State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University
School of Resources and Safety Engineering, Chongqing University

煤与瓦斯突出是制约煤矿安全生产的重大灾害之一。我国煤层赋存环境复杂多变。针对时有发生的突出灾害事故，为了进一步提高突出预测和预警的准确率。梳理了突出发生机理的研究进展，指出地应力、瓦斯、煤体物理力学性质仍是防治突出的关键三要素，预测和预警的指标仍以此为基础；总结了突出预测的发展现状，指出预测的方法主要有单指标法、综合指标法和多属性指标法。主要存在预测位置局部、预测时间不连续、适应性差等不足；分析了突出预警的关键进展，指出基于突出孕育过程中的地应力、瓦斯、煤体演化机理，主要有声发射监测、电磁辐射监测、微震监测、瓦斯浓度时序监测，以及声电瓦斯综合监测预警方法。由于监测数据精度低、预警结果准确率低等不足而影响现场应用效果。基于当前突出预测和预警现状，以及煤矿安全智能化的需求，提出未来研究展望：突出预测应在启动判据与强度预测上，同时发展精细化、可量化指标；突出预警应跟踪指标的非线性变化，发展基于理论指标的趋势预警，基于事故经验的匹配预警，以及基于监控数据挖掘的前兆预警。通过组合预警模型，将定性与定量预警相结合，形成基于理论−经验−数据多重驱动组合预警模型，进一步提高预警准确率。同时发展矿山数字孪生建设，形成整体、连续、准确的煤矿突出灾害可视化智能预警。

Coal and gas outburst is one of the major disasters that restrict the safe production of coal mine. The coal seam occurrence environment in China is complex and changeable. Outburst disasters occur from time to time. In order to further improve the accuracy of outburst prediction and early warning, some progresses in the mechanisms of outburst were reviewed, and the three key elements, which are gas, crustal stress and coal mechanics, for the prevention of outburst were pointed out. The development status of outburst prediction was summarized. The prediction methods mainly include single index method, comprehensive index method and multi-attribute index method. The main shortcomings of prediction methods are small prediction range, non-continuous prediction, poor adaptability, etc. The key progress of outburst early warning was analyzed. Based on the changes of crustal stress, gas and coal in the process of outburst preparation, the early warning methods of outburst mainly include acoustic emission (AE), electromagnetic radiation (EMR), micro-seismic (MS), gas concentration, and AE-EMR-Gas comprehensive monitoring and early warning methods. The purpose of real time early warning is realized by judging the dangerous values of monitoring parameters. At present, the field application effect is affected by the low accuracy of monitoring data and the low reliability of early warning results. Based on the current situation of outburst prediction and early warning, as well as the demand for intelligent coal mine safety, the future research prospects were proposed. The outburst prediction should develop fine and quantifiable indexes about starting criteria and intensity prediction. Outburst early warning should track the nonlinear changes of indicators, develop trend early warning models based on theoretical indicators, empirical early warning models based on accident matching, and precursor recognition early warning models based on monitoring data mining. Through combining early warning models, combining qualitative and quantitative early warning methods, a combined early warning model based on theory, experience, and data was formed to further improve the accuracy of early warning. At the same time, the digital twin construction of mines should be developed to form an integrated, continuous and accurate visual intelligent early warning of coal mine outburst disasters.

国家自然科学基金面上资助项目(52174166)

梁运培，郑梦浩，李全贵，等. 我国煤与瓦斯突出预测与预警研究现状[J]. 煤炭学报，2023，48(8)：2976−2994.

LIANG Yunpei，ZHENG Menghao，LI Quangui，et al. A review on prediction and early warning methods of coal and gas outburst[J]. Journal of China Coal Society，2023，48(8)：2976−2994.