Search Results (124)

Coal spontaneous combustion in arid regions poses severe threats to both ecological security and resource sustainability. Focusing on the detection challenges in Fire Zone No. 1 of the Miaoergou Coalfield, Xinjiang, this study proposes an Integrated Geophysical Collaborative Detection Framework that combines high-precision magnetic surveys, spontaneous potential (SP) measurements, and transient electromagnetic (TEM) methods. This innovative framework effectively overcomes the limitations of traditional single-method detection approaches, enabling the precise delineation of fire zone boundaries and the accurate characterization of spatial dynamics of coal fires. The key findings of the study are as follows: (1) High-magnetic anomalies (with a maximum ΔT of 1886.3 nT) exhibit a strong correlation with magnetite-enriched burnt rocks and dense fracture networks (density > 15 fractures/m), with a correlation coefficient (R²) of 0.89; (2) Negative SP anomalies (with a minimum SP of −38.17 mV) can effectively reflect redox interfaces and water-saturated zones (moisture content > 18%), forming a “positive–negative–positive” annular spatial structure where the boundary gradient exceeds 3 mV/m; (3) TEM measurements identify high-resistivity anomalies (resistivity ρ = 260–320 Ω·m), which correspond to non-waterlogged goaf collapse areas. Spatial integration analysis of the three sets of geophysical data shows an anomaly overlap rate of over 85%, and this result is further validated by borehole data with an error margin of less than 10%. This study demonstrates that multi-parameter geophysical coupling can effectively characterize the thermo-hydro-chemical processes associated with coal fires, thereby providing critical technical support for the accurate identification of fire boundaries and the implementation of disaster mitigation measures in arid regions. Full article

Antimicrobial resistance (AMR) surveillance plays a critical role in tracking emerging trends and informing evidence-based policies. This study assessed bacterial contamination and resistance profiles of Escherichia coli and Pseudomonas aeruginosa in 1886 drinking water samples from 12 regions of Ghana between April 2024 and April 2025. Findings were compared to a baseline study from the Greater Accra region (2022). Water samples analysed included sachet, bottled, tap, borehole, well, and surface water. Isolates were tested for antibiotic susceptibility using the Kirby–Bauer disk diffusion method. The majority of treated and packaged water samples were free from bacterial contamination. E. coli was frequently detected in untreated surface water (68%) and well water (63%). E. coli isolates from untreated water samples exhibited high resistance to cefuroxime (74%) and amoxicillin-clavulanate (50%); resistance to gentamicin increased from 3% in 2022 to 35% in 2025, while ertapenem resistance rose from 6% to 18%. Multidrug-resistant (MDR) E. coli isolates were found in samples from eight regions, and MDR P. aeruginosa in three, mostly from borehole water. These findings highlight the urgency to integrate AMR surveillance into national water quality initiatives, along with coordinated public health interventions, to educate communities on household water treatment practices and the health risks posed by AMR. Full article

Historical chemical production sites often harbor irregularly distributed solid waste landfills, posing significant environmental risks. Traditional drilling methods, while accurate, are inefficient for comprehensive characterization due to high costs and spatial limitations. This study aims to develop an integrated geophysical drilling approach to accurately delineate the spatial distribution and volume of landfilled solid waste (predominantly organic pollutants) at two decommissioned chemical plant sites (total area: 8954 m²). Methods: We combined (1) geophysical surveys (transient electromagnetic (TEM, 50 profiles, 2936 points), high-density resistivity (HDR, 2 profiles, 192 points), and ground-penetrating radar (GPR, 22 profiles, 1072.1 m)) and (2) systematic drilling verification (136 boreholes, ≤10 m × 10 m density). Anomalies were interpreted through integrating geophysical responses, historical records, and borehole validation. Spatial modeling was conducted using Kriging interpolation in EVS software. The results show that (1) the anomalies exhibited a “sparse multi-point distribution” across zones A2 (primary waste concentration), A4, and A6, which were differentiated into solid waste, foundations, contaminated soil, voids, and cracks; (2) drilling confirmed solid waste at nine locations (A2: “multi-point, small-quantity” residues; A6: contaminated clay layers with garbage) with irregular thicknesses (0.2–1.3 m); (3) TEM identified diagnostic medium–high-resistivity anomalies (e.g., 28–37 m in A4L3), while GPR detected 17 shallow anomalies (only one validated as waste); and (4) the total waste volume was quantified as 266.9 m³. The methodology reduced the field effort by ∼35% versus drilling-only approaches, resolved geophysical limitations (e.g., HDR’s volume effect overestimating the thickness), and provided a validated framework for efficient characterization of complex historical landfills. Full article

