Revealing shallow and deep complex geological features with FWI: Lessons learned

Conventional Full Waveform Inversion (FWI), mostly based on diving-waves, has become a standard velocity model building tool. Using a dataset from the deep water on the Mexican side of the Gulf of Mexico (GoM), we show that FWI can be effective at resolving different types of complex geological features in the shallow overburden. Unfortunately, it is well known that below diving-wave penetration depth, FWI has to rely solely on reflections. In this case, the velocity update is dominated by high-wavenumber components, and the inversion dependence on the accuracy of the density model increases. However, we show that reflections can still help solve for low wavenumbers of the velocity model when different components of the FWI gradient are properly used for Reflection-wave-based Full Waveform Inversion (RFWI). This allowed reflection data to improve the velocity model at a geologically challenging location within our GoM project area, where traditional ray-based tomography failed and where depths exceed diving wave penetration. We discuss the lessons learned on RFWI from this example.