Geophysical simulation of landslide model based on electrical resistivity and refraction seismic tomography through unstructured meshing

Mass movements of land, such as landslides, pose significant threats to human safety and infrastructure. This study focuses on advancing the understanding of landslide dynamics through the application of geophysical surveys, specifically Electrical Resistivity Tomography (ERT) and Seismic Refraction Tomography (SRT). Unstructured meshing, as a pivotal technique in geophysics simulation studies, provides flexibility in discretizing complex geological structures. This method allows for refined mesh elements where needed, optimizing computational resources. In the field of geophysics, unstructured meshing is particularly advantageous for accurately representing subsurface heterogeneities. This study employs pyGIMLi, a Geophysical Inversion and Modeling Python library. This Python programming library, though devoid of a GUI, offers a comprehensive suite of tools for geophysical data analysis and inversion. This library incorporates unstructured meshing capabilities. This feature enhances the accuracy of simulations, enabling researchers to model intricate geological formations with more precision. Using this library empowers users to seamlessly generate, manipulate, and analyze unstructured meshes, facilitating robust simulations and detailed investigations of subsurface properties in geophysics. In this study, we present a novel approach to simulate a 3-layered landslide using ERT and SRT, coupled with inverse modeling through utilizing the unstructured meshing of the inversion area. The synthetic model produced has a depth of study extending to 65 meters. The SRT model reveals a dense coverage in layer 2, providing crucial information about the subsurface characteristics. The utilization of ERT and SRT in tandem allows for a comprehensive understanding of the landslide structure, offering insights into detecting the slip surface of the landslide. The study's innovative methodology provides a robust framework for the analysis of complex geological scenarios. The results obtained from this simulation contribute to the broader knowledge of landslide dynamics and offer a valuable tool for assessing and mitigating landslide risks in similar geological settings.