Enhanced oil recovery in reservoirs via diffusion-driven CO2 flooding: Experimental insights and material balance modeling

CO 2 flooding is central to carbon utilization technologies, yet conventional waterflooding models fail to capture the complex interactions between CO2 and formation fluids. In this study, one- and two-dimensional nuclear magnetic resonance experiments reveal that CO2 markedly enhances crude oil mobility during miscible displacement via multiple synergistic mechanisms, yielding a recovery factor of 60.97%, which surpasses that of immiscible displacement (maximum 57.53%). Guided by these findings, we propose a convection–diffusion model that incorporates the diffusion coefficient (D) and porosity (ϕ) as key parameters. This model captures the spatiotemporal evolution of the CO2 front and addresses a key limitation of conventional formulations—the omission of diffusion effects. It improves predictions of gas breakthrough time and enables optimized injection design for low-permeability reservoirs. Extending classical material balance theory, we develop an enhanced CO2 flooding equation that integrates critical transport phenomena. This formulation incorporates CO2 diffusion, oil phase expansion, reservoir adsorption, and gas compressibility to describe the dynamic transport and mass compensation of injected CO2. Validation through experimental and numerical data confirms the model's robustness and applicability under low-permeability conditions. The proposed framework overcomes limitations of physical experiments under extreme environments and offers theoretical insight into oil recovery enhancement and CO2 injection strategy optimization.