煤矿矿震定位中异向波速模型的构建与求解

摘要

针对煤矿上覆岩层层状赋存和离层带的特点,构建矿井尺度的微震监测系统异向波速模型,模型中波速向量由地面探头速度与井下探头速度组成.研究了在只有强矿震信号和混有爆破信号两种条件下,以到时残差最小为目标和震源定位误差最小为目标的两种求解模型,模型求解选用具有全局寻优特性的遗传算法与CMEAS算法结合的混合算法.现场实际应用得出,只使用爆破信号的到时残差法最优,混有强矿震信号的到时残差法其次；与爆破信号定位所用的统一简化波速模型相比,震源定位误差大幅度降低.在此基础上进一步减低定位误差,还需从微震台网的优化布设方面解决.%According to the characteristics of layered bedding strata and bed separation zone in coal mine, an anisotropic velocity model is built by two kinds of velocity, that is, one for underground sensor and the other for surface sensor, to form the velocity vector. In order to solve the vector, two objective functions of minimum arrival time residuals and minimum source location errors are created under two conditions with strong tremor signals only and also mixed with blasting signals. These objective functions are solved by the mixed algorithm combining genetic algorithm with CMEAS algorithm, which has good global search capability. The site application results show that the arrival time residual method using blasting signal only is thernbest, the next is the arrival time residual method using mixed blasting signal and strong tremor signal. Compared to the isotropic velocity model; the average source location error of verification blasting signals is reduced greatly. In order to further decrease the source location error, the microseismic network should also be optimized.