Enhanced accuracy in flow-unit-definition in a carbonate reservoir by integrating conventional core analysis with the interpretation of borehole images, NMR and conventional logs within a stratigraphic framework: A case study from the Permian Basin

摘要

Primary depositional facies control sediment types and sediment body geometries in carbonate systems, which in turn control primary pore type(s) and reservoir geometries. Therefore, the reservoir modeling of carbonates requires a better understanding of the original rock fabric types in addition to the knowledge of depositional facies. Accurate identification of primary rock fabric can be used to predict pore network characteristics – porosity, permeability and pore connectivity- that define a flow unit. Additionally, rock types themselves are often predicatively distributed within a correlatable stratigraphic unit, thereby enabling a spatial prediction of fluid flow properties. Accurate evaluation of a carbonate reservoir in terms of fluid flow units requires integration of critical geologic attributes determined from careful core description, including original rock type determination, depositional facies interpretation, and reservoir facies determination, with wireline log signatures. Electrical borehole images, when properly calibrated to core, can be used to identify primary facies and reservoir types in uncored wells. This paper presents the results of integrating the sedimentological descriptions of conventional cores and petrophysical analysis with the interpretation of borehole images, NMR and conventional logs. Wireline logs and conventional core were acquired from a well producing from in a Wolfcamp carbonate reservoir in the Permian Basin for the present study. Dunham-based rock type assemblages were classified into primary depositional facies and grouped into high frequency cycle stacking patterns. Both whole core and plugs were analyzed for porosity and permeability, which were then correlated with the log derived porosity and permeability. Electrical borehole image was used not only for the electro facies correlation with the depositional facies but also for the purpose of estimating porosity and permeability by using a recently developed new technique (Chitale et. al., 2007) to evaluate the pore space characteristics in carbonates. The newly developed software technique first equates the total image conductivity signal with total porosity that is then resolved into fractions co relatable with micro-, primary- and secondary porosity. The new technique of image interpretation uses published models to equate carbonate rock types and their porosity types with permeability. It was found that the image-log derived electro facies and bedding in the carbonate as well as the internal fabric of the carbonates (sedimentary structures and