Dynamic Matching FWI
A step-change in velocity modelling and subsurface imaging resultsLearn More
Full waveform inversion (FWI) develops a subsurface model that best explains the observed seismic data through iteratively minimizing the misfit between modelled and observed data.
This is inherently a nonlinear optimization problem and thus often suffers from local-minima and cycle-skipping issues. To attack these issues, TGS FWI uses a dynamic warping technique to resolve long wavelength components; then image-guided FWI starts from low frequency, small offset data, and gradually extends to higher frequency and longer offset data for shallow model inversion. Diving-wave FWI can also be used to update anisotropy parameters. The process then turns to reflection mode; get large wavenumber background update through the wavepath kernel, and then changes to phase-only reflection FWI for high-resolution model update. TGS FWI provides a spatial correlation map, phase residual map and other tools to QC the convergence and possible cycle skipping. TGS FWI can handle all types of acquisitions (NAZ/WAZ streamer, OBC/OBN, land etc.) and provide a high-resolution model for imaging uplift.
Jian Mao , James Sheng , Matt Hart , and Taejong Kim (2016) ”High-resolution model building with multistage full-waveform inversion for narrow-azimuth acquisition data.” The Leading Edge, 35(12), 1031–1036.
A. Salem, M. Hart, S. Baldock, C. Lang, J. Chen, J. Sheng; 2018, “Image Guided Full Waveform Inversion (IGFWI) Modelling of Shallow Channel Features in the Moray Firth”, EAGE