ANALYSIS OF ACOUSTIC IMPEDANCE (AI) INVERSION AND MULTI-ATTRIBUTE SEISMIC METHODS FOR HYDROCARBON RESERVOIR CHARACTERIZATION IN THE CEE FIELD

Abstract

This study aims to characterize the hydrocarbon reservoir in the CEE Field, Upper Talang Akar Formation, South Sumatra Basin, using an acoustic impedance (AI) seismic inversion approach combined with multi-attribute seismic analysis. Well log data were utilized to identify lithology and target zones, which are characterized by low gamma ray values, porosity above 0.2, and low water saturation. AI inver- sion identified a reservoir zone with acoustic impedance values between 5,000 and 7,000 g/cc*m/s, consistent with the characteristics of sandstone as a reservoir rock. A high correlation (0.91) between the inversion results and well log data indicates the reliability of the inversion output. Furthermore, the multi-attribute stepwise re- gression method was applied to predict porosity distribution, yielding a training correlation of 0.856 and a validation correlation of 0.711. These results enable higher-resolution mapping of the reservoir zone, both laterally and vertically. The integration of AI inversion and multi-attribute analysis has proven effective in en- hancing the accuracy of subsurface geological modeling and in supporting more precise identification of hydrocarbon-prospective zones.