Jizhong Energy Group Corporation Ltd.
Key Laboratory for Mine Water Disaster Detection and Prevention and Control
Hebei Mine Microseism Key Laboratory
Hebei Coal Research Institute Co., Ltd.

现阶段，我国越来越多的矿井进入深部开采和下组煤开采期，煤层开采受岩溶水害威胁严重，矿井深部突水隐患探查不清，采掘过程中缺乏科学有效的突水监测预警手段，是造成矿井突水灾害的主要原因。为夯实水害预警监测基础，提出“双驱动”煤矿水害微震预警架构，利用数据驱动与模型驱动，实时动态监测工作面底板突水风险等级及范围，对突水风险趋势智能预测预报。在数据驱动的框架下，以微震事件时空演变规律为切入点，通过对微震事件震源机制反演与属性分析，为导水通道形成判断提供依据，结合水文动态数据变化，建立相应突水判据，对突水风险进行评价。在模型驱动的框架下，构建含分类预测、聚类分析等多种算法的深度学习模型，将典型微震事件群作为模型输入，定量动态预测未来微震事件发生的空间范围与聚集度，继而确定突水风险等级与危险区域。基于微震数据及模型的煤矿水害“双驱动”预警技术，开发了相应的区域性煤矿水害三维智能预警平台，实现了水害风险特征的动态智能预警预测和危险区域的三维可视化显示。实践证明，采用确定性数据研判与智能模型预测的“双驱动”微震预警体系，对突水风险等级和范围的预测效果显著，实现了对底板水害高风险区域的精确预警与防控。

At the present stage, more and more mines in China are entering the deep mining and lower group coal mining period. The coal seam mining is seriously threatened by karst water, the hidden danger of water inrush in the deep mine is unclear, and the lack of scientific and effective water inrush monitoring and early warning means in the mining process is the main reason for the water inrush disaster in the mine.In order to consolidate the foundation of early warning and monitoring of water disasters, a “double drive” micro earthquake early warning framework for coal mine water disasters is proposed. Using data drive and model drive, the risk level and scope of water inrush from the floor of the working face are monitored dynamically in real time, and the trend of water inrush risk is predicted intelligently.Under the framework of data driving, taking the temporal and spatial evolution law of microseismic events as the breakthrough point, through the inversion and attribute analysis of the source mechanism of microseismic events, it provides a basis for judging the triggering cause of microseismic events, the rupture trend and the formation of water diversion channels. In combination with the changes of hydrological dynamic data, it establishes the corresponding criteria for water inrush and evaluates the risk of water inrush.Under the framework of model driven, a deep learning model with multiple algorithms such as classification prediction and cluster analysis is constructed. The typical microseismic event cluster is used as the model input to quantitatively and dynamically predict the spatial range and concentration of future microseismic events, and then determine the water inrush risk level and risk area. Based on the “double drive” early-warning technology of coal mine water disaster based on microseismic data and model, the corresponding regional 3D intelligent early-warning platform of coal mine water disaster is developed, which realizes the dynamic intelligent early-warning prediction of water disaster risk characteristics and 3D visual display of dangerous areas.The practice has proved that the “double drive” microseismic early warning system using deterministic data research and intelligent model prediction has a remarkable effect on predicting the level and scope of water inrush risk, and has realized accurate early warning and prevention and control of high-risk areas of floor water damage.

张党育，武　斌，贾　靖，等. 基于微震数据及模型的煤矿水害“双驱动”预警体系构建与应用[J]. 煤炭科学技术，2023，51（S1）：242−255.

ZHANG Dangyu，WU Bin，JIA Jing，et al. Construction and application of “Dual-drive” pre-warning system for coal mine water disaster based on microseismic data and model[J]. Coal Science and Technology，2023，51（S1）：242−255.