The essence of roof water inrush in coal mines fundamentally stems from the development of water-bearing fracture zones, facilitating the intrusion of overlying aquifers and thereby leading to water hazard incidents. Monitoring rock-fracturing conditions through the analysis of microseismic data can, to a certain extent, facilitate the prediction and early warning of water hazards. The water inflow volume stands as the most characteristic type of data in mine water inrush accidents. Hence, we investigated the feasibility of predicting water inrush events through anomalies in microseismic data from the perspective of water inflow volume variations. The data collected from the microseismic monitoring system at the 208 working face were utilized to compute localization information and source parameters. Based on the hydrogeological conditions of the working face, the energy screening range and its calculation grid characteristics were determined, followed by the generation of kernel density cloud maps at different depths. By observing these microseismic kernel density cloud maps, probabilities of roof water-conducting channel formation and potential locations were inferred. Subsequently, based on the positions of these roof water-conducting channels on the planar domain, the extension depth and expansion direction of the water-conducting channels were determined. Utilizing microseismic monitoring data, a quantitative assessment of water inrush risk was conducted, thereby establishing a linkage between microseismic data and water (inrush) data, which are two indirectly related datasets. The height of microseismic events was directly proportional to the trend of water inflow in the working face. In contrast, the occurrence of water inflow events and microseismic events exhibited a specific lag effect, with microseismic events occurring prior to water inrush events. Abnormalities in microseismic monitoring data partially reflect changes in water-conducting channel patterns. When connected with coal seam damage zones, water inrush hazards may occur. Therefore, abnormalities in microseismic monitoring data can be regarded as one of the precursor signals indicating potential floor water inrushes in coal seams.

中文翻译：

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集成微震监测预测煤矿突水灾害

煤矿顶板突水的本质是由于含水破碎带发育，有利于上覆含水层的侵入，从而导致水害事故的发生。通过微震数据分析监测岩石破裂状况，在一定程度上有利于水害的预测和预警。涌水量是矿井突水事故中最具特征的数据类型。因此，我们从涌水量变化的角度研究了通过微震数据异常预测突水事件的可行性。利用208工作面微震监测系统采集的数据计算定位信息和震源参数。根据工作面水文地质条件，确定能量筛选范围及其计算网格特征，生成不同深度的核密度云图。通过观察这些微震核密度云图，推断出屋顶导水通道形成的概率和潜在位置。随后，根据这些屋顶导水通道在平面域上的位置，确定了导水通道的延伸深度和扩展方向。利用微震监测数据，对突水风险进行定量评估，从而建立微震数据和突水（突水）数据这两个间接相关数据集之间的联系。微震事件的高度与工作面涌水趋势成正比。相比之下，涌水事件和微震事件的发生表现出特定的滞后效应，微震事件发生在突水事件之前。微震监测数据的异常部分反映了导水通道格局的变化。与煤层破坏区相连时，可能发生突水危险。因此，微震监测数据的异常可以被视为煤层潜在底板突水的前兆信号之一。