Assessing the effectiveness of the shear-tensile-compressive model in earthquake source inversions: synthetic experiments and field application

Author:

Ren Yi1ORCID,Vavryčuk Václav23ORCID,Zhao Li1ORCID

Affiliation:

1. School of Earth and Space Sciences, Peking University , Beijing 100871 , China

2. Institute of Geophysics, The Czech Academy of Sciences , Boční II 1401, 14100, Praha 4 , Czech Republic

3. Institute of Geology, The Czech Academy of Sciences , Rozvojová 269, 16500, Praha 6 , Czech Republic

Abstract

SUMMARY As an alternative to the moment tensor (MT) model for earthquake sources, the shear-tensile-compressive (STC) model offers a kinematic description of the source mechanism and leads to a more robust inversion problem. However, the premise of the source inversion based on STC is to ensure the accuracy of parameter $\kappa $ defined as the ratio of the Lamé constants, $\kappa $=$\lambda /\mu $, in a fault zone. In this study, we carry out a series of synthetic experiments using P-wave amplitudes in source mechanism inversions based on both the STC and MT models, and consider the influence of noise, the uncertainties in source locations and in the velocity model. We show that the nonlinear STC inversion with an appropriate value of $\kappa $ leads to more accurate result compared to the linear MT inversion. We also propose a new joint-STC inversion method to jointly invert for parameter $\kappa $ and the remaining parameters of the STC model (magnitude and the strike, dip, rake and slope angles). The results indicate that our proposed method yields robust results for both the parameter $\kappa $ and focal mechanisms. We apply our joint-STC inversion method to field microearthquake data observed in the West Bohemia region to validate some of the conclusions drawn from the synthetic experiments.

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Czech Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

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