Direct waveform inversion (DWI) by explicit time-space causalityMS67

The full waveform inversion (FWI) is widely used to obtain images using recorded waveforms and it can be cast into a global nonlinear optimization problem. There are many known challenges in FWI. Using time-space causality of the wavefield, we propose to convert the global nonlinear optimization into many local linear inversions that can be directly solved (DWI). The conversion has no information loss. DWI naturally uses all data types and is unconditionally convergent and efficient.

This presentation is part of Minisymposium “MS67 - Advances and new directions in seismic imaging and inversion (3 parts)
organized by: Mauricio Sacchi (University of Alberta) , Sergey Fomel (University of Texas, Austin) , Laurent Demanet (MIT ) .

Yingcai Zheng (University of Houston)
computed tomography, image reconstruction, inverse problems, inverse scattering, nonlinear optimization, waveform inversion