The layout of microseismic monitoring (MSM) station networks is very important to ensure the effectiveness of source location inversion; however, it is difficult to meet the complexity and mobility requirements of the technology in this new era. This paper proposes a network optimization method based on the geometric parameters of the proposed sensor-point database. First, according to the monitoring requirements and mine-working conditions, the overall proposed point database and model are built. Second, through the developed model, the proposed coverage area, envelope volume, effective coverage radius, and minimum energy level induction value are comprehensively calculated, and the evaluation reference index is constructed. Third, the effective maximum envelope volume is determined by taking the analyzed limit of monitoring induction energy level as the limit. Finally, the optimal design method is identified and applied to provide a sensor station layout network with the maximum energy efficiency. The method, defined as the S-V-E-R-V model, is verified by a comparison with the existing layout scheme and numerical simulation. The results show that the optimization method has strong practicability and efficiency, compared with the mine’s layout following the current method. Simulation experiments show that the optimization effect of this method meets the mine’s engineering requirements for the variability, intelligence, and high efficiency of the microseismic monitoring station network layout, and satisfies the needs of event identification and location dependent on the station network.

The particularity of the occurrence conditions of the ore body in Xianglushan Tungsten Mine determines the mining form of the ore body and the particularity of the ground pressure distribution after mining. A large number of mined-out areas, supporting pillars, and natural and human factors have formed a comprehensive disaster environment. This can lead to frequent disasters, great harm, serious economic losses, and the necessity of severe environmental protection operations in the mine. This study aims to establish a microseismic monitoring system according to the actual needs of the site and to reveal the law of ground pressure manifestation by analyzing the distribution characteristics of microseismic events; to analyze the occurrence stability of the goaf; further verify it laterally; and finally, demonstrate the feasibility and effectiveness of the microseismic monitoring sensor system. In view of the current ground pressure problem in Xiangxuoshan tungsten mine, the stress change characteristics during dynamic mining and filling were obtained through comparative analysis of different perspectives such as surface change, energy release, and mining loudness, and key areas were identified to improve the reliability of underground ground pressure monitoring. The results show that the process of deposit destabilization caused by ore body mining can be further analyzed by microseismic monitoring, and the combination of surface settlement, mining intensity, and energy release can verify the accuracy of stress distribution and ground pressure transfer. In turn, the general reliability of underground ground pressure hazard warning is empirically improved.

The thick ore bodies in the Xianglushan tungsten mine have been irregularly mined, forming a super large, connected irregular goaf group and tall, isolated irregular pillars inside. At the same time, there is a production capacity task of recovering residual and dangerous ore bodies. This poses the potential for serious ground-pressure disasters, such as roof caving, pillar collapse, and large-scale goaf collapse during mining. Based on the actual needs of the site, we established a microseismic monitoring system. After analyzing the mining and filling processes and their relationships, and, combined with the distribution characteristics of microseismic multiple parameters, we constructed a ground-pressure disaster warning mode and mechanism. We analyzed the stability of the goaf, further formed a warning system, and achieved disaster warning. In response to the current situation of the difficulty of early warning of ground pressure in the Xianglushan tungsten mine, continuous on-site monitoring of existing goaves, point pillars, and strip pillars, as well as analysis of stress changes during dynamic mining and filling processes, we explored scientific and reasonable early warning mechanisms and models, understanding the relationship between the changes in microseismic parameters during dynamic mining and filling processes and ground pressure, studying and improving the reliability of underground microseismic monitoring and early warning, and achieved the internal connection between building early warning systems and the prevention of ground-pressure disasters. The results indicate that the mining and filling process of the ore body is the main factor in maintaining a stable and balanced distribution of underground ground pressure in mining engineering. Microseismic monitoring can invert the evolution of ground pressure and form a feedback system with ground-pressure warning, achieving mine safety management.

Potential faults are common sensitive geological bodies that affect the safe mining of underground mines, often leading to major accidents such as rock instability and rockburst during mining. The failure mechanism of faults has been widely studied. However, due to the spatiotemporal specificity of fault occurrence, there are few theoretical and mathematical methods suitable for effective analysis in mine safety risk management. This study aims to introduce fractal theory to characterize the spatiotemporal activity fractal characteristics of induced faults intersecting the mining site and roadway during the mining process of the Ashele copper mine in China. Using microseismic systems and fractal theory, a spatiotemporal fractal model of the fault slip process is constructed, and a fractal analysis method is proposed. The fractal dimension value is calculated based on the spatiotemporal parameters of different segments and stages. The fractal dimension is used to characterize and analyze the evolution of the fault. The physical formation process of potential faults and the relationship between fractal dimension values and multiple parameters, including spatial clustering, regional distribution characteristics, and energy-release characteristics, were analyzed based on the division of events into different time stages. Discovering fractal dimension’s temporal and spatial–temporal characteristics can provide technical references for mine disaster prevention.

The early warning of disasters such as ground pressure in deep hard rock mines has long constrained the safe and efficient development of mining activities. Based on fractal theory and fractal dimension interpretation, this study constructs a microseismic monitoring system for mining areas, extracting key elements, particularly time and energy elements. Using the box-counting method of fractal theory, the study investigates the fractal dimensions of microseismic time–energy elements, data interpretation, and disaster source early warning. Through parameter analysis, events related to local potential failure are identified and extracted, and disaster characteristics are revealed based on microseismic activity. A time–energy fractal dimension-based analysis method is developed for preliminary fractal analysis and prediction of regional damage. A time–energy-centered early warning model is constructed, narrowing the prediction range to a scale of 10 m. Based on the fractal interpretation of time–energy data, the prediction and early warning of rock mass failure in mining areas are achieved, with the reliability of nested energy warnings ranging between 91.7% and 96.2%. A comprehensive evaluation criterion for fractal dimension values is established, enabling accurate delineation of warning zones and providing scientific decision-making support for mine safety promotion.

The development of mineral resources in China is increasingly targeting the recovery of residual ore bodies, which significantly elevates geotechnical risks, including goaf collapse and pillar instability. To address these challenges, this study developed an integrated ground pressure control system that coordinates mining, backfilling, and support technologies. The system is dynamically optimized through a microseismic monitoring-based feedback mechanism, forming a closed-loop disaster management framework. Based on a two-year microseismic monitoring campaign (October 2012–September 2014), which captured 103 located events, a strong spatial clustering of seismic activity was observed, with over 7% of event pairs occurring within 20 m, particularly at the abutment of the syncline ore body. A zonal early-warning model was established using key parameters (event rate ratio ≥ 3, cluster density ≥ 15 events/10,000 m³, energy ratio ≥ 4). The effectiveness of the control system was validated by a 5.9% reduction in located events and a decrease in maximum magnitude from 0.3 to −0.2, despite a 34% year-on-year increase in ore production in 2019. These results demonstrate that the integrated approach provides a reliable and adaptive solution for ground pressure disaster prevention during residual ore recovery.