<![CDATA[Field X in the Central Sumatra Basin presents unique characteristics due to suboptimal data quality for seismic inversion analysis. However, a comprehensive reservoir characterization is still required. Therefore, alternative strategies are needed to optimize the available data, one of which is multi-attribute seismic analysis. This study aims to characterize the reservoir in the Menggala Formation, Central Sumatra Basin, using multi-attribute seismic analysis. The petrophysical parameters used include density porosity (DPHI), water saturation (Sw), and shale volume (Vsh) as primary indicators for assessing reservoir quality. The dataset consists of post-stack 3D seismic data and well log data from four calibration wells, including gamma ray, density, neutron, and resistivity logs. The research workflow began with petrophysical analysis to derive DPHI, Sw, and Vsh values from the well log data, followed by seismic attribute extraction within the target reservoir intervals. Multi-attribute linear regression was then applied to establish a quantitative relationship between seismic attributes and well log data, enabling the lateral prediction of petrophysical parameter distributions across the study area. Model validation was conducted by comparing the predicted values against well log data, yielding correlation coefficients of r= 0.63 (Vsh), r= 0.85 (DPHI), indicating sufficiently reliable and acceptable prediction results. Based on the modeled property distributions, potential reservoir zones are characterized by low Vsh, high DPHI, reflecting the presence of clean sandstone with good hydrocarbon potential. These findings serve as a valuable reference for identifying prospect zones and supporting future development planning within the study area.]]>
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