Reservoir Characterization Using Integrated Petrophysical Evaluation, Seismic Attributes, and AVO Modeling in JASMI Field, Niger Delta Basin

Abstract

This study presents an integrated reservoir characterization workflow aimed at delineating the hydrocarbon potential of the JASMI Field in the Niger Delta Basin. The research focuses on transforming raw subsurface data into a predictive geological model to minimize exploration uncertainty and optimize field development strategies. The multidisciplinary approach integrates petrophysical evaluation, structural seismic interpretation, multi-attribute analysis, and Amplitude Versus Offset (AVO) modeling. Data from seven wells and a 3-D post-stack seismic volume were analyzed using Schlumberger Petrel and Hampson Russell software. Four key reservoir intervals (Sands A, B, C, and D) were identified and correlated across the field. Petrophysical analysis identified Sand A as the premier reservoir, exhibiting excellent storage and flow capacity with average effective porosity of 29.3% and permeability reaching up to 758 mD. Sands B and C showed moderate reservoir properties; however, fluid saturation analysis revealed that Sand B is largely water-saturated (Sw ~94%), while Sand C holds selective potential in structurally advantageous zones. Seismic attribute analysis (RMS amplitude, sweetness, and average energy) successfully identified direct hydrocarbon indicators (DHIs). These high-amplitude anomalies strongly correlate with anticlinal features and fault-assisted closures, particularly for Sands A and D. AVO responses further validated these findings with Class II/III anomalies, confirming the presence of hydrocarbons in the mapped reservoirs. The study concludes that Sand A represents the most prospective target for commercial exploitation due to its superior petrophysical quality and strong seismic conformity. Sands B and C offer secondary interest, whereas Sand D exhibits limited economic viability due to lower porosity and higher heterogeneity. This integrated approach enhances reservoir prediction accuracy and provides a robust framework for optimized drilling and future field development in the Niger Delta.