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

摘要

Primary depositional facies control sediment types andsediment body geometries in carbonate systems, whichin turn control primary pore type(s) and reservoirgeometries. Therefore, the reservoir modeling ofcarbonates requires a better understanding of theoriginal rock fabric types in addition to the knowledgeof depositional facies. Accurate identification ofprimary rock fabric can be used to predict pore networkcharacteristics – porosity, permeability and poreconnectivity- that define a flow unit. Additionally, rocktypes themselves are often predicatively distributedwithin a correlatable stratigraphic unit, thereby enablinga spatial prediction of fluid flow properties.Accurate evaluation of a carbonate reservoir in terms offluid flow units requires integration of critical geologicattributes determined from careful core description,including original rock type determination, depositionalfacies interpretation, and reservoir facies determination,with wireline log signatures. Electrical boreholeimages, when properly calibrated to core, can be usedto identify primary facies and reservoir types in uncoredwells. This paper presents the results ofintegrating the sedimentological descriptions ofconventional cores and petrophysical analysis with theinterpretation of borehole images, NMR andconventional logs.Wireline logs and conventional core were acquiredfrom a well producing from in a Wolfcamp carbonatereservoir in the Permian Basin for the present study.Dunham-based rock type assemblages were classifiedinto primary depositional facies and grouped into highfrequency cycle stacking patterns. Both whole core andplugs were analyzed for porosity and permeability,which were then correlated with the log derivedporosity and permeability. Electrical borehole imagewas used not only for the electro facies correlation withthe depositional facies but also for the purpose ofestimating porosity and permeability by using arecently developed new technique (Chitale et. al., 2007)to evaluate the pore space characteristics in carbonates.The newly developed software technique first equatesthe total image conductivity signal with total porositythat is then resolved into fractions co relatable withmicro-, primary- and secondary porosity. The newtechnique of image interpretation uses publishedmodels to equate carbonate rock types and theirporosity types with permeability.It was found that the image-log derived electro faciesand bedding in the carbonate as well as the internalfabric of the carbonates (sedimentary structures and