Full waveform inversion with dynamic image warping

Full waveform inversion (FWI) can generate high-resolution subsurface models, but often suffers from an objective function with local minima caused mainly by an absence of low frequencies in seismograms. These local minima cause cycle skipping when the initial model for FWI is far from the true model. To avoid cycle skipping, traveltime inversion is often used to compute initial models for FWI. We propose to incorporate the merits of traveltime inversion in FWI. We use dynamic image warping (DIW) to measure the traveltime misfit between recorded data and synthetic data. When compared with correlation-based techniques often used in traveltime inversion, DIW reduces errors in estimates of time shifts caused by cycle skipping. FWI with DIW then uses these time shifts to mitigate the problem of local minima in the objective function. FWI with DIW is then a hybrid method for inversion that combines the benefits of both conventional FWI and traveltime inversion.