Electrical Resistivity Tomography (ERT) is an efficient geophysical exploration technique widely used in the exploration of groundwater resources, environmental monitoring, engineering geological assessment, and archaeology. However, the undulation of the terrain significantly affects the accuracy of ERT data, potentially leading to false anomalies in the resistivity images and increasing the complexity of interpreting subsurface structures. This paper reviews the progress in the research on terrain correction for resistivity methods since the early 20th century. From the initial physical simulation methods to modern numerical simulation techniques, terrain correction technology has evolved to accommodate a variety of exploration site types. The paper provides a detailed introduction to various terrain correction techniques, including the ratio method, numerical simulation methods (including the finite element method and finite difference method), the angular domain method, conformal transformation method, inversion method, and orthogonal projection method. These methods correct the distortions caused by terrain using different mathematical and physical models, aiming to enhance the interpretative accuracy of ERT data. Although existing correction methods have made progress in mitigating the effects of terrain, they still have limitations such as high computational demands and poor alignment with actual geological conditions. Future research could explore the improvement of existing methods, the enhancement of computational efficiency, the reduction of resource consumption, and the use of advanced technologies like deep learning to improve the precision and reliability of corrections.
Keywords: Deep learning in data interpretation; Electrical resistivity tomography (ERT); Geophysical exploration; Terrain correction techniques.
© 2024 The Author(s).