EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Bayesian Finite-fault inversion for determination of rupture geometry and slip function

Hamed Davari1, Anooshiravan Ansari1, Sanaz Vajedian2, and Navid Kheirdast1
Hamed Davari et al.
  • 1International Institute of Earthquake Engineering and Seismology, Seismology, Tehran, Iran, Islamic Republic of (
  • 2Institute of Photogrammetry and GeoInformation, Leibniz University Hannover

In the finite-fault modelling we aim to invert the observed data to image the earthquake rupture inside the solid crust medium. The common finite fault inversion methods usually take a planar geometry for the ruptured area, however, evidences show more complicated geometries (e.g. 2016 Mw7.8 Kaikura) can causes the seismic event. Having the advanced remote sensing technologies (e.g. InSAR), with a high data resolution in the near fault area, we can increase the accuracy for determination of rupture geometry. In this study, we consider a large three dimensional ensemble of point sources in the solid crust medium, each point source can trigger six moment tensor components that makes the model space of the problem. We then find the most probable geometry of the ruptured area by inverting the interferometric observation for moment tensor components. Using the Bayesian inversion with MCMC (Markov Chain Monte Carlo) simulation the fault geometry and static slip deformation is determined from moment tensor to have a ruptured zone that maximizes the posteriori likelihood. The proposed method would be applied to 2019 M5.9 Torkamanchay earthquake in Iran and the preliminary results is presented.

How to cite: Davari, H., Ansari, A., Vajedian, S., and Kheirdast, N.: Bayesian Finite-fault inversion for determination of rupture geometry and slip function , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1073,, 2019

This abstract will not be presented.