Isolated permafrost is widely distributed in freeze–thaw transition zones, characterized by blurred boundaries and strong spatial variability. Traditional methods such as drilling and electrical resistivity surveys are often limited in achieving efficient and continuous boundary identification. This study focuses on a typical isolated permafrost region in Northeast China and proposes a boundary detection strategy based on multi-frequency electromagnetic (EM) measurements using the GEM-2 sensor. By designing multiple frequency combinations and applying joint inversion, a boundary identification framework was developed and validated against borehole data. Results show that the multi-frequency joint inversion method improves the spatial identification accuracy of permafrost boundaries compared to traditional point-based techniques. In areas lacking boreholes, the method still demonstrates coherent boundary imaging and strong adaptability to geomorphological conditions. The multi-frequency joint inversion strategy significantly enhances imaging continuity and effectively captures electrical variations in complex freeze–thaw transition zones. Overall, this study establishes a complete non-invasive technical workflow—“acquisition–inversion–validation–imaging”—providing an efficient and scalable tool for engineering site selection, foundation design, and permafrost degradation monitoring. It also offers a methodological paradigm for electromagnetic frequency optimization and subsurface electrical boundary modeling. Full article

In the context where the surrounding rock of deep coal mine roadways is in a complex mechanical environment of “three highs and one disturbance”, mining disturbances are prone to cause instability and damage to the roadways, and the severe deformation of the south wing main roadway caused by mining disturbances in the 2404 working face of a certain mine in the Jiaoping Mining Area restricts safe production. In order to reduce the deformation and damage of the south wing main roadway affected by long-term dynamic pressure, this study proposes a determination method of key rock strata for top cutting pressure relief and the pressure-relief method along the stress transmission path of the south wing main roadway. It completes the design and field test of the hydraulic fracturing scheme for the hard roof of the 2404 transportation roadway, and evaluates the pressure-relief effect through means such as pressure curves, mine pressure manifestation laws, and borehole observation. The results show that hydraulic fracturing significantly weakens the strength of the roof rock strata, forms through cracks between the pressure-relief holes, reduces the average working resistance of the support by 18% after fracturing, and reduces the average pressure step distance of the roof by 34%. During the mining process, the stress variation range of the coal pillar is small, and there is no obvious deformation or damage to the surrounding rock and support structure of the south wing main roadway. It effectively cuts off the stress transmission path of the hard roof and controls the deformation of the roadway, providing technical support for the control of surrounding rock in deep dynamic pressure roadways. Full article

Over the past decade, the application of Tunnel Boring Machines (TBMs) in tunnel construction has increased significantly. During the construction process, numerous unfavorable geological structures, especially water-conducting structures, are encountered. The commonly used Tunnel Seismic Prediction (TSP) method often cannot accurately interpret water-conducting features, while resistivity methods are sensitive to low-resistivity bodies, which are frequently associated with water channels. Due to the limited space and the surrounding pipe lining near the tunnel face, as well as the difficulty in drilling boreholes under TBM construction conditions, this paper proposes a novel electrode arrangement method that replaces rigid electrodes with flexible electrodes installed on the sidewalls. This approach overcomes the difficulty of deploying traditional electrodes downward in TBM tunnels. A simple direct current resistivity configuration was employed for field testing during the construction of the Guiyang Metro Line 3 TBM tunnel, and the results were compared with those from the Tunnel Seismic Prediction (TSP) method. The experimental results demonstrate that the improved DC resistivity method achieves high detection accuracy for water-conducting structures within a range of 30 m, showing strong consistency with the TSP detection results. This validates the feasibility and accuracy of the method, effectively addressing the challenges associated with traditional electrode deployment in TBM tunnels while compensating for the limited response of seismic methods to water-bearing structures. However, the effectiveness near the tunnel face remains suboptimal, with insufficient current distribution—an area requiring improvement, potentially by increasing forward current supply or further optimizing the electrode layout. Additionally, the study highlights the limitations of relying solely on a single advanced prospecting method. It suggests adopting an integrated approach, primarily based on seismic methods supplemented by electrical methods, to enable joint detection and interpretation, thereby minimizing the risk of accidents during construction. Full article

