A Robust Gradient for Long Wavelength FWI Updates

Abstract

We introduce a robust method to produce long wavelength updates in gradient-based Full Waveform Inversion (FWI). The solution introduces dynamic weights in the velocity sensitivity kernel derived from impedance and velocity parameterization of the classical objective function. The new kernel implementation effectively eliminates the migration isochrones produced by the specular reflections, enhances the low wavenumber components in the gradient in heterogeneous media, and is able to deliver velocity updates beyond the penetration depth of diving waves. We use synthetic examples to illustrate how this dynamic weighted FWI gradient successfully recovers the velocity from pre-critical reflections. We also show with dual-sensor streamer data from deep-water Gulf of Mexico how the dynamic weighted FWI gradient can combine both transmitted and reflected energy in a global FWI scheme.