From Routine to Integrated Core Analysis: Setting Up the Database for Reservoir Quality Modelling

Routine core analysis (RCA) for Reservoir Quality (RQ) prediction comprises a collection of measurements acquired with different analytical techniques, which does not include operator-bias evaluation, or integration of continuous sedimentological core description with spot measurements on plugs and thin sections. RCA data rarely have verified uncertainty specifications, thus hampering statistically-rigorous extrapolation of spot measurements such as petrographic description, to the entire reservoir volume. Petrographic analysis gives insight into the controls on RQ through unravelling the diagenetic fingerprint that shapes the eventual porosity and permeability in the reservoir. Because thin-section analysis is time consuming and costly, protocols for selection of representative thin sections should aim at maximizing information obtained from small data sets, so as to minimize costs and prevent unnecessary destruction of core material. This paper presents a flexible protocol for representative thin-section selection based on evaluation of RCA data (i.e., poro-perm and grain-density plug measurements), illustrated on a core of a Carboniferous fluvial sandstone reservoir. The results of the petrographic analysis are interpreted in terms of their relation with sedimentological and geochemical signatures, and it is demonstrated that application of the protocol highly increased the RCA data value which to date merely served as petrophysical indicators.