The evolution of mining-induced overburden fractures (MIOFs) and their dynamic monitoring are critical for preventing roof water hazards and gas disasters in coal mines. Conventional methods often fail to provide sufficient accuracy under the thin soft–hard interbedded roof strata, necessitating advanced alternatives. Here, we address this challenge by proposing a borehole resistivity method (BRM) based on Back-Propagation Neural Network full-space inversion (BPNN-FSI). Based on the Carboniferous Taiyuan Formation in the North China Coalfield, geoelectric models of MIOFs were established for different mining stages. Finite element simulations generated apparent resistivity responses to train and validate the BPNN-FSI model. At the 9-204 working face of Dianping Coal Mine (Shanxi Province), we compared the proposed BRM based on BPNN-FSI with an empirical formula, numerical simulation, similarity physical simulation, and underground inclined drilling water-loss observations (UIDWLOs). Results demonstrate that the BRM based on BPNN-FSI achieves sub-1% error in height of MIOF (HMIOF) monitoring, with a maximum detected fracture height of 52 m—significantly outperforming conventional methods. This study validates the accuracy and robustness of BRM based on BPNN-FSI for MIOF monitoring in thin soft–hard interbedded roof strata, offering a reliable tool for roof hazard prevention and sustainable mining practices. Full article

With coal mines’ mining depth increasing, the stress environment in deep mining (including key factors such as high ground stress, strong disturbance, and complex geological structures, as well as stress redistribution after deformation of surrounding roadway rock) is complex, which leads to increasingly prominent deformation and failure problems for goaf-side roadways in thick coal seams. Surrounding rock deformation is difficult to control, and mine pressure behavior is violent, making traditional support technologies no longer able to meet the mining safety requirements of roadways in deep thick coal seams. Taking the 6311 working face of Tangkou Coal Mine as the engineering research background, this paper systematically summarizes the deformation and failure characteristics of goaf-side roadways in deep thick coal seams through field monitoring, borehole peeping, and other means, and conducts in-depth analysis of their failure mechanisms and influencing factors. Aiming at these problems, a synergistic support–unloading control method for goaf-side roadways is proposed, which integrates roof blasting pressure relief, coal pillar grouting reinforcement, and constant-resistance energy-absorbing anchor cable support. The effects of the unsupported scheme, original support scheme, and synergistic support–unloading control scheme are compared and analyzed through FLAC^3D numerical simulation. Further verification through field application shows that it has remarkable effects in controlling roadway convergence deformation, roof separation, and bolt (cable) stress. Specifically, compared with the original support schemes, the horizontal displacement on the coal pillar side is reduced by 89.5% compared with the original support scheme, and the horizontal displacement on the solid coal side is reduced by 79.3%; the vertical displacement on the coal pillar side is reduced by 45.8% and the vertical displacement on the solid coal side is reduced by 42.4%. Compared with the original support scheme, the maximum deformation of the roadway’s solid coal rib, roof, and coal pillar rib is reduced by 76%, 83%, and 88%, respectively, while the separation between the shallow and deep roof remains at a low level. The coal stress continues fluctuating stably during the monitoring period; the force on the bolts (cables) does not exceed the designed anchoring force, with sufficient bearing reserve space (47% remaining), and no breakage occurs, which fully proves the feasibility and effectiveness of the synergistic support–unloading control technology scheme. This technology realizes the effective control of on-site roadways and provides technical reference for the support engineering of coal mine goaf-side roadways under similar conditions. Full article

The time-domain electromagnetic method has been widely applied in mineral exploration, oil, and gas fields in recent years. However, its response characteristics remain unclear, and there is an urgent need to study the response characteristics of the borehole-surface transient electromagnetic(BSTEM) field. This study starts from the time-domain electric field diffusion equation and discretizes the calculation area in space using tetrahedral meshes. The Galerkin method is used to derive the finite element equation of the electric field, and the vector interpolation basis function is used to approximate the electric field in any arbitrary tetrahedral mesh in the free space, thus achieving the three-dimensional forward simulation of the BSTEM field based on the finite element method. Following validation of the numerical simulation method, we further analyze the electromagnetic field response excited by vertical line sources.. Through comparison, it is concluded that measuring the radial electric field is the most intuitive and effective layout method for BSTEM, with a focus on the propagation characteristics of the electromagnetic field in both low-resistance and high-resistance anomalies at different positions. Numerical simulations reveal that BSTEM demonstrates superior resolution capability for low-resistivity anomalies, while showing limited detectability for high-resistivity anomalies Numerical simulation results of BSTEM with realistic orebody models, the correctness of this rule is further verified. This has important implications for our understanding of the propagation laws of BSTEM as well as for subsequent data processing and interpretation. Full article

