Elastic reflection waveform inversion with variable density

Abstract

Elastic full waveform inversion (FWI) provides a better description of the subsurface than those given by the acoustic assumption. However it suffers from a more serious cycle skipping problem compared with the latter. Reflection waveform inversion (RWI) provides a method to build a good background model, which can serve as an initial model for elastic FWI. Therefore, we introduce the concept of RWI for elastic media, and propose elastic RWI with variable density. We apply Born modeling to generate the synthetic reflection data by using optimized perturbations of P- and S-wave velocities and density. The inversion for the perturbations in P- and S-wave velocities and density is similar to elastic least-squares reverse time migration (LSRTM). An incorrect initial model will lead to some misfits at the far offsets of reflections; thus, can be utilized to update the background velocity. We optimize the perturbation and background models in a nested approach. Numerical tests on the Marmousi model demonstrate that our method is able to build reasonably good background models for elastic FWI with absence of low frequencies, and it can deal with the variable density, which is needed in real cases.