7th Asia Pacific Meeting on Near Surface Geoscience and Engineering

This study introduces the Short-Offset Transient Electromagnetic (SOTEM) method for deep ore exploration, representing a significant advancement over traditional electromagnetic techniques. While methods such as Controlled Source Audio-frequency Magnetotellurics (CSAMT) and Long-offset Transient Electromagnetics (LOTEM) are widely used in mineral exploration, they are often constrained by depth limitations and resolution issues stemming from plane-wave field assumptions and signal strength challenges. The SOTEM approach employs a ground wire source with bipolar currents and utilizes shorter offsets—ranging from 0.3 to 2 times the detection depth. This innovation enhances signal strength, reduces noise interference, and minimizes averaging effects. To improve data interpretation accuracy, the adaptive regularized inversion algorithm (ARIA) is applied. A case study conducted at the Xiaoshan Mine in northern China demonstrates the practical application of SOTEM. Survey lines successfully identified high-resistivity formations and potential mineralization zones. Results indicate that SOTEM offers high detection accuracy and deep penetration capabilities, making it particularly effective in complex terrains, such as mountainous regions. Key advantages include increased signal strength, enhanced resolution, reduced transmitter power needs, and improved efficiency for deep-mining applications. The Xiaoshan case confirmed the successful detection of mineralization anomalies, highlighting the method’s suitability for deep geological exploration.

The near-surface structure plays a crucial role in the quality of seismic imaging for oil and gas exploration. To measure the velocity structure of near surface, the micro logging method is commonly used. While effective, this method faces limitations in regions where drilling is not feasible, such as urban areas, airports, railways, or gravel-rich terrains. Surface waves, which propagate along the Earth’s free surface, offer a potential alternative. We established a workflow for surface wave acquisition, processing, and interpretation using small trace intervals of less than 5 meters. This approach enables surface wave surveys to produce interpretation results comparable to those obtained from micro logging. Both theoretical models and actual drilling data demonstrate that small trace interval surface waves can match or exceed the near-surface detection capabilities of traditional micro logging.

Faults are a common type of geological structure, widely found in areas with active tectonic development. Fault zones may be accompanied by a large number of fractures, which are conducive to the formation of complex fracture networks in oil and gas development. However, faults also exhibit characteristics of low strength and susceptibility to deformation. Due to excavation and seepage effects, there are wellbore surrounding stress field and seepage stress fields near horizontal wells. To clarify the influence of the wellbore surrounding stress field and seepage stress field on the near-wellbore faults, this study established two different physical models, derived general theoretical formulas for the near-wellbore faults under the influence of the wellbore surrounding stress field and seepage field, and combined this with the basic fault activation theory based on the Mohr-Coulomb criterion. The study also defined the regional activation rate, analyzed the activation risk of near-wellbore faults under the influence of the two stress fields, and designed orthogonal experiments to study the influencing factors. This research provides certain reference significance for optimizing the selection of horizontal well locations.

The induced polarization (IP) effects, associated with polarizable bodies, are increasingly observed in the transient electromagnetic (TEM) surveys, often characterized by rapid voltage decay followed by sign reversal. In a field TEM survey over a Volcanogenic Massive Sulfide (VMS) deposit, which exhibits high IP properties, an anomalous voltage decay without sign reversal was observed. To enhance data interpretation, we developed a 1D model using Cole-Cole parameters derived from spectral induced polarization (SIP) measurements of borehole core samples from the VMS area. The synthetic data exhibit rapid decay without sign reversals, consistent with the field observations. By performing both resistivity-only (RO) and IP-incorporated inversions, the results demonstrate that only the IP-incorporated inversion accurately fits the data and provides a reliable interpretation. This highlights the importance of carefully analyzing anomaly late-time voltage decay in TEM data, particularly in scenarios with moderately resistive backgrounds or deeply buried polarizable bodies. This study advocates for an approach that integrates IP effects to provide more accurate and reliable evaluations in regions with polarizable targets such as sulfides or clays.

Ground Penetrating Radar (GPR) has been an integral part of utility surveying since the early 2000’s and the use of GPR systems for civil engineering applications and utility mapping has been the focus of research since the early days of the development of the GPR method.

This study examines the difference between the two main developments for utility surveying – single-channel GPRs and high-density GPR arrays. Comparative data was collected in the town of Gainsborough, UK with the aim of discussing and highlighting the advantages and disadvantages for each system.

The results demonstrate the high efficiency of multi-channel array GPR, offering higher resolution results, increased data quality and faster data collection. However, single-channel GPR can be more efficient and cost-effective in hardware and data collection in areas with tight urban footpaths/sidewalks, such as city centres with numerous street furniture and obstacles.