This study investigates cement–bentonite slurries with hydration accelerators for borehole backfilling applications in infrastructure reconstruction projects. Two formulations with different accelerator dosages (5 and 10 kg/m³) were evaluated through combined experimental testing and Moving Particle Semi-implicit (MPS) numerical modeling to optimize material performance. The research focuses on time-dependent rheological evolution and its impact on construction performance, particularly bleeding resistance and workability retention. Experimental flow tests revealed that both formulations maintained similar initial flowability (240–245 mm spread diameter), but the higher accelerator dosage resulted in 33% flow reduction after 60 min compared to 12% for the lower dosage. Bleeding tests demonstrated significant improvement in phase stability, with bleeding rates reduced from 2.5% to 1.5% when accelerator content was doubled. The MPS framework successfully reproduced experimental behavior with prediction accuracies within 3%, enabling quantitative analysis of time-dependent rheological parameters through inverse analysis. The study revealed that yield stress evolution governs both flow characteristics and bleeding resistance, with increases several hundred percent over 60 min while plastic viscosity remained relatively constant. Critically, simulations incorporating time-dependent viscosity changes accurately predicted bleeding behavior, while constant-viscosity models overestimated bleeding rates by 60–130%. The higher accelerator formulation (10 kg/m³) provided an optimal balance between initial workability and long-term stability for typical borehole backfilling operations. This integrated experimental–numerical approach provides practical insights for material optimization in infrastructure reconstruction projects, particularly relevant for aging infrastructure requiring proper foundation treatment. The methodology offers construction practitioners a robust framework for material selection and performance prediction in borehole backfilling applications, contributing to improved construction quality and reduced project risks. Full article

To address the challenges in identifying NAPL contamination within low-permeability clay sites, this study innovatively integrates high-density electrical resistivity tomography (ERT) with a UNet deep learning model to establish an intelligent contamination detection system. Taking an industrial site in Shanghai as the research object, we collected apparent resistivity data using the WGMD-9 system, obtained resistivity profiles through inversion imaging, and constructed training sets by generating contamination labels via K-means clustering. A semantic segmentation model with skip connections and multi-scale feature fusion was developed based on the UNet architecture to achieve automatic identification of contaminated areas. Experimental results demonstrate that the model achieves a mean Intersection over Union (mIoU) of 86.58%, an accuracy (Acc) of 99.42%, a precision (Pre) of 75.72%, a recall (Rec) of 76.80%, and an F1 score (f1) of 76.23%, effectively overcoming the noise interference in electrical anomaly interpretation through conventional geophysical methods in low-permeability clay, while outperforming DeepLabV3, DeepLabV3+, PSPNet, and LinkNet models. Time-lapse resistivity imaging verifies the feasibility of dynamic monitoring for contaminant migration, while the integration of the VGG-16 encoder and hyperparameter optimization (learning rate of 0.0001 and batch size of 8) significantly enhances model performance. Case visualization reveals high consistency between segmentation results and actual contamination distribution, enabling precise localization of spatial morphology for contamination plumes. This technological breakthrough overcomes the high-cost and low-efficiency limitations of traditional borehole sampling, providing a high-precision, non-destructive intelligent detection solution for contaminated site remediation. Full article

In this work, we explore the optimization of 3D Electrical Resistivity Tomography (ERT) measurement protocols for a 3D borehole grid configuration. Currently, there is no widely accepted standard measurement scheme for such setups. The use of numerous electrodes and the possibility of cross-borehole configurations lead to an extremely large number of potential electrode combinations. However, not all these combinations contribute significantly to the final resistivity model, and a complete measurement cycle requires substantial time to perform. This becomes particularly problematic in dynamic subsurface conditions, where changes may occur during data acquisition. In such cases, the measurements collected within a single cycle may reflect different subsurface states. Conversely, attempting to shorten acquisition time can result in too few measurements to resolve the subsurface structure at high resolution. Furthermore, most existing approaches assume a uniform half-space model and treat all measurements equally, failing to prioritize those that are most sensitive to actual subsurface changes. To address these challenges, we propose a 3D measurement optimization approach that yields an efficient acquisition scheme. This method produces inversion results comparable to those obtained from much larger datasets while reducing both measurement and processing requirements. Our optimization is based on a sensitivity-driven selection algorithm that accounts for the real subsurface structure rather than assuming a generic half-space. The proposed methodology is validated using synthetic data and tested with experimental data obtained from a laboratory tank setup. These experimental measurements were used to monitor permeation grouting; a technique applied to reduce permeability and/or increase the strength of granular soils through targeted injection. Full article

