An application of time-domain multiscale waveform tomography to marine data

We propose a multiscale method for time-domain waveform tomography. The data are low-pass filtered using a Wiener filter, and the inversion is carried out using a multiscale method with a dynamic early-arrival muting window. The adjoint method is used in the inversion for an efficient computation of the gradient directions. A staggered-grid, explicit finite-difference method with 4th-order accuracy in space and 2nd-order accuracy in time is utilized for forward modeling and the adjoint calculation. Our method is applied to a marine seismic dataset. The initial velocity model for waveform tomography is obtained by using traveltime tomography with dynamic smoothing filters. The velocity tomogram obtained from waveform tomography has a higher resolution and a better accuracy than the initial model. The tomogram accuracy is verified by comparing common image gathers.