Optimizing gas injection strategies: a comparative equation of state-based study of asphaltene precipitation and onset pressures
Year: 2026
Type: article
Abstract: Asphaltene deposition poses a significant challenge in gas injection processes for Enhanced Oil Recovery (EOR), as it can severely impede fluid flow and diminish reservoir productivity. This study investigates the impact of injected gas composition, specifically Carbon Dioxide (CO₂), Nitrogen (N₂), and natural gas/Methane (CH₄), on asphaltene onset points and the corresponding amount of precipitation. Our analysis utilized the Peng-Robinson (PR) and Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) Equations of State (EOS), as implemented in the PVTsim Nova software. Simulations were systematically performed on six diverse crude oil samples across seven distinct gas injection scenarios. The results consistently demonstrate that increasing the molar percentage of CO₂ in the injected gas leads to a substantial reduction in asphaltene instability, manifesting as an average 15% decrease in Upper Asphaltene Onset Pressure (UAOP) and, in certain instances, over 50% reduction in the asphaltene precipitation amount. Conversely, the introduction of less polar gases, such as N₂ or CH₄, significantly destabilizes the crude oil, increasing the UAOP by up to 49% in some cases and markedly elevating precipitation levels; for example, an 80% N₂ content in one scenario more than doubled asphaltene precipitation. The present study provides an integrated analysis of asphaltene phase behavior by simultaneously evaluating the asphaltene onset points and precipitation volume. It also examines the fundamental influence of injected gas molecular polarity on asphaltene stability through solubility parameter analysis. These findings offer valuable guidance for the design and optimization of gas injection strategies to minimize asphaltene deposition risks and improve the efficiency and sustainability of EOR operations.
Institution: Amirkabir University of Technology
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,390
OpenAlex ID: W7212353203