Microseismic positioning method based on differential evolution algorithm

Authors

WANG Yunhong, Xian Research Institute Co. Ltd., China Coal Technology and Engineering Group Corp., Xian 710077, China
WANG Baoli, Xian Research Institute Co. Ltd., China Coal Technology and Engineering Group Corp., Xian 710077, China
DUAN Jianhua, Xian Research Institute Co. Ltd., China Coal Technology and Engineering Group Corp., Xian 710077, China

Abstract

Aiming at the problem that the location accuracy of conventional time-based microseismic location method depends on the accuracy of travel time, a differential evolution microseismic location method is proposed to improve the locating target function. Based on the traditional micro-seismic P-wave travel-time location method, the error weighting coefficient was added to the localization objective function, which reduced the impact of the first-time picking accuracy on the microseismic location by reducing the effect of the microseismic signal path with low initial pick-up accuracy on the locating error. The differential evolution algorithm, through population initialization, mutation, crossover, and selection operations, solves the improved micro-seismic location target function and achieves microseismic location. The model data and measured data are subjected to trial processing. The results show that the improved objective function can significantly reduce the error. The contribution of large components to the total error; the proposed differential evolution micro-seismic location method to improve the localization objective function can greatly reduce the influence of the pick-up error on the locating accuracy when the pick-up error of some microseismic signal paths is large or even wrong, get better location results.

Keywords

microseismic, differential evolution, location, travel time, pick-up accuracy

DOI

10.3969/j.issn.1001-1986.2019.01.026

Recommended Citation

WANG Yunhong, WANG Baoli, DUAN Jianhua, et al. (2019) "Microseismic positioning method based on differential evolution algorithm," Coal Geology & Exploration: Vol. 47: Iss. 1, Article 27.
DOI: 10.3969/j.issn.1001-1986.2019.01.026
Available at: https://cge.researchcommons.org/journal/vol47/iss1/27

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