Optimal stacking for multi-azimuth pre-stack seismic data

Abstract

Offshore exploration for hydrocarbons in increasingly challenging environments often requires more advanced acquisition methods than conventional 3D narrow azimuth towed streamer to better image the sub-surface for AVO analysis and reservoir characterization. Multi-Azimuth (MAZ), Wide-Azimuth (WAZ) or Full-Azimuth (FAZ) seismic acquisition overcomes the limitations of the conventional acquisition in better illuminating the sub-surface, suppressing the multiple and enhancing signal to noise (S/N) ratio. Nevertheless, to realize the added value of multi-azimuth data, the data need to be combined in a way that will overcome the issues such as time-shift and amplitude difference due to varied illumination between the surveys. This paper describes a method that can be used for combining MAZ pre-stack data to generate AVO preserving common image gathers (CIGs) in the presence of poor illumination. Based on the concept of crosscorrelation, MAZ CIGs are first flattened to account for any inaccuracy in the velocity model and imaging process so as to align the events to a pilot. Repeating the crosscorrelation process, weights are then derived from the correlation coefficients and applied to individual offsets that take into account the AVO behaviour. With this post-migration processing, any anomaly in AVO resulted from poor illumination can be mitigated. Applying it on MAZ post-stack data, the method can also provide optimal stacking for obtaining higher S/N images. We demonstrate, through synthetic and real data examples, that clearer images with high AVO fidelity can be obtained from MAZ data using our optimal stacking method.