The 3D resistivity imaging surveying is adept at identifying structural details at various subsurface depths, and it can acquire valuable underground information even in complex geological environments. This technique has been widely applied in fields such as geological exploration, hydrogeology, and environmental monitoring. Currently, the 3D electrical resistivity surveys in the field are primarily deployed using regular grid and equidistant electrode layouts. However, when the survey area is influenced by obstacles or when the target being investigated is particularly complex, this may hinder the deployment of the electrode array in accordance with a rectangular grid. In some instances, it may even be impossible to position the electrodes directly above the target of investigation. The only viable option is thus to place electrodes around obstacles or special targets. In view of this, this paper studied unconventional electrode arrays and inversion imaging techniques of 3D electrical resistivity surveying in confined areas. It presents the design of three electrode arrays: “□”-shaped, “U”-shaped, and “L”-shaped. Furthermore, the study explores 3D resistivity finite element numerical simulation and inversion imaging techniques based on continuous electrical media. Finally, model experiments were conducted to verify the feasibility of these three special electrode arrays. We have applied the “□”-shaped electrode array to investigate the foundation structure of an ancient pagoda in Zhejiang Province, achieving promising results. This study provides valuable reference for the research and application of special observation in 3D electrical resistivity exploration.

Soil heavy metal contamination poses a serious threat to soil ecosystems and human health. Geochemistry is often used in soil heavy metal contamination research to identify pollution sources, identify elemental cycling mechanisms, and assess the spatial distribution and risk of contamination. However, it is difficult to directly reflect the spatial continuity and deep distribution patterns of contamination. Three-dimensional electrical resistivity tomography (3D ERT) technology often indirectly predicts the distribution of soil contamination by leveraging the electrical structure of the subsurface medium. However, many factors influence this electrical structure, leading to biased predictions. This paper combines geochemistry with 3D ERT technology. A nonlinear statistical model is established based on the geochemical analysis results and resistivity of soil samples. A 3D ERT model is then constructed. This model is used to further investigate the spatial distribution patterns of soil heavy metal contamination and assess the extent of contamination. This study investigated soil sample collection and chemical analysis of heavy metal content at a heavy metal contaminated site in Hunan Province. Antimony contamination was particularly severe in the soil. The 3D ERT data collection and inversion imaging were performed in the soil sample collection area. A 3D ERT model was established to analyze and evaluate the distribution range and extent of antimony contamination in the area. Comparing the antimony content predicted by the model with the actual test data, the results show that the error range is 0.6–16.6%, and the average error is 5.8%. The model has high accuracy, achieving good overall prediction and evaluation results.

As strategic critical metals, tungsten (W) and tin (Sn) require efficient exploration methods for effective resource development. This study implemented an advanced spread-spectrum induced polarization (SSIP) method in the Xitian mining district of southern China. Through optimized survey system configuration (maximum current electrode spacing of 5200 m, 12-channel acquisition, and five discrete frequency points), we achieved significant advancements: (1) a penetration depth of 1200 m, and (2) three- to five-times higher data acquisition efficiency compared to conventional symmetrical quadrupole arrays. Inversion results of resistivity and chargeability profiles from two parallel survey lines (total length 2.4 km) demonstrated an 85% spatial correlation between resistivity and chargeability anomalies, successfully identifying three mineralized veins. Drill-hole verification confirmed the presence of greisen veins (characterized by low resistivity 3%) and skarn veins (moderate resistivity 150–200 $\mathrm{\Omega }\cdot \mathrm{m}$ and chargeability 1.5–2%). The method exhibits a detection sensitivity of 0.5% chargeability contrast for deep-seated W-Sn polymetallic deposits, providing quantitative technical references for similar deposit exploration.