Impact of Biomarker ...

Reservoir classification remains a fundamental aspect of petroleum geoscience and production optimization, serving as a key determinant of a nation’s ability to manage, audit, and allocate hydrocarbon resources accurately. In Nigeria, where the Niger Delta represents the epicenter of petroleum production, understanding the subtle geochemical variations that differentiate oil and gas reservoirs is vital for both technical and policy purposes, particularly under OPEC audit and classification criteria. This study investigates the impact of biomarker distribution on the characterization and classification of reservoir fluids within the Niger Delta Basin using gas chromatography–flame ionization detection (GC-FID) and compositional fingerprinting techniques. Fifty (50) reservoir fluid samples were analyzed across representative stratigraphic intervals and depositional settings. The distribution of n-alkanes (n-C7–n-C35), isoprenoids (pristane and phytane), and diagnostic biomarker ratios such as Pr/Ph, C17/C18, Carbon Preference Index (CPI), and sterane–terpane distributions were evaluated. Results demonstrate that biomarker assemblages provide clear, reproducible discrimination between oil, gas-condensate, and borderline systems. Gas-dominant fluids are characterized by lighter hydrocarbon dominance (n-C7–n-C15), Pr/Ph < 1.0, CPI ≈ 1.0, and higher maturity indicators, while oil-prone systems exhibit heavier n-alkane envelopes (n-C20–n-C35), Pr/Ph > 1.5, and elevated CPI values. Transitional fluids display intermediate signatures reflective of mixed organic inputs and moderate maturity. The findings confirm that GC-FID-based biomarker fingerprinting offers a robust, auditable, and cost-effective framework for reservoir classification, with significant implications for reservoir management, production forecasting, and Nigeria’s compliance with OPEC audit requirements.