关键词: 矩张量反演, 传感器校准, 微震, 震源机制, 噪声

Abstract: Moment tensor inversion is an effective method to study the mechanism of deep rock mass failure, and station/sensor calibration is very important for obtaining accurate moment tensors. In order to obtain more accurate sensor calibration coefficients and moment tensors, a new sensor calibration method is developed: the search calibration method. The proposed method and the network calibration method are respectively applied to the microseismic monitoring data of the Geysers geothermal field in northern California. Then, based on the calibration results, a series of theoretical calculations and simulations are conducted to verify the effectiveness of the two different calibration methods. By comprehensively considering the influence of factors such as different focal mechanism parameters, preset calibration coefficients, noise addition methods and noise levels, the theoretical calculation and simulation analysis of the effectiveness comparison of calibration methods are carried out. The results show that both calibration methods can obtain stable coefficients from microseismic monitoring data, the components and stress state distribution of events are more concentrated after calibration; under all simulated conditions, the two calibration methods can effectively reduce the moment tensor errors; under low noise level condition, the moment tensor errors of two calibration methods are very small and similar; under mixed noise level and high noise level conditions, the accuracy and stability of the search calibration results are better than that of network calibration in most cases; based on the simulation results, the more reliable moment tensors of the Geysers microseismic data are selected. The research ideas and conclusions can provide further guidance for the study of microseismic moment tensor.

Key words: moment tensor inversion, sensor calibration, microseismic, focal mechanism, noise