Reservoir Quality Evaluation Using Petrophysical Logs and Seismic Attribute Techniques: A Case Study of GOTO Field, Niger Delta

Abstract

The 21st-century global energy demand necessitates advanced reservoir characterization to optimize hydrocarbon exploitation and minimize drilling risks. This study integrates petrophysical analysis and multi-attribute seismic interpretation to evaluate the hydrocarbon potential of the GOTO Field in the Niger Delta. Using suites of well logs from seven wells and 3D post-stack seismic data, four reservoir sands (A, B, C, and D) were delineated and correlated across the field. Petrophysical evaluation reveals that Sand A is the most prospective unit, exhibiting excellent reservoir quality with average effective porosity of 29.3%, permeability reaching 758 mD, and moderate water saturation. Sands C and D show moderate quality with localized potential, while Sand B is identified as predominantly water-saturated (91–96%). Seismic interpretation identified major structural traps, including rollover anticlines and fault-assisted closures. Analysis of seismic attributes—including RMS Amplitude, Average Energy, and Sweetness—revealed strong anomalies in Sands A, C, and D that conform to structural highs, serving as direct hydrocarbon indicators (DHIs). The high degree of consistency between petrophysical data and seismic attribute responses demonstrates that this integrated quantitative approach significantly reduces exploration uncertainty and improves the precision of reservoir evaluation in complex deltaic environments.