Objective In China, as mineral resource mining is increasingly expanding towards the deep parts of the Earth, the safe and efficient exploitation of deep resources has become a major strategic and technological challenge at the national level to be addressed urgently. Understanding the movement patterns of mining-affected strata in deep environments will assist in improving the intelligent prevention and control of mine disasters, thereby ensuring the safe and efficient exploitation of deep resources.

Methods Targeting the complex and diverse forms of the overburden’s structural planes in deep mining, as well as a lack of characterization methods tailored to the evolutionary process of the structural planes, this study proposed a digital characterization method based on borehole wall images. First, by leveraging the structural information of rock masses derived from borehole wall images, this study developed a method for describing characteristic points that reflect the spatial morphologies and locations of structural planes. This allowed for the digitization of the three-dimensional spaces of the overburden’s structural planes. Second, based on the typical evolutionary characteristics of the structural planes, this study established a characterization system for the evolutionary process of the overburden’s structural planes, which involved the linear movement, torsional movement, and thickness evolution of the structural planes. Last, the proposed method was applied to a practical case, demonstrating its superiority in the fine-scale characterization of the evolutionary process of key zones of the structural planes compared to traditional simple image-based characterization methods.

Results and Conclusions  The proposed method can present the evolutionary characteristics of the structural planes of rock masses at different deep locations in the form of three-dimensional point cloud coordinates. Compared to traditional image display, the scatter plots of spatial characteristic points present more detailed change processes, enabling a more fine-scale characterization of the evolutionary process of key zones and the rapid search of typical characteristic zones of rock movement. The proposed method provides a more convenient digital basis for revealing the variation patterns of internal rock movement in the mining process, serving as a new digital method to characterizing evolutionary processes in research on the movement of strata during mine exploitation.