基于斯奈尔定律及布谷鸟算法的层状岩体微震定位研究

Research on microseismic event locating in layered rock masses based on Snell's law and Cuckoo search algorithm

微震事件的精确定位对岩爆监测预警至关重要,虽然传统分段波速模型的定位误差比单一波速模型有大幅降低,但是定位误差依然很大(本算例为28.51 m)。因此,提出一种基于斯奈尔定律及布谷鸟算法的微震定位方法来提高层状岩体中的定位精度。研究结果表明,布谷鸟算法采用莱维飞行的搜索策略可以实现长步长与短步长相结合进行空间最优解的搜索,在震源反演过程中通过模拟布谷鸟的专性繁殖寄生行为表现出很好的鲁棒性,能实现微震事件的可靠定位。同时结合斯奈尔定律可以有效克服两点间弹性波传播路径被简化成直线所引起的误差,定位误差比传统分段波速模型有显著降低(本算例可降低至0.12 m)。

Precise localization of microseismic events plays an important role in rockburst monitoring and early warning,and although the positioning error of the sectional wave velocity model is substantially lower than that of the single wave velocity model,the positioning error is still large(28.51 m of an example in this paper).Therefore,this paper proposes a new microseismic localization method based on Snell's law and Cuckoo search algorithm to improve the localization accuracy in layered rock masses.The results show that the Cuckoo search algorithm can combine long and short step lengths to search for spatially optimal solutions using the Levy flight search strategy,presents good robustness in the process of seismic source inversion by simulating the specialized breeding parasitic behavior of Cuckoos,and can achieve reliable localization of microseismic events.It is also indicated that the combination of the Cuckoo search algorithm and the Snell¢s law can effectively overcome the error caused by simplifying the elastic wave propagation path between two points to a straight line,and can significantly reduce the positioning error compared to the sectional wave velocity model(down to 0.12 m in this paper).