Improving images below shallow gas clouds with adaptive data-selection FWI and Q- tomography: A case study at East Breaks, GOM

Summary The presence of shallow gas anomalies continues to be a challenge in seismic imaging in the Gulf of Mexico (GOM). Due to the strong absorption property and irregular shape of a gas cloud, the seismic image below it could suffer from frequency, amplitude, and phase distortion. Q tomography and pre-stack depth Q migration (Q-PSDM) are efficient tools for compensating these distortion effects caused by absorptive heterogeneities. However, deriving Q models is a challenging task, especially when the shape of gas anomalies are complex and the velocity inside or close to the gas cloud area is not correct. Standard ray-based tomography fails to capture the detailed rapid velocity variation for the areas with or beneath a high lateral or vertical contrast (e.g., gas pocket, shale, salt, and carbonate). Full waveform inversion (FWI) provides highresolution velocity details but is still an expensive process with its success highly dependent on the quality of the initial model. We present a case study at East Breaks, GOM, that combines adaptive data-selection FWI and Q tomography to invert the velocity and absorption model around a gas cloud area to improve the seismic image.