## 1 Introduction  
About 27% of China's proven coal resources are exposed to different degrees of water hazards, of which the floor water inrush hazard is particularly prominent in North China [1, 2]. With the gradual increase in the depth of coal mining in China, the spatial relationship between the panel and the aquifer is more complicated, and the environment of geo-stress and permeability pressure is more variable; the severity and frequency of the occurrence of water inrush generally increase. Researchers have made many advances through statistical methods [3, 4], mechanical analysis [5, 6], numerical simulation [7, 8], physical experiments [9, 10], and other research methods, which have effectively revealed the mechanism of floor water inrush and proposed a variety of prevention and control methods. All of the above methods make too many assumptions, and the reality of the geological environment is very complex and variable, so there are often limitations for practical problems. Microseismic monitoring is a non-destructive, real-time, dynamic, large-scale observation measurement technology [11, 12], through monitoring the propagation of elastic waves in the stratum, it can reflect the performance of faults, joints, and other discontinuous complex structures, water conduction channels, hydraulic source, and other information [13, 14]. With the rapid development of computer technology and three-dimensional visualization in recent years, it has been more widely used in the prevention of coal mine water inrush. Moment tensor inversion (MTI) theory was introduced in early seismic studies [15; 16]. Microseismic information can be described mathematically using MTI theory, and so microseismicity due to rock fracture can be expressed as a linear combination of moments, which will be very helpful in understanding the type and mechanism of fracture [17]. In terms of application in the field, [PERSON] et al. [18] obtained the measured parameters such as the activation pattern of the geological structure, the depth of the floor damage zone, the height of the fractured zone, and the size of the reasonable coal pillar through the three-dimensional display of the microseismic positioning results. [PERSON] and [PERSON] [19] established a prediction model of water-conducting channel based on microseismic monitoring signal mutation analysis by fitting the activation damage depth data from on-site microseismic monitoring. [PERSON] et al. [20] developed a method of identifying water-conducting channels based on the inversion of microseismic energy density and rupture connectivity of the rock layer, and verified it in the field by visual resistivity monitoring data. [PERSON] et al. [21] utilized microseismic monitoring to classify the water-conducting channels into four types and find the weak areas of the grouting curtain, which compensates well for the weak links of water inrush. The above research results can be used to locate the position and types of water-conducting channels, classify the areas with high water-surge potential, and be applied in the prevention and control of water hazards on the floor and roof dynamic disasters in coal mines through microseismic monitoring. However, they all belong to the monitoring during the process of engineering disturbance and lack of timeliness, which means that violent water inrush accidents cannot be avoided if the water-conducting channel is connected to a water source with high water pressure and high water volume. There is a lack of research on the distribution patterns of microseismicity events induced by other man-made works (floor grouting, etc.) during the period when the working face has not yet been mined, and whether it can be used as an indicator for predicting water inrush. We refer to the microseismicity induced by grouting works prior to coal seam mining as \"Pre-mining Grouting-induced Microseismicity, PMGIM\".