Enhanced oil recovery in reservoirs via diffusion-driven $\text{CO}_{2}$ flooding: Experimental insights and material balance modeling

TL;DR

This paper demonstrates that diffusion-driven CO2 flooding significantly improves oil recovery by combining experimental NMR insights with advanced modeling that includes diffusion, adsorption, and compressibility effects, leading to optimized injection strategies.

Contribution

It introduces a novel convection-diffusion model and an extended material balance equation that incorporate diffusion and other transport phenomena for better prediction and optimization of CO2 flooding in reservoirs.

Findings

CO2 enhances oil mobility via multiple mechanisms.

Recovery factor exceeds 60%, surpassing immiscible displacement.

The new model accurately predicts gas breakthrough and aids in injection design.

Abstract

$\text{CO}_{2}$ flooding is central to carbon utilization technologies, yet conventional waterflooding models fail to capture the complex interactions between CO$_2$ and formation fluids. In this study, one- and two-dimensional nuclear magnetic resonance experiments reveal that $\text{CO}_{2}$ 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 ($\phi$) as key parameters. This model captures the spatiotemporal evolution of the $\text{CO}_{2}$ 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 $\text{CO}_{2}$ flooding equation that integrates critical transport phenomena. This formulation incorporates $\text{CO}_{2}$ diffusion, oil phase expansion, reservoir adsorption, and gas compressibility to describe the dynamic transport and mass compensation of injected $\text{CO}_{2}$. 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 $\text{CO}_{2}$ injection strategy optimization.