Identification of sweet spots in shale reservoir formations

Abstract

The main goal for shale resource characterization is usually the identification of sweet spots which represent the most favourable drilling targets. Such sweet spots can be picked up as those pockets in the target formation that exhibit high total organic carbon (TOC) content as well as high brittleness. At any well location, when the resistivity and sonic transit-time curves are scaled and overlaid, they follow each other almost everywhere, except in the kerogen-rich zones, where they cross over. While such a cross over is only seen visually, it can be transformed into an attribute known as ΔlogR that incorporates both the resistivity and velocity information and is expected to be high for organic-rich zones. Such a transformation would allow us to identify organic-rich zones only at well locations. In this study, we introduce a methodology for computing ΔlogR as a volume from seismic data. For doing this, the ΔlogR curve computed at well locations is correlated with different attribute curves that can be derived from seismic data. An attribute curve which shows the maximum correlation is selected and crossplotted against ΔlogR to determine the relationship between the two. This relationship is then used for extracting the ΔlogR volume from 3D seismic data.