Theoretical and Experimental Study on Parameter Optimization of Active Sources in Seismic Tomography

Abstract

Given the high cost of active seismic tomography and the large influence on mining production, as well as the uncontrollable inversion period and accuracy of the target area during the passive seismic tomography, an optimization algorithm based on adding a certain number of artificial microseism (active sources) was proposed through the distribution characteristic of microseismic events (passive sources). The active source parameter optimization method realizes the combination of active source and passive source and improves the accuracy of inversion at the same time. The method uses a multiobjective optimization genetic algorithm to fuse the accuracy index and stability index that preevaluates the inversion effect and solves the best combination of active sources to improve the inversion effect. At the same time, experimental studies were carried out. After the active source was added, the inversion accuracy of high-stress areas and the ability to resist data errors were greatly improved. The inversion results were more in line with the law of stress transfer and stress distribution, which enhanced the connectivity of the low-velocity area of the fault zone or weakened zone.