Abstract

This study presents an integrated, multidisciplinary petrophysical workflow. Key solutions include reinterpreting logs with NMR data to distinguish between effective and noneffective porosity and assess fluid mobility through Free Fluid Index (FFI) and Bound Fluid Volume (BFV). Saturation models are refined using Waxman-smits water saturation approaches, supported by saturation height model and historical production data to recalibrate conventional equations like Archie. Fracture and flow behavior are evaluated using borehole image logs to identify conductive fractures and flow barriers, helping areas which have productive fracture corridors. Reservoir zonation is improved through Reservoir Quality Index (RQI) and flow unit analysis based on available core and log data, aiding targeted stimulation and recompletion efforts. Additionally, machine learning (MLR) is used for permeability prediction, especially useful in fields with inconsistent data quality.