Significance of accurate selection of the seismogenic faults from the earthquake focal mechanisms for stress field reconstruction
Stress field inversion based on focal mechanisms requires accurate identification of seismogenic faults from the two nodal planes given by the focal mechanism,and then obtaining the stress field by fitting the slip direction of the seismogenic faults.However,current techniques and methods cannot guarantee that seismogenic faults can be accurately identified from all focal mechanisms.Therefore,a small fraction of the auxiliary fault planes are included in the fault data used for stress field inversion,and to what extent does the presence of this fraction of pseudo faults cause the reconstructed stress field to deviate from the actual stress field?In this paper,we have shown through synthetic experiments that the incorrect selection of faults for part of the focal mechanisms may cause the reconstructed stress direction and the relative magnitude of the principal stresses(R)to deviate significantly from the actual situation.The amount of deviation in the reconstructed stress field is mainly related to three factors,which are the actual stress R value,the fraction of focal mechanisms that incorrectly selected faults,and the noise level contained in the focal mechanisms.When the actual stress R value is around the median,the only way to accurately reconstruct the R value is to accurately select the fault planes.When the actual stress R value is relatively small,accurate selection of the fault plane helps to accurately reconstruct the stress orientation.Therefore,accurate selection of faults from the focal mechanisms can ensure that the orientation and R value of the stress field can be accurately reconstructed under different background stress fields,which is important for reasonable interpretation of tectonic movement based on the reconstructed stress field.
Earthquake focal mechanismReconstructing stress fieldIdentifying seismogenic fault planeRelative magnitude of the principal stresses
万方数据
维普
