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Regional hazard prediction of rock bursts using microseismic energy attenuation tomography in deep mining

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  • Mingwei Zhang

    (China University of Mining and Technology)

  • Shengdong Liu

    (China University of Mining and Technology)

  • Hideki Shimada

    (Kyushu University)

Abstract

Rock burst prediction is a worldwide challenge that we have long tried to overcome. This study tentatively proposed a method to regionally predict rock burst hazards using microseismic energy attenuation. To verify the feasibility of the proposal, first, the mechanism of microseismic energy propagation and attenuation in rock medium was explored, and dominant attenuation characteristics of microseismic waves were analyzed. Second, a spatial attenuation model of microseismic energy was established, and the average energy attenuation coefficient for each wave path was defined. A 3D seismic energy attenuation inversion algorithm was put forward, and the corresponding computation matrix was developed. Third, a continuous microseismic field investigation was carried out in a deep coal mine. Seismic energy attenuation coefficient was confirmed using the calibrated focus position and energy determination. Based on data discretization processing, energy attenuation inversion and tomography, potential rock burst hazard regions were strictly zoned in mining areas. Finally, regional prediction results obtained from the microseismic energy attenuation were compared with the direct measurement results obtained from the classical drilling dust method to verify the reliability of proposed approach. It turns out that rock burst hazard regions predicted by the microseismic energy attenuation agreed well with the objective hazardous situations. Seismic energy attenuation coefficient is a significant evaluation factor that directly mirrors the inelastic performance of rock medium. Energy attenuation coefficient threshold used for determining the rock burst hazard regions was 3.0 km−1. Reliability of the seismic energy attenuation inversion and tomography was closely related to the spatial distribution of microseisms in a localized region. The optimum spatial density of microseisms was 0.2 m−3. Regional rock burst prediction using microseismic energy attenuation is an effective approach for revealing potential hazardous regions in deep mining conditions. This approach improves the pertinence of geological hazard prevention and provides a beforehand reference for targeted hazard management.

Suggested Citation

  • Mingwei Zhang & Shengdong Liu & Hideki Shimada, 2018. "Regional hazard prediction of rock bursts using microseismic energy attenuation tomography in deep mining," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1359-1378, September.
    • Handle: RePEc:spr:nathaz:v:93:y:2018:i:3:d:10.1007_s11069-018-3355-3
    DOI: 10.1007/s11069-018-3355-3
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    References listed on IDEAS

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    1. Robert J. Geller, 2011. "Shake-up time for Japanese seismology," Nature, Nature, vol. 472(7344), pages 407-409, April.
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    Cited by:

    1. Xiqi Liu & Gang Wang & Leibo Song & Rong Hu & Xiaoming Ma & Xiaoping Ou & Shiji Zhong, 2023. "Study on the influence of fracture dip angle on mechanical and acoustic emission characteristics of deep granite," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 95-116, August.
    2. Weizhang Liang & Asli Sari & Guoyan Zhao & Stephen D. McKinnon & Hao Wu, 2020. "Short-term rockburst risk prediction using ensemble learning methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1923-1946, November.
    3. Qinghe Zhang & Weiguo Li & Liang Yuan & Tianle Zheng & Zhiwei Liang & Xiaorui Wang, 2024. "A review of tunnel rockburst prediction methods based on static and dynamic indicators," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(12), pages 10465-10512, September.

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