Image Enhancements for Subsalt Targets; Thunder Horse Case Study

Summary We present the results of two model-based image enhancement approaches applied to the most recent surface and borehole seismic images of the Thunder Horse field, Gulf of Mexico. Seventy five percent of the field is under a salt canopy, and one area of the reservoir, Thunder Horse North, exhibits a steeply dipping structure closing against the salt stalk. Full-azimuth, long-offset data, such as a recently acquired ocean-bottom node survey, greatly improved the ability to illuminate each zone of the reservoir. However, a critical factor to the final image interpretability continues to be the use of image conditioning and enhancement techniques, integrated within the imaging workflow, that allow for the discrimination of signal and noise to attenuate all undesired events. We review the shot-patched angle-gather illumination weighting workflow and the dip-guided selective stacking techniques used (separately or in conjunction) to optimize the quality and greatly improve the interpretability of the latest pre- and poststack images of the Thunder Horse field.