Abstract
Abstract
Water damage seriously threatens the safe production of coal mines, so it is necessary to carry out advanced detection to determine the hydrogeological situation, and the preliminary survey often involves the drilling of on-site drill holes in the tunnel. The use of directional drill holes, combined with advanced geophysical prospecting technology, enables advanced water disaster detection with long distance and high precision and is independent of the tunnel environment influence. The transient electromagnetic method (TEM) is highly sensitive to low-resistivity anomalies and plays a crucial role in water damage detection. To address the size limitation of borehole detection, in this study, a small rectangular multi-turn loop borehole advanced detection method was developed (borehole TEM, BTEM) to detect low-resistivity anomalies within 10 m of the borehole in the radial direction. To satisfy the size requirements for borehole detection and the detection distance, a small rectangular multi-turn loop device with a width of 6 cm and a length of 50 cm was designed. To resolve the issue of self-inductance and mutual inductance enhancement caused by multi-turn coils, a uniform full-space low-resistivity abnormal body model was established using the Ansys Maxwell software, and we analyzed the vertical magnetic field component of the rectangular multi-turn small loop at different time points and the transient electromagnetic response of the different turns. Then, we determined the appropriate parameters for the transmitting and receiving device. The developed method was applied to several different experimental scenarios to obtain the electrical distribution of the anomalous body in front of the device, and the measured data were inverted and interpreted to obtain the apparent resistivity-depth profile. The results demonstrate that the inversion results align well with the actual situation, confirming the effectiveness of the BTEM. This research offers a potential solution for borehole advance detection and provides a solid theoretical foundation for further studies.
Funder
Huawei Technologies Co., Ltd