Reservoir Modeling of Carbonate on Fika Field: The Challenge to Capture the Complexity of Rock and Oil Types

Abstract

DOI: 10.17014/ijog.v1i2.181The carbonate on Fika Field has a special character, because it grew above a basement high with the thickness and internal character variation. To develop the field, a proper geological model which can be used in reservoir simulation was needed. This model has to represent the complexity of the rock type and the variety of oil types among the clusters. Creating this model was challenging due to the heterogeneity of the Baturaja Formation (BRF): Early Miocene reef, carbonate platform, and breccia conglomerate grew up above the basement with a variety of thickness and quality distributions. The reservoir thickness varies between 23 - 600 ft and 3D seismic frequency ranges from 1 - 80 Hz with 25 Hz dominant frequency. Structurally, the Fika Field has a high basement slope, which has an impact on the flow unit layering slope. Based on production data, each area shows different characteristics and performance: some areas have high water cut and low cumulative production. Oil properties from several clusters also vary in wax content. The wax content can potentially build up a deposit inside tubing and flow-line, resulted in a possible disturbance to the operation. Five well cores were analyzed, including thin section and XRD. Seven check-shot data and 3D seismic Pre-Stack Time Migration (PSTM) were available with limited seismic resolution. A seismic analysis was done after well seismic tie was completed. This analysis included paleogeography, depth structure map, and distribution of reservoir and basement. Core and log data generated facies carbonate distribution and rock typing, defining properties for log analysis and permeability prediction for each zone. An Sw prediction for each well was created by J-function analysis. This elaborates capillary pressure from core data, so it is very similar to the real conditions. Different stages of the initial model were done i.e. scale-up properties, data analysis, variogram modeling, and then the properties were distributed using the geostatistic method. Finally, after G&G collaborated with petrophysicists and reservoir engineers to complete their integrated analysis, a geological model was finally created. After that, material balance was needed to confirm reserve calculations. The result of OOIP (Original Oil in Place) and OGIP (Original Gas in Place) were confirmed, because it was similar to the production data and reservoir pressure. The model was then ready to be used in reservoir simulation.