High-resolution transient electromagnetic data hybrid dimensional detection method of water hazard in coal mine dataset

Transient electromagnetic method (TEM) surveys in engineering geophysics research can be used to detect low-resistivity target bodies such as water. In this study, we developed a hybrid-dimensional TEM data inversion method that achieves fast and stable 3D inversion results. The newly developed method produces high-resolution coal mine water hazard detection results, which solves the problem of misestimating water hazard anomalies. This method first constructs an initial model reflecting the main electrical structure of the survey region. Then, 3D inversion with the initial model is designed to obtain a precise resistivity model subsurface that can reflect the distribution of water hazards. The initial model is constructed by weighted layered constraint inversion (WLCI) to obtain a reliable subsurface resistivity model of sedimentary strata in coal mines. In addition, as we use unstructured tetrahedral meshes for model discretization, the improved 3D inversion method can effectively eliminate the influence of high-relief topography and improve the positioning accuracy of anomalous bodies. The application of the synthetic model shows that hybrid-dimensional inversion can achieve accurate identification of water hazard-prone geological bodies from reliably restored electrical distributions underground. Field data processing results show that the detection of water in a goaf is effective in a coal mine in Ordos, Inner Mongolia, China. The resistivity distributions of sedimentary strata can be accurately restored by the new method, which fits well with the known geology and underground drilling.