3D inversion of 2D electrical resistivity data for geotechnical analysis

Geophysical methods are effective tools for geotechnical analysis. In particular, the two-dimensional electrical resistivity method is widely applied in the determination of broken, cracked, and karst cave structures in many countries around the world. The information given by this method plays an important role in preventing and mitigating the risk of geological hazards caused by geological structures. Geotechnical analysis is also an important step in civil construction. However, the interpretation of two-dimensional problems with individual sections still has certain limitations, such as the delineation of the spatial distribution of interesting objects in the entire survey area. We propose a new data processing procedure for the two-dimensional electrical resistivity methods based on rearranging the data as the input of three-dimensional inversion. If the distribution of survey lines is dense enough, we can use two-dimensional data to solve the three-dimensional inverse problems. This inversion will give us a diagram of resistivity distribution in three-dimensional space, which is intuitive and high detail in identifying interesting objects. In this study, the authors have solved the three-dimensional inverse problems from the two-dimensional electrical resistivity survey carried out in the Hoa Lac area, west of Hanoi city. The result shows that the resistivity distribution in three-dimensional space not only increases the intuition but also the accuracy in reflecting the spatial distribution of hidden underground objects. This also defines the localization and determination of fracture zones in the study area as more reliable than explained in each section according to the results of solving two-dimensional inverse problems. The effectiveness of this new method has been proven when compared with drilling results in the studied area.

How to Cite

Pham, D.Ngoc, Pham, K.Ngoc, Lai, P.Hop and Thi, N. 2022. 3D inversion of 2D electrical resistivity data for geotechnical analysis. Journal of Mining and Earth Sciences. 63, 6 (Dec, 2022), 45-52. DOI:https://doi.org/10.46326/JMES.2022.63(6).05.

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