Abstract: During underground coal mining, surveying operations are commonly constrained by limited roadway space, poor intervisibility, and the restricted applicability of certain surveying instruments, which makes it difficult to establish conventional survey control networks and to achieve effective measurement error control for survey points. Moreover, with the increasing requirements of underground mine safety production for 3D models, transparent geology, and inversion validation based on multi-source data fusion, conventional surveying methods have become insufficient for real-time, full-coverage, and high-precision applications, while the data silo effect among different data sources remains evident. To address these issues, this study proposes an integrated method in which a high-precision surveying control network is established and point cloud data acquired by 3D laser scanning are used to construct a high-precision 3D model. In addition, geophysical exploration data, including those obtained by the transient electromagnetic method and the seismic wave method, are incorporated and collaboratively processed using professional 3D modeling and geological inversion software. On the basis of efficient 3D model construction for mine roadways and goafs, the model is further integrated with the geometric morphology and physical property parameters of geological bodies for coordinated inversion and validation according to different operational requirements. The validation results show that the proposed method controls the positional accuracy error of irregular spatial points within ±1 cm and improves the accuracy of spatial volume calculation by more than 4% compared with total station surveying. Within a detection range of 150 m, the identification error for geological anomalies such as faults, fractured zones, and water-rich zones is less than 10 m.