Characteristics of rockburst and early warning of microseismic monitoring at qinling water tunnel

In-depth records of the geological and rockburst data during the construction of the Qinling Water Tunnel of the Han to the Wei River project, analysis of the initial stress field distribution rules of the rock mass within a buried depth of 700 m. According to the situation of the site, strength stress ratio criterion, Russense criterion and Hoek criterion, were analysed and modified, and the rockburst tendency criterion suitable for Qinling Water Tunnel was proposed. According to the rockburst data, the rockbursts in the TBM tunnelling section of Qinling Water Tunnel were classified and counted, and the characteristics and risk reasons of rockbursts were summarized. The microseismic monitoring technology was applied to carry out the monitoring and early warning of rockburst in Qinling Water Tunnel, so as to achieve the effect of real-time monitoring. By comparing the microseismic monitoring results with the statistical data of rockburst, it was found that the microseismic monitoring has high accuracy of rockburst prediction. Finally, combined with two typical cases of rockburst prediction, it can be found that microseismic monitoring can reflect the preparation process of rockburst and use artificial intelligence for rockburst early warning, which has great practical significance for the prevention of rockburst.

Automated summary

This study conducted in-depth records and analysis of the geological and rockburst data of the Qinling Water Tunnel. It proposed a rockburst tendency criterion, utilized microseismic monitoring technology for rockburst monitoring and early warning, and compared the results with statistical data to find a high accuracy in rockburst prediction.