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Sectional velocity model for microseismic source location in tunnels
Highlights A suitable sectional velocity model for microseismic source location in tunnels is proposed. An efficient global optimization algorithm (particle swarm optimization) is used. The impact of velocity error on microseismic source location in tunnels is discussed. The sectional velocities obtained are close to the actual ones and location accuracy is improved. The sectional velocities obtained are in accordance with the geological conditions.
Abstract Microseismic (MS) source location is the foundation of MS monitoring and warning. The accuracy of MS source location depends on the accuracy of the velocities used in the location algorithm. In this work, a suitable sectional velocity model for MS source location in tunnels is proposed. In the model, the velocities from the MS source to the MS sensors in any one group are almost the same but those to different groups of MS sensors may be different. An efficient global optimization algorithm (particle swarm optimization) is applied to search for the MS source location and sectional velocity. Results from a tunnel simulation show that the velocities obtained using the sectional velocity model are close to the actual ones and location accuracy is greatly improved. The average location error is reduced by 78.3% (from 13.05 to 2.83m). The proposed model was applied to MS source location in the deeply-buried tunnels of the Jinping II hydropower station in China. The case shows that the sectional velocities obtained are in accordance with the geological conditions. The locations of rockburst and MS events in the rockburst development process are clustered in the actual rockburst area. The method is good for rockburst monitoring and warning in the tunnels. In addition, the impact of error in the velocity on MS source location accuracy in tunnels is discussed. In tunnels, error in velocity is found to have a great impact on MS source location accuracy.
Sectional velocity model for microseismic source location in tunnels
Highlights A suitable sectional velocity model for microseismic source location in tunnels is proposed. An efficient global optimization algorithm (particle swarm optimization) is used. The impact of velocity error on microseismic source location in tunnels is discussed. The sectional velocities obtained are close to the actual ones and location accuracy is improved. The sectional velocities obtained are in accordance with the geological conditions.
Abstract Microseismic (MS) source location is the foundation of MS monitoring and warning. The accuracy of MS source location depends on the accuracy of the velocities used in the location algorithm. In this work, a suitable sectional velocity model for MS source location in tunnels is proposed. In the model, the velocities from the MS source to the MS sensors in any one group are almost the same but those to different groups of MS sensors may be different. An efficient global optimization algorithm (particle swarm optimization) is applied to search for the MS source location and sectional velocity. Results from a tunnel simulation show that the velocities obtained using the sectional velocity model are close to the actual ones and location accuracy is greatly improved. The average location error is reduced by 78.3% (from 13.05 to 2.83m). The proposed model was applied to MS source location in the deeply-buried tunnels of the Jinping II hydropower station in China. The case shows that the sectional velocities obtained are in accordance with the geological conditions. The locations of rockburst and MS events in the rockburst development process are clustered in the actual rockburst area. The method is good for rockburst monitoring and warning in the tunnels. In addition, the impact of error in the velocity on MS source location accuracy in tunnels is discussed. In tunnels, error in velocity is found to have a great impact on MS source location accuracy.
Sectional velocity model for microseismic source location in tunnels
Feng, Guang-Liang (author) / Feng, Xia-Ting (author) / Chen, Bing-Rui (author) / Xiao, Ya-Xun (author) / Jiang, Quan (author)
Tunnelling and Underground Space Technology ; 45 ; 73-83
2014-09-19
11 pages
Article (Journal)
Electronic Resource
English
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