# Applications of Microseismic Monitoring Technique in Coal Mines: A State-of-the-Art Review
## 5 Some Prospects of the Microseismic Monitoring Technique in Coal Mines
### Comprehensive Assessment of Mining-Induced Instabilities  
The mechanisms of disasters in deep coal mines are complicated and influenced by many contributing factors, e.g., the stress regime, geological defects, excavation geometry, and rock mechanical properties. It is very challenging to monitor, analyze, and warn of mining-induced instabilities using a single research method such as theoretical analysis, a laboratory test, numerical modeling, or a field survey. Both theoretical analysis and numerical modeling have to simplify the complicated boundary conditions of deep excavations, and laboratory tests, limited by model dimensions, make it difficult to study the effect of geological defects. On the other hand, the accuracy of field monitoring data greatly influences disaster mitigation in coal mines. Therefore, an integrated approach that combines features and leverages the strengths of various methods is prospective for more accurate assessment and control of mining-induced instabilities.  
The mechanical parameters of rocks deteriorate continuously during coal mining, while the mechanical parameters of fresh rock specimens are usually employed in numerical modeling to study the evolution of rock damage, which means the numerical results do not align well with actual scenarios. [PERSON] et al. [124] developed a damage model of rocks concerning the relationship between microseismic source parameters and releasable strain energy, which used microseismic source parameters (e.g., seismic energy, apparent volume, source dimension, and seismic efficiency) as inputs to update the mechanical parameters of rocks in a numerical model dynamically and analyze the evolution of surrounding rock damage in the Shirengou iron mine. [PERSON] et al. [108] integrated the improved theoretical model considering confined aquifer pressure and RFPA numerical modeling to investigate the stress regime variation and floor failure process, and further estimated the floor failure depth using microseismic monitoring data. The flow chart for assessing the risk of the water intrusion is shown in Figure 13.  
The microseismic monitoring technique can continuously capture coal/rock fracturing at a wide range of scales and is commonly used in conjunction with other monitoring methods, e.g., the stress meter, extensometer, and borehole televi  
Figure 12: Image learning configuration and flow chart for microseismic signal recognition: (**a**) image learning configuration; (**b**) flow chart, revised from [123].  
interpret the stress and deformation field of coal/rock limited by the quantity of data from a few pre-defined monitoring points, which will affect the accuracy of assessment and early warning of mining-induced disasters based on microseismic monitoring and other monitoring data. Laser scanning can be used in underground mines for convergence monitoring, change detection, and deformation tracking [125], as it is able to acquire the deformation field of coal/rock mass. Mobile laser scanning, e.g., vehicle- and drone-mounted [126], is highly suitable for coal mining environments due to its ease of operation and the ability to quickly scan large areas. Therefore, microseismic monitoring and laser scanning are effective in detecting the microcracking field and deformation field of coal/rock, and they can be used in combination for a comprehensive assessment of mining-induced disasters.