Coal mine goaf detection remains confronted with the lack of fast, effective and low-cost exploration means, especially for the accurate prediction of mining threats primarily caused by hydraulic infiltration. The rapid popularization of passive electromagnetic methods has contributed greatly to improving the interpretation effects of different types of goafs. This paper, firstly, summarizes the pros and cons of various exploration methods in goaf detection. Then, the feasibility of goaf detection using novel passive electromagnetic methods (e.g., the super low frequency alternating magnetic component method (SLF) and audio frequency magnetotelluric method (AMT)) is proposed and further discussed. With well-designed geo-electrical goaf models, the theoretical results demonstrate that the semi-quantitative interpretation of SLF responses can be directly used for the delineation of the target layer in the estimated depth range. In contrast, 3D inversion provides more information about conductive targets with the appropriate initial model selection. Then, shallow, low-resistive targets can be more accurately allocated in the inversion maps. Moreover, the real data interpretation results from study areas demonstrate that the SLF method can utilize the magnetic component responses to effectively identify the fault structures, and indirectly contributes to judge the goaf collapse locations in favor of describing the potential distribution of fracture water infiltration. Combined with the three-dimensional (3D) resistivity inversion of AMT data, the low-resistive water-rich areas within the depth of 400 m were revealed. The inverted depth distributions are basically consistent with those of the water-filled goafs and surrounding layers, which were also confirmed by known logging data. The detailed delineations of water-control fracture zones can be inferred to relate to aquifers in some mining areas; this can reveal potential collapses that require successive mining planning. In specific working faces, goaf risks have been handled in advance by strengthening the continuous monitoring of the water level and water inflow. The above verification has laid a theoretical and practical foundation for passive electromagnetic interpretation methods for effectively predicting collapse-type risks or hydraulic threats in coal mine goafs.
