Enhanced delineation of reservoir compartmentalization from advanced Pre and Post-stack seismic attribute analysis

Abstract

Reservoir compartmentalization has a huge bearing on fluid flow within hydrocarbon reservoirs, and can impact overall recovery during field development. Small and subseismic faults can have a dramatic effect on the compartmentalization within a reservoir, but until recently they have not typically been incorporated into fault interpretations. This can be due to data fidelity and the amount of time needed to manually pick them. Their omission from the interpretation – and ultimately reservoir models – means the understanding of reservoir compartmentalization is incomplete, hence solving this problem is critical to improve production. Approaches that automatically identify and extract faults from seismic volumes are available. These automated methods aim to emphasize discontinuities within seismic volumes and are usually focused on poststack data. However, they need preconditioned inputs that are often based around a coherence algorithm. This preconditioning aims to suppress noise but can inflict data degradation, which may diminish smaller features in the seismic volumes. This article proposes an enhanced approach using a new combination of preconditioning steps designed to avoid these degradation problems. It also proposes the use of prestack seismic data, which has not traditionally been used for this purpose. Analysis of various pre-stack elements is displayed to show it can delineate more features than poststack data alone in certain noisy areas, such as gas effects or low frequencies. Finally, it demonstrates that the best approach combines results from pre- and poststack analysis to produce a more complete picture of reservoir compartmentalization.