Time domain induced polarization (TDIP) has emerged as a highly effective tool for characterizing soil and groundwater contamination. Numerous studies have focused on the objective of enhancing accuracy of TDIP results. However, the acquisition of high quality TDIP data has received less attention than it deserved. In this study, three data acquisition methods were evaluated across seven distinct sites, with a particular focus on the controlling factors that influence data quality. This study addresses the questions about how to select a reliable TDIP acquisition method. The results demonstrate that there are significant differences in the raw data obtained through different acquisition methods, with the inverted results derived from these datasets exhibiting varying discrepancy. The data quality associated with the dual cables utilizing non-polarizable electrodes layout (Dual-CL-NP) is markedly superior, thereby ensuring the reliability of the results. Furthermore, apparent resistivity and measured voltage are identified as the key factors on data quality. The threshold values for selecting the acquisition method are determined. The Dual-CL-NP method should be utilized when the averaged apparent resistivity is less than 7.9 Ω•m. Consequently, a guideline for TDIP data acquisition is proposed, which addresses the limitations associated with TDIP data quality and facilitates its advancement

The fast sweeping method (FSM) is a widely used numerical scheme for solving eikonal equations. It employs a local solver at each grid point and use Gauss-Seidel iteration to calculate the traveltime field. Due to the Gauss-Seidel iteration, the conventional programming of FSM is implemented by element-wise operations, making it difficult to leverage convenient GPU parallelization. This constraint hinders the potential for further improving the computational efficiency of the traveltime field, especially when dealing with large-scale models. In this paper, we adopt the Jacobi iteration instead and propose a tensorization implementation of FSM for factored eikonal equation with a first-order Lax-Friedrichs local solver. Particularly, it is very easy to carry out this implementation on computing device equipped with GPUs. Numerical experiments show that, although the number of iterations required for the algorithm to converge has increased a lot, tensor programming can greatly save computation time with almost no additional memory requirements.

Short offset transient electromagnetic method (SOTEM) is a new electromagnetic detection method, which is suitable for mineral resources exploration. In order to optimize the data processing results, this paper introduces the CNN-BiLSTM network model for one-dimensional inversion. The response of the electric field component and the magnetic field component of the theoretical model is used as input, and the real resistivity is used as the training template for training. The observed data of the two fields can be quickly inverted by the trained network model calculation. It has been verified that the inversion method has excellent accuracy and layered structure characterization ability, good stability for low and high resistivity anomalies, and high computational efficiency.

Surface wave waveform inversion (SWI), recognized as a high-precision technique for shallow subsurface imaging, is extensively employed in the detection of underground structures. However, SWI faces several challenges that hinder its broader application in engineering, including the absence of low-frequency components, limited sensitivity to longitudinal waves and density parameters, and a pronounced reliance on initial models. To mitigate the Cycle-Skipping phenomenon stemming from low-frequency information loss and initial model dependency, this study introduces a novel multi-parameter waveform inversion approach for surface waves, leveraging a partial convolutional Siamese network (SIAMPCNN-SWI). This approach ingests observational and initial data into a shared-parameter partial convolutional Siamese network to extract multi-scale features, thereby enhancing the recovery of low-frequency information and reducing the dependency on initial models. Subsequently, the feature discrepancies extracted are utilized as loss functions for estimation, and automatic differentiation is harnessed for backpropagation, enabling the high-precision reconstruction of shallow subsurface structures. Numerical simulations and field data validations demonstrate that this method outperforms traditional approaches in terms of inversion accuracy, stability, and computational efficiency for multi-parameter inversion tasks. This method offers a robust solution for shallow subsurface exploration under complex geological conditions and holds significant potential for broader application.

This study introduces an optimized methodology for mapping directional contaminant flow paths by integrating rotating surface electrodes with in-hole Electrical Resistivity Tomography (ERT), supported by numerical simulations and validated through field application. Surface electrodes are rotated around a borehole at multiple azimuths while keeping in-hole electrodes stationary. Four electrode configurations—A-BMN, A-MNB, AB-MN, and AM-NB—are assessed using synthetic azimuthal apparent resistivity datasets. Directional sensitivity is evaluated for two scenarios: in-panel anomalies, where surface electrodes align with subsurface anomalies, and off-panel anomalies, where anomalies are opposite the surface electrodes. Arrays with high in-panel and low off-panel sensitivity exhibit reduced symmetrical effects and enhanced directional performance. The results show that symmetrical effects and limited directionality affect the A-BMN and A-MNB arrays, while the AB-MN array displays low accuracy and poor performance. In contrast, the AM-NB array demonstrates superior accuracy, minimal symmetrical effects, and strong directionality. Field tests validate the numerical findings, revealing significant resistivity variations at specific azimuths that align with the orientation of the injection well. Rose diagrams effectively indicate dominant flow paths and contaminant migration directions. This integrated approach offers a reliable, cost-effective solution for detecting preferential flow pathways and advancing subsurface mapping techniques.