FACIES ANALYSIS, ROCK TYPE, AND PROPERTY DISTRIBUTION IN UPPER INTERVAL OF BATURAJA FORMATION, KRISNA FIELD, SUNDA BASIN

摘要

Krisna Field is located in the western part of thernoffshore Southeast Sumatra (SES) Block, in thernSunda Basin. The field, which is managed by thernCentral Business Unit, SES Block, produces oilrnfrom carbonate reservoirs within the BaturajarnFormation, with the main production coming fromrnthe upper interval (UBR).rnProduction plots and water injection data show thatrnthere are problems associated with reservoirrnheterogenity and conectivity. It therefore becamernessential to undertake the task of reservoirrncharactertization in order to address these problemsrnand gain an understanding and establish a rationalernfor forward direction to achieve maximum recoveryrnefficiency. It is the objective of this study to identifyrnlithofacies and facies associations and characterizernthe distributions of rock type, porosity andrnpermeability.rnThin section petrographic analysis of core samplesrnfrom Krisna D-04 and Krisna E-02 wells show thatrnthere are five lithofacies: foraminifera shale,rnplanktonic foraminifera packstone, skeletalrnwackestone, skeletal packstone, and benthicrnforaminifera packstone. The carbonate reservoirrnwas previously interpreted as a reef complex.rnHowever, lithofacies and seismic attribute (meanrnamplitude) analysis indicate two facies associationsrnare present, skeletal mound and slope to basin.rnRock type (RT) identification using Pore GeometryrnStructure was used as an indicator of reservoirrnheterogeneity. This resulted in the identification ofrnsix RT’s, each with specific porosity andrnpermeability trends, unrelated to lithofacies, butrncorrelated to pore types and sizes. The six rock types are: RT1 associated withrninterparticle-moldic micropores, RT2 associatedrnwith interparticle mesopores, RT3 associated withrninterparticle-moldic mesopores, RT4 associatedrnwith interparticle-moldic macropores, RT5rnassociated with vuggy-moldic macropores, and RT6rnassociated with vuggy-channeling.rnUsing a stochastic methodolgy it was possible tornshow that rock type distribution in the skeletalrnmound facies association controlled porosity andrnpermeability distribution. The study determined thatrnrock type, porosity, and permeability distributionrnare the main factors controlling heterogenity andrnconectivity in the UBR reservoir. The study resultsrnwill be used as the main input to a dynamicrnsimulation for water injection and furtherrndevelopment planning in Krisna Field.