Bayesian Dynamic Finite-Fault Inversion: 1. Method and Synthetic Test

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Authors

Frantisek Gallovic , Lubica Valentova, Jean-Paul Ampuero , Alice-Agnes Gabriel 

Abstract

Dynamic earthquake source inversions aim to determine the spatial distribution of initial stress and friction parameters leading to dynamic rupture models that reproduce observed ground motion data. Such inversions are challenging, particularly due to their high computational burden, thus so far only few attempts have been made. Using a highly efficient rupture simulation code, we introduce a novel method to generate a representative sample of acceptable dynamic models from which dynamic source parameters and their uncertainties can be assessed. The method assumes a linear slip-weakening friction law and spatially variable prestress, strength and characteristic slip weakening distance along the fault. The inverse problem is formulated in a Bayesian framework and the posterior probability density function is sampled using the Parallel Tempering Monte Carlo algorithm. The forward solver combines a 3D finite difference code for dynamic rupture simulation on a simplified geometry to compute slip rates, and pre-calculated Green’s functions to compute ground motions. We demonstrate the performance of the proposed method on a community benchmark test for source inversion. We find that the dynamic parameters are resolved well within the uncertainty, especially in areas of large slip. The overall relative uncertainty of the dynamic parameters is rather large, reaching ~50% of the averaged values. In contrast, the kinematic rupture parameters (rupture times, rise times, slip values), also well-resolved, have relatively lower uncertainties of ~10%. We conclude that incorporating physics-based constraints, such as an adequate friction law, may serve also as an effective constraint on the rupture kinematics in finite-fault inversions.

DOI

https://doi.org/10.31223/osf.io/tmjv4

Subjects

Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics

Keywords

Dates

Published: 2019-02-12 20:08

Last Updated: 2019-05-28 14:16

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License

GNU Lesser General Public License (LGPL) 2.1

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