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Prediction of rockbursts in a typical island working face of a coal mine through microseismic monitoring technology
Highlights The precursor information to coal instability and increasing probability of rockburst is studied. Two rockburst accidents have been identified by the analysis of microseismic data. A new methodology for rockburst forecasting in underground coal mine. Characterize the damage degree of coal rock mass by microseismic energy.
Abstract Coal has dominated the energy structure in China for a long time. In recent years, dynamic disasters such as rockbursts have affected the safety of coal mine in production with the increase of coal mining depth. Microseismic monitoring is a non-intrusive monitoring technique that can be used to collect much key information: it has been widely applied in coal mine safety monitoring. In this paper, the failure mechanism and energy conversion in a coal-rock mass during mining were investigated, revealing the controlling effect of the surrounding rock mass on the coal seam. microseismic events during mining were monitored by using a self-built high-precision microseismic monitoring system, a variety of analytical methods have been used to quantify the monitoring results, and two rockburst accidents have been identified. The responses of different parameters before the rockburst were analyzed, and the response characteristics of different parameters to rockburst were summarized. The functional relationship between microseismic energy and rock damage was established by classical Benioff strain theory. Combined with the microseismic energy, strain, the degree of damage and the damage, the model of coal-rock mass was verified and modified through physical experiments. A new parameter for rockburst prediction (the energy rockburst warning (ERW) index) was defined and the numerical relationship between ERW and microseismic energy was deduced. The monitoring data were analyzed using this model and results showed that compared with other analysis, the new model can effectively assess the stability of coal-rock mass to a certain extent.
Prediction of rockbursts in a typical island working face of a coal mine through microseismic monitoring technology
Highlights The precursor information to coal instability and increasing probability of rockburst is studied. Two rockburst accidents have been identified by the analysis of microseismic data. A new methodology for rockburst forecasting in underground coal mine. Characterize the damage degree of coal rock mass by microseismic energy.
Abstract Coal has dominated the energy structure in China for a long time. In recent years, dynamic disasters such as rockbursts have affected the safety of coal mine in production with the increase of coal mining depth. Microseismic monitoring is a non-intrusive monitoring technique that can be used to collect much key information: it has been widely applied in coal mine safety monitoring. In this paper, the failure mechanism and energy conversion in a coal-rock mass during mining were investigated, revealing the controlling effect of the surrounding rock mass on the coal seam. microseismic events during mining were monitored by using a self-built high-precision microseismic monitoring system, a variety of analytical methods have been used to quantify the monitoring results, and two rockburst accidents have been identified. The responses of different parameters before the rockburst were analyzed, and the response characteristics of different parameters to rockburst were summarized. The functional relationship between microseismic energy and rock damage was established by classical Benioff strain theory. Combined with the microseismic energy, strain, the degree of damage and the damage, the model of coal-rock mass was verified and modified through physical experiments. A new parameter for rockburst prediction (the energy rockburst warning (ERW) index) was defined and the numerical relationship between ERW and microseismic energy was deduced. The monitoring data were analyzed using this model and results showed that compared with other analysis, the new model can effectively assess the stability of coal-rock mass to a certain extent.
Prediction of rockbursts in a typical island working face of a coal mine through microseismic monitoring technology
Zhang, Chao (author) / Jin, Gaohan (author) / Liu, Chao (author) / Li, Shugang (author) / Xue, Junhua (author) / Cheng, Renhui (author) / Wang, Xinglong (author) / Zeng, Xiangzhen (author)
2021-04-10
Article (Journal)
Electronic Resource
English
Spectral Analysis of Microseismic Signals for Prediction of Rockbursts
| British Library Conference Proceedings | 1998
Energy, mine stability and rockbursts
| Springer Verlag | 1999