Conditioning the full waveform inversion gradient to welcome anisotropy CWP Research

Multi-parameter full waveform inversion (FWI) su ers from the complex nonlinearity in the objective function, compounded by the eventual tradeo between the model parameters. A hierarchical approach based on frequency and arrival time data decimation to maneuver the complex nonlinearity associated with this problem usually falls short in anisotropic media. In place of data decimation, I use a model gradient lter approach to access the parts of the gradient more suitable to combat the potential nonlinearity and parameter trade o . The lter is based on representing the gradient in the time-lag normalized domain, in which small scattering angles of the gradient update are initially muted out. A model update hierarchical ltering strategy includes applying varying degree of ltering to the di erent anisotropic parameter updates. A feature not easily accessible to simple data decimation. Using both FWI followed by re ection based FWI (RFWI) is handled best by a combination of anisotropic parameters that starts with the horizontal velocity.