Enhancing hydrocarbon prediction in carbonate reservoirs using novel SQp and SQs attributes: A case study from Central Luconia, Malaysia

Carbonate reservoirs host a substantial portion of the world’s hydrocarbon resources but remain challenging to characterize due to their heterogeneity and complex pore systems. This study enhances hydrocarbon prediction in the Jintan Field, Central Luconia, by integrating simultaneous inversion with SQp and SQs attenuation attributes. Elastic inversion generated Zp, Zs, density, and Vp/Vs volumes, from which SQp and SQs were derived. Cluster separability analysis shows that SQp-SQs delivers the strongest fluid discrimination across all wells, yielding the highest Silhouette Scores (0.13-0.21), lowest Davies-Bouldin indices (1.17-1.38), and Calinski-Harabasz values up to 409, substantially outperforming conventional attributes. These improvements enabled clearer detection of gas-bearing carbonate units and enhanced reservoir continuity mapping, particularly in intervals poorly resolved by traditional inversion methods. The integrated elastic-attenuation workflow reduces interpretation ambiguity and provides a more reliable approach for characterizing heterogeneous Central Luconia carbonates.