RESERVOIR CHARACTERIZATION FOR CARBONATE RESERVOIR IN BATURAJA FORMATION, IN "X" FIELD, SOUTH SUMATRA BASIN THROUGH THE INTEGRATION OF ROCK PHYSICS AND EXTENDED ELASTIC IMPEDANCE INVERSION - Putri Pramestiningrum, Dinda
More than 50% of the world's oil and gas reserves are stored in carbonate reservoirs. However, the carbonate reservoir is more complex due to the influence of variations in the pore types that compose the reservoir, making it difficult to characterize this reservoir. In this research, the characterization of carbonate reservoirs for the Baturaja Formation, South Sumatra Basin will be carried out using a rock physics approach through pore type analysis and by seismic inversion. The pore type in carbonate rocks can be explained by using the aspect ratio value. In modeling the aspect ratio is influenced by the accuracy in estimating the elastic modulus of the rock matrix. In this study, the elastic modulus of the rock matrix was estimated using the Krief model approach and the pore type estimation was carried out using the Kumar-Han method. In estimating the pore type using Kumar-Han, the data will be divided into two different zones, namely soft and stiff with Vp Wyllie time-average and Hashin-Shtrikmann. The aspect ratio value itself will be determined using the Kuster-Toksoz method. From the seismic inversion approach, Extended Elastic Impedance (EEI) seismic inversion was carried out to extract the volume of the most sensitive elastic parameters, namely lambda-rho and mu-rho. From the correlation analysis of the chi angle, it is found that the angles that have the maximum correlation for lambda-rho and mu-rho are 870 and -280, respectively. The results of the pore type analysis show that our reservoir is dominated by stiff pore and the analysis results show that there is a relationship between the elastic parameter and the aspect ratio where the more stiff our pores are, the higher the elastic parameter value will be. From the analysis of the results of the seismic inversion, it can be seen that our reservoir distribution is in the high area, seen from the distribution of low lambda-rho, mu-rho and lambda / mu values.