and the obstruction of conductive pathways. (3) Over time, resistivity exhibits a two-stage increasing trend, associated with ethanol volatilization and water loss. Resistivity changes in fine sand samples contaminated with ethanol at concentrations ranging from 75% to 95% follow a two-stage pattern. The initial phase of growth is characterized by a gradual increase over a period of 0–48 h, followed by a more rapid increase during the subsequent phase, which extends from 48 to 144 h. The results show that higher initial ethanol concentrations enhance the sensitivity of resistivity to temporal changes. Comprehensive analysis indicates that the resistivity variation mechanism under multi-factor coupling conditions can be summarized as follows: the water content is the dominant factor in the regulation of the conductive pathways; the particle size distribution determines pore structure and the characteristics of the particle interface; ethanol concentration and contamination time dynamically alter pore fluid properties, collectively regulating the resistivity response. Although the experiments were conducted under controlled laboratory conditions and the results have certain limitations, they provide a preliminary reference for interpreting resistivity responses in relatively homogeneous sandy contaminated sites and offer theoretical support for the application of resistivity methods in contamination identification and dynamic monitoring. Full article

The archaeological remains of the Roman villa at Madonna del Piano are situated at the foot of the hill on which the municipality of Castro dei Volsci (Italy) now stands. This crucial region guarantees access to the coastal areas and is situated between the Via Latina and the Amaseno Valley. The first signs of the existence of archaeological structures can be seen in several historic aerial images, where anomalies are readily visible. The remnants of an imperial-era villa with varying periods of occupation were discovered during excavations carried out between the mid-1980s and the early 1990s. These remnants can now be identified in three distinct complexes that were previously linked as a component of a single complex. Given the site’s importance, a research project based on numerous studies and multi-scale approaches was launched in 2024 to collect new data and fill any knowledge gaps. The technique focused on the villa and its surroundings using LiDAR scans, geophysical prospections, 3D surveys of visible structures, archival research, and historical aerial photogrammetry. The findings provide new insight into the settlement by clarifying and elucidating its structure, relationships, and roles of the three complexes, and placing the results within a broader geographical context. Full article

Spontaneous potential (SP) logging remains a widely used method in well geophysics. However, its interpretation is often limited by simplified physical models and correction charts that do not fully account for the processes governing SP generation, particularly in shaly and heterogeneous formations. In this study, we develop a finite element-based algorithm for modeling SP responses in complex near-wellbore environments, with the aim of providing a more physically consistent framework for interpretation. The proposed algorithm is based on the numerical solution of the Poisson equation with electrochemical source terms, incorporating the cation transport number to describe diffusion–adsorption processes and allowing for smooth variations in formation resistivity, fluid properties, and shale content. The numerical implementation is validated against published analytical solutions, correction charts, and previous numerical studies, showing good agreement in both the shape and amplitude of modeled SP responses across a range of geological scenarios, including thin beds and invasion zones. Application to real data from a Southeast Asia gas field demonstrates that the approach provides reliable estimates of formation water salinity and the cation transport number, with results consistent with independent estimates. The proposed method offers a flexible tool for SP response modeling and may complement existing interpretation techniques, particularly when working with heterogeneous formations and limited legacy datasets. Full article

Interferometric Synthetic Aperture Radar (InSAR) is crucial for monitoring ground displacement, particularly in Pakistan’s capital area, where urban expansion and active geotectonics converge. This study introduces the Consecutive Interferogram Stacking Approach (CISA), a processing framework optimized for near-real-time deformation monitoring using full-resolution Sentinel-1 data from adjacent acquisition pairs. Unlike conventional InSAR techniques that rely on spatial multilooking to suppress phase noise—which sacrifices spatial resolution for computational efficiency—CISA preserves native resolution through sequential interferogram stacking, accepting that short-interval interferograms retain geophysical phase instabilities (including fading signals) inherent to scatterer decorrelation. By minimizing temporal decorrelation through consecutive pairing, CISA enhances interferogram coherence (6–14% improvement) and reduces Root Mean Square Error (RMSE) by approximately 25% compared to conventional multilooked time series, while enabling the computational efficiency critical for operational applications. The framework’s incremental architecture allows velocity updates within hours of new image acquisition—requiring only single interferogram addition rather than complete network reprocessing—making it suitable for rapid-response hazard assessment where latency constraints outweigh the need for long-baseline phase filtering. CISA reveals spatiotemporal subsidence patterns potentially reflecting the influence of fault zone geometry, groundwater fluctuation, and urbanization, with full-resolution analysis delineating linear deformation patterns spatially consistent with blind fault traces through multi-directional displacement modeling. These findings demonstrate that operational monitoring of geohazards can be achieved through strategic trade-offs between processing latency and geophysical noise suppression, providing actionable intelligence for infrastructure risk management in tectonically active urban environments. Full article