An Evolutive Linear Kinematic Source Inversion

Abstract : We present a new hierarchical time kinematic source inversion method able to assimilate data traces through evolutive time windows. A linear time domain formulation relates the slip rate function and seismograms, preserving the positivity of this function and the causality when spanning the model space: taking benefit of the time‐space sparsity of the rupture model evolution is as essential as considering the causality between rupture and each record delayed by the known propagator operator different for each station. This progressive approach, both on the data space and on the model space, does require mild assumptions on prior slip rate functions or preconditioning strategies on the slip rate local gradient estimations. These assumptions are based on simple physical expected rupture models we foresee. Successful applications of this method to a well‐known benchmark (Source Inversion Validation Exercise 1) and to the recorded data of the 2016 Kumamoto mainshock (Mw=7.0) illustrate the advantages of this alternative approach of a linear kinematic source inversion. This stabilized overparameterized optimization of a linear forward problem has a potential extension to stochastic inversion in a Bayesian framework in the future to assess uncertainties on kinematic source inversions, which is more difficult to investigate under nonlinear formulations.