A review on prediction and early warning methods of coal and gas outburst

Abstract

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.

Keywords

• coal and gas outburst
• outburst mechanisms
• outburst prediction
• outburst early warning
• coal mechanies