Abstract: Geological assurance technology constitutes a fundamental basis for achieving safe, efficient, and environmentally sustainable coal mining, and serves as a critical pillar supporting the intelligent development of coal mines. Transparent geological assurance systems enable comprehensive and dynamic perception of mine geological conditions, facilitating the end-to-end application of geological information-from acquisition, modeling, and analysis to decision-making-and have thus become an integral component of intelligent coal mine operations. The system is centered on multi-source spatiotemporal information perception and relies on high-resolution three-dimensional(3-D) seismic exploration, directional long-distance drilling equipment, integrated borehole-based advanced geophysical prospecting, and real-time seismic monitoring during mining and tunneling to dynamically identify key geological parameters such as coal-rock undulation, structural anomalies, hydrogeological hazards, and roof-floor stability. Multi-source heterogeneous geological data are integrated through coordinate registration, cross-validation, and joint inversion methods, while kriging interpolation, radial basis functions, and stochastic simulation algorithms are employed to achieve continuous and uncertainty-quantified representations of geological geometries and property fields, thereby constructing a high-precision 3-D geological model of the entire mine for continuous spatial characterization. On this basis, a “mining-geology” digital twin couples dynamic engineering data, such as mining equipment operation and support activities-with the 3-D geological model. Through virtual-real mapping technology, the system enables real-time feedback of geological bodies and their associated attributes to mining operations and, combined with multi-field coupled disaster mechanism models, analyzes the perturbation effects of mining activities on geological structures, providing early warning and risk-informed decision support for coal mine production. Meanwhile, the system can quantify complex geological conditions and achieve high-frequency, real-time dynamic updates of geological information adapted to mining processes. Empirical applications have demonstrated that transparent geological assurance systems effectively support three-dimensional forecasting and management of concealed hazard factors, realizing a “Transparent Geology+” approach to mine disaster prevention and control, and supporting mining geological navigation applications such as shearer cutting, roadway excavation layouts, and support optimization. In summary, transparent geological assurance technology has achieved notable advancements; however, due to the complexity of mine geological conditions, challenges remain in the degree of geological information perception, the construction of adaptive geological analysis models, and the intelligent integration of equipment and models. Consequently, current systems still face issues related to model update efficiency and equipment-model coordination. In the future, research should continue to advance across four key dimensions: the information perception layer, the model twin layer, the intelligent cognition layer, and the collaborative control layer. It should focus on high-precision multi-source information detection and fusion, intelligent evolution of digital twins, intelligent analysis technologies based on geological vertical large models, and integrated applications for full-mine production systems and equipment, thereby providing sustained theoretical support and technological pathways for intelligent and transparent geological assurance in coal mining.