A novel algorithm for asphaltene precipitation modeling in shale reservoirs with the consideration of capillary pressure during the CCUS processes

Abstract

Tight and shale reservoirs have markedly expanded their role in global oil and gas production. However, the overall recovery from these reservoirs is suboptimal, leaving much of the shale oil unrecovered. CO2 flooding is a promising enhanced oil recovery (EOR) technique that can improve oil extraction and simultaneously facilitate carbon capture, utilization, and storage (CCUS). However, this method presents challenges, notably the precipitation and deposition of asphaltene, which risks plugging the nanoporous structure characteristic of shale reservoirs. Given that the nanopore sizes in these reservoirs align closely with asphaltene particle dimensions, the risk of pore and throat blockages during gas injection is pronounced. Although various asphaltene precipitation models have been proposed, there is still a lack of robust algorithms accounting for the substantial influence of capillary pressure on asphaltene precipitation in these nanopores. In this study, a novel three-phase vapor–liquid-asphaltene equilibrium calculation algorithm coupled with capillary effect is developed. The algorithm is first validated by comparing with the experimental data of the Px phase diagram and asphaltene precipitation amount. The validated algorithm is then used to conduct example calculations to demonstrate the robustness of the new algorithm and to examine the impact of capillarity on the three-phase vapor–liquid-solid (VLS) equilibria. Computation results show that capillary pressures in nanopores substantially modify the three-phase VLS equilibria, causing shifts in saturation pressure and influencing asphaltene precipitation. Generally, asphaltene precipitation in nanopores occurs at a lower pressure and gas injection concentration. The smaller pore sizes intensify these effects, but the impact diminishes as pressure increases. Additionally, the gas composition also greatly affects asphaltene precipitation. The results reveal that this new algorithm is robust across different conditions, offering an innovative approach that reliably predicts asphaltene precipitation considering the effect of capillary pressures, paving the way for improved EOR and CCUS in shale reservoirs.