In subsurface reservoir studies, permeability is an unpredictable parameter, and the main challenge is identifying a parameter that strongly correlates with it. To address this, analyses were conducted using a comprehensive dataset. The study is based on 1575 thin sections obtained from approximately 402.63 meters of cores, along with 1445 porosity and 1390 permeability data points. Additionally, wireline log data covering 462.63 meters from the Dalan and Kangan formations in a key well located in the central Persian Gulf is included. Based on the available logs, artificial effective porosity logs were obtained through the deterministic petrophysical evaluation methods, using sonic, density, density/neutron, and neutron/sonic. The flow zone indicator, Winland’s R35 and electrofacies were used to manage the heterogeneity. It was concluded that the effective porosity log employed the ratio of compressional to shear wave velocity instead of the sonic log in the neutron/sonic method, demonstrate a strong correlation with permeability. Therefore, it can be used for predicting this variable parameter in heterogenous reservoirs. In this study, a new, repeatable, data-driven approach is introduced that uses wireline log-derived porosity logs. The unique use of Vp/Vs ratios in constructing effective porosity logs offers a novel, highly correlated predictor of permeability.
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