Investigation of coal and gas outburst risk by microseismic monitoring

Anhu Wang; Dazhao Song; Xueqiu He; Linming Dou; Zhenlei Li; Ziyin Zu; Quan Lou; Yingjie Zhao

doi:10.1371/journal.pone.0216464

Investigation of coal and gas outburst risk by microseismic monitoring

PLoS One. 2019 May 23;14(5):e0216464. doi: 10.1371/journal.pone.0216464. eCollection 2019.

Authors

Anhu Wang^{1

2}, Dazhao Song^{1

2}, Xueqiu He^{1

2

3}, Linming Dou⁴, Zhenlei Li^{1

2}, Ziyin Zu⁵, Quan Lou⁶, Yingjie Zhao²

Affiliations

¹ Laboratory of Educational Ministry for High Efficient Mining and Safety in Mental Mine, University of Science and Technology Beijing, Beijing, China.
² School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, China.
³ Zhong-an Academy of Safety Engineering, Beijing, China.
⁴ Key Laboratory of Deep Coal Resource Mining, Ministry of Education of China, School of mines, China University of Mining and Technology, Xuzhou, Jiangsu, China.
⁵ Guizhou panjiang refined coal co., Ltd, Panzhou, China.
⁶ School of Resources and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China.

Abstract

In order to improve the monitoring and prediction of coal and gas outburst, this paper proposes a new method for dynamic regional prediction of coal and gas outburst using microseismic (MS) monitoring. The theoretical basis of this method is presented. An index evaluation system was established and applied, based on which field tests were carried out in a coal mine. The results show that seismic monitoring with frequency and energy indexes can obtain good results for mining disturbance intensity monitoring and geological structure detection; the regional stress distribution detected by seismic wave tomography is consistent with the theoretical stress field, making its use of great significance for optimizing coal and gas outburst drilling parameters and improving overall tunneling efficiency. This approach overcomes the limitations of traditional methods in the temporal and spatial dimensions and realizes dynamic and continuous monitoring of coal and gas outburst-prone areas.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Coal Mining*
Environmental Monitoring*
Humans
Models, Theoretical*
Natural Gas / analysis*

Substances

Natural Gas

Grants and funding

This work was financially supported by the State Key Research Development Program of China (Grant No.2016YFC0801408), the National Natural Science Foundation of China (Grant No.51634001, 51774023), and the Fundamental Research Funds for the Central Universities (Grant No. 06500033). Guizhou panjiang refined coal co.,Ltd provided support in the form of salaries for author ZZ, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.