Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam

Coal remains an important fuel and energy, especially in China. For coal mining in deep mines, the threat of coal and rock dynamic disasters (such as coal and gas outburst) to safe production is becoming more and more serious with the greatly increasing geo-stress and gas pressure. Hence, it is particularly important to real-timely monitor and finely identify outburst-hazardous zones and their hazard levels during coal mining. However, conventional methods fail to continuously and precisely monitor outburst-hazardous zones in spatial distribution. Previous studies have shown that under the coupling action of stress and gas, the electric potential (EP) signals can be generated and their response characteristics are closely related to the loading state and damage evolution process of coal. The inversion imaging method can be utilized to analyze the spatial distribution of the EP signals. On this basis, the field tests were conducted to study the EP response characteristics to the mining process of deep coal seams and analyze the relationship between the EP response and outburst hazard. Moreover, in view of the EP inversion imaging mechanism, the bilateral EP inversion n model was established on the mining-disturbed coal seam ahead of the mining face and the field application was also carried out. Furthermore, on account of the membership index of fuzzy mathematics, the critical EP inversion value was proposed. Then the outburst-hazardous zones in the coal seam ahead of the mining face were divided finely and identified quantitatively. In the end, the verification result showed that the yellow zones enable to identify most of outburst-hazardous zones, thus effectively avoiding the missing identification. Besides, the red zones can improve the identification efficiency, which is conducive to focusing on identifying zones with a high hazard level. The study results provide a valuable new application method for finely identifying coal and gas outburst hazards and preventing coal and rock dynamic disasters in deep coal mines.

Automated summary

This study utilizes electric potential (EP) signals generated under the coupling action of stress and gas to real-time monitor and finely identify coal and rock dynamic disaster hazard zones. The study provides a valuable new method for accurately identifying outburst hazards and preventing coal and rock dynamic disasters in deep coal mines.