Research on fractal dimension warning of microseismic spatiotemporal data for rock mass failure

• Published in: Journal of applied geophysics Vol. 242; p. 105898
• Main Authors: Zhao, Congcong, Song, Dazhao, Zhou, Zilong
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2025
• Subjects: Deep hard rock mines; Disaster warning and application; Fractals and fractal dimensions; Microseismic monitoring; Rock mass area failure; Spatiotemporal data; Microseismic monitoring; Spatiotemporal data; Deep hard rock mines; Rock mass area failure; Fractals and fractal dimensions; Disaster warning and application
• ISSN: 0926-9851
• DOI: 10.1016/j.jappgeo.2025.105898

The research on rock mass failure and early warning mines has always constrained mine safety management and enterprise production efficiency. To interpret microseismic time and spatial data related to mining disasters, to achieve early warning of mining area disasters. Specifically, key elements of rock mass damage time and space are collected at the mining site, and events related to local potential damage are identified and extracted. They are then subjected to fractal interpretation, and an analysis method based on spatiotemporal fractal dimension is constructed. At the same time, the interpretation results are analyzed and verified by combining the distribution of on-site time and spatial elements and fractal dimension field cloud maps. Ultimately, a warning model centered on time and space was constructed, forming a method for multi-dimensional warning of mining disasters based on spatiotemporal data. When the fractal dimension value is greater than or equal to 0.52, a warning is issued; The warning accuracy can be improved from 103 m3 to 13 m3. The feasibility of the method system was verified through comprehensive evaluation of fractal dimension values and combined with the actual warning range on site, providing support for mine safety production. •Microseismic monitoring data and mine structural safety management.•Temporal and spatial elements of microseismic data.•Fractal theory and interpretation of microseismic events.•Mining disaster analysis and early warning.