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

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Abstract

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.

Highlights

  • The EP signals response can reflect the stress state and damage evolution of coal seams.

  • The bilateral EP inversion model was established ahead of mining face to reveal the electric field distribution characteristics.

  • The EP inversion results could identify the hazardous zones of dynamic disaster for coal and gas outburst in the coal seam.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China, China (52104234, 51774277), National Science Foundation for Young Scientists of Jiangsu Province (BK20210504), and the Fundamental Research Funds for the Central Universities (2021xQN1104).

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Authors and Affiliations

  1. State Key Laboratory for GeoMechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Yue Niu, Feng Gao & Zhizhen Zhang

  2. Key Laboratory of Coal Methane and Fire Control, Ministry of Education, China University of Mining and Technology, Xuzhou, 221116, China

    Yue Niu, Enyuan Wang, Zhonghui Li, Baolin Li & Xin Zhang

  3. School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Yue Niu, Feng Gao & Zhizhen Zhang

  4. School of Safety Engineering, China University of Mining and Technology, No. 1 Daxue Road, Tongshan District, Xuzhou City, 221116, Jiangsu Province, People’s Republic of China

    Yue Niu, Enyuan Wang, Zhonghui Li, Baolin Li & Xin Zhang

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  1. Yue Niu
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  2. Enyuan Wang
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  3. Zhonghui Li
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  4. Feng Gao
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  5. Zhizhen Zhang
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  6. Baolin Li
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  7. Xin Zhang
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Correspondence to Enyuan Wang or Zhonghui Li.

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Niu, Y., Wang, E., Li, Z. et al. Identification of Coal and Gas Outburst-Hazardous Zones by Electric Potential Inversion During Mining Process in Deep Coal Seam. Rock Mech Rock Eng 55, 3439–3450 (2022). https://doi.org/10.1007/s00603-022-02804-z

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  • DOI: https://doi.org/10.1007/s00603-022-02804-z

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