O. A. OLAFUYI

Worldwide efforts to reduce carbon emissions require technologies that can substantially decrease human-caused CO₂ releases while preserving energy reliability. Carbon Capture and Storage (CCS) presents an interim solution by capturing carbon dioxide from industrial facilities and storing it permanently underground in geological structures. This study examines the viability of storing CO₂ in a typical depleted oil field in Nigeria's Niger Delta Basin using sophisticated compositional modeling through Computer Modelling Group (CMG) software. A detailed three-dimensional reservoir model was constructed using geological, rock property, and production data to simulate extended-term CO₂ injection, plume movement, and entrapment patterns. The research assesses actual storage volumes, injection limitations, pressure changes, and the roles of various trapping methods—including structural containment, residual entrapment, dissolution, and mineralization—across a century-long timeframe. Findings show storage capacity ranging from 5.5 to 11.2 million tonnes of CO₂ with pressure remaining safely under fracture thresholds, confirming reliable containment with negligible escape potential. Parameter studies demonstrate that variations in rock permeability, remaining oil content, and injection speeds significantly affect storage performance and CO₂ distribution patterns. The results validate that Nigeria's depleted petroleum reservoirs offer suitable geological and technical conditions for secure, effective carbon sequestration. This research provides a simulation-driven methodology for nationwide CCS implementation, advancing Nigeria's progression toward reduced-carbon energy systems and adherence to global climate commitments.

Condensate banking is a critical flow assurance challenge in gas condensate reservoirs that can reduce well productivity by up to 60% due to near-wellbore liquid accumulation when reservoir pressure falls below the dew point. Accurate prediction of this phenomenon is essential for optimizing field development strategies, well design, and production forecasting. However, conventional cubic equations of state, particularly the widely used Peng-Robinson (PR) equation, systematically underpredict the severity of condensate banking due to fundamental limitations in their mean-field thermodynamic assumptions. This research presents a novel modification to the Peng-Robinson equation of state that incorporates density-dependent attractive forces to better capture the molecular correlations and beyond-mean-field effects that dominate liquid phase behavior in gas condensate systems. The proposed PR-DD (Peng-Robinson with DensityDependent attraction) modification introduces a densitycorrection function, f(ρᵣ) = 1 + c₁ρᵣ² + c₂ρᵣ⁴, to the attractive parameter, where ρᵣ is the reduced density and c₁, c₂ are empirically determined coefficients. This modification addresses the critical deficiency of standard cubic equations in representing the enhanced intermolecular attractions that occur at liquid densities, particularly relevant for accurately predicting retrograde condensation and liquid dropout volumes. The methodology encompasses three major components: (1) development and validation of the PR-DD equation of state against experimental PVT data, including constant volume depletion (CVD) tests showing liquid dropout curves; (2) implementation of PR-DD within a fully compositional reservoir simulator using local grid refinement to capture near-wellbore gradients; and (3) comprehensive comparison with standard PR predictions through parallel simulations of a representative offshore gas condensate reservoir