Abstract

Full-waveform inversion (FWI) has been widely used on 3D data sets to build detailed velocity models over the past 10 years. Most of these projects used pressure data and an acoustic approximation, with the assumption that the field data were dominated with P-waves. This approach of FWI can determine parameters related to the acoustic wave equation. It focuses on updating velocities by minimizing the misfit between observed and model data. Acoustic FWI, using the pressure component of collected data, has shown tremendous potential in simple geologic settings. Successful FWI projects, using wide-azimuth streamer, ocean bottom, and land survey geometries, have convinced the oil industry to pursue the next step by involving more physical properties. However, questions remain on how far we can properly describe field data with the acoustic approximation and at what point we need to switch to a much more expensive elastic wave equation implementation. In a complicated geologic region such as the Gulf of Mexico (GoM), the seismic wavefield can be complex and elastic FWI is needed to achieve a better velocity model, even when using mostly pressure data alone. We demonstrate the application of elastic FWI on sparse-node ocean-bottom-node data from the GoM and show comparisons to the acoustic solution. The comparisons demonstrate the benefits of the elastic FWI implementation when applied to image steeply dipping Miocene sands beneath a complex salt canopy, despite the increased computational expense. Furthermore, we demonstrate that when elastic FWI is applied to sufficiently high frequencies, the FWI-derived reflectivity product and velocity model are reliable interpretation products.

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