Seismic super-resolution method: Enhancing reservoir delineation and characterization through high-resolution seismic data

Abstract Seismic resolution plays a crucial role in the successful development of both conventional and unconventional assets. The accuracy of structural and stratigraphic interpretations, as well as reservoir characterization, hinges on the resolution and quality of seismic data. In this study, we introduce an inversion-based method for enhancing seismic resolution, drawing inspiration from super-resolution techniques in computer vision. This method, termed seismic super-resolution (SSR), utilizes seismic data coupled with regularizations to drive the inversion, thereby avoiding bias from well data. Our approach has been adopted globally, ranging from conventional assets in Alaska and China to unconventional assets in the Eagle Ford Shale and Permian Basin, significantly impacting field development. This includes improved well planning, reduced drilling uncertainties, and enhanced reservoir delineation. This paper highlights the efficacy and practical applications of the SSR method across various geologic settings.