To address the challenge of dynamic monitoring during grouting operations in coal mine fault zones under pressurized mining, this study proposes the Borehole–Tunnel Joint Resistivity Method (BTJRM). By integrating three-dimensional (3D) electrode arrays in both tunnels and boreholes with 3D resistivity inversion technology, this approach enables fully automated underground data acquisition and real-time processing, facilitating comprehensive dynamic monitoring of grout propagation. A case study was conducted on a coal mine fault grouting project, where tunnel and borehole survey lines were deployed to construct a 3D cross-monitoring network, overcoming the limitations of traditional 2D data acquisition. Finite volume method and quasi-Gauss–Newton inversion algorithms were employed to analyze dynamic resistivity variations, enhancing spatial resolution for detailed characterization of grout migration. Key findings include: (1) Grout diffusion reduced resistivity by 10%, aligning with electrical response patterns during fracture-filling stages; (2) 3D inversion reveals that grout propagates along the principal stress axis, forming a “Y”-shaped low-resistivity anomaly zone that penetrates the fault structural block and extends into roadway areas. The maximum planar and vertical displacements of grout reach 100 m and 40 m, respectively. Thirty days post-grouting, resistivity recovers by up to 22%, reflecting the electrical signature of grout consolidation; (3) This method enables 3D reconstruction of grout diffusion pathways, extends the time window for early warning of water-conducting channel development, and enhances pre-warning capabilities for grout migration. It provides a robust framework for real-time sealing control of fault strata, offering a novel dynamic monitoring technology for mine water inrush prevention. The technology can provide reliable grouting evaluation for mine disaster control engineering. Full article

Electrical imaging logging technology precisely characterizes the features of the formation on the borehole wall through high-resolution resistivity images. However, the problem of blank strips caused by the mismatch between the instrument pads and the borehole diameter seriously affects the accuracy of fracture identification and formation continuity interpretation in marine oil and gas reservoirs. Existing inpainting methods struggle to reconstruct complex geological textures while maintaining structural continuity, particularly in balancing low-frequency formation morphology with high-frequency fracture details. To address this issue, this paper proposes an inpainting method using a dual-stream network based on the collaborative optimization of wavelet and spatial-channel convolution. By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. A dual-stream encoder–decoder network architecture is adopted, and the wavelet transform convolution (WTConv) module is utilized to enhance the multi-scale perception ability of the generator, achieving a collaborative analysis of the low-frequency formation structure and high-frequency fracture details. Combined with the spatial channel convolution (SCConv) to enhance the feature fusion module, the cross-modal interaction between texture and structural features is optimized through a dynamic gating mechanism. Furthermore, a multi-objective loss function is introduced to constrain the semantic coherence and visual authenticity of image reconstruction. Experiments show that, in the inpainting indexes for Block X in the South China Sea, the mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) of this method are 6.893, 0.779, and 19.087, respectively, which are significantly better than the improved filtersim, U-Net, and AOT-GAN methods. The correlation degree of the pixel distribution between the inpainted area and the original image reaches 0.921~0.997, verifying the precise matching of the low-frequency morphology and high-frequency details. In the inpainting of electrical imaging logging images across blocks, the applicability of the method is confirmed, effectively solving the interference of blank strips on the interpretation accuracy of marine oil and gas reservoirs. It provides an intelligent inpainting tool with geological interpretability for the electrical imaging logging interpretation of complex reservoirs, and has important engineering value for improving the efficiency of oil and gas exploration and development. Full article

Geophysics is a discipline that studies the properties of subsurface media using physical methods, among which electromagnetic methods have long been an important technical approach in resource exploration. The anisotropy of resistivity in underground media objectively exists in electromagnetic exploration. However, most borehole-to-surface electromagnetic methods (BSEMs) currently process and interpret data based on the assumption of isotropy, which can lead to misinterpretations of observational data in regions where an isotropy is significant. To address this, we propose a 3D edge-based finite element method on unstructured meshes for simulating resistivity anisotropy in BSEMs. A principal-axis anisotropic tensor is introduced to model anisotropy, and the vertical-line transmitter is transformed into an equivalent set of point sources, enabling efficient computation. The accuracy and effectiveness of the proposed numerical algorithm are validated through comparisons with the solutions from Dipole1D and MARE2D. Furthermore, a comparative analysis of reservoir dynamic monitoring under isotropic and anisotropic conditions using the same model reveals that the relative errors in amplitude and phase exceed 40%, and anisotropy must be adequately considered in reservoir monitoring with borehole-to-surface electromagnetic methods. For reservoir models with varying extraction rates, this study further examines the influence of a transmitter’s position on the electromagnetic response characteristics in anisotropic reservoir dynamic monitoring. The results indicate that effective monitoring cannot be achieved when the transmitter is located above the reservoir; however, when the transmitter is positioned below the reservoir, the borehole-to-surface electromagnetic method can significantly enhance the monitoring of reservoir dynamics. Full article