Nanoscale Transport of Multicomponent Fluids in Shales

Abstract

CO2 injection has demonstrated significant potential for enhanced oil recovery techniques in unconventional reservoirs, but there exists many challenges in optimizing its operations due to the limited understanding of CO2-oil transport mechanisms in these systems. This dissertation addresses these challenges using molecular dynamics (MD) simulations by investigating the gas and oil transport behaviors and properties within single nanopores under reservoir conditions. The first study examines the exchange dynamics of decane with CO2 and CH4 in a 4 nm-wide calcite nanopore. It is shown that both gases form distinct adsorbed and free molecular populations upon entering the pores, leading to different extraction dynamics. Notably, CO2-decane exchange is initially driven by adsorbed populations, with a transition to free populations later; whereas CH4 -decane exchange follows the opposite pattern. Despite these differences, the transport of both gases apparently follows the same diffusive behavior, with CH4 exhibiting higher effective diffusivities. By calculating self-diffusivities at various relevant compositions, it is found they do not always align well with their effective diffusivities. The second study therefore focuses on Maxwell-Stefan (M-S) diffusivities as a more comprehensive framework to describe the diffusion of CO2-decane mixtures in the first study. It is found that D12 (CO2-decane interactions) remains relatively constant across compositions, unlike bulk mixtures, while D1,s (CO2-wall interactions) increases sharply with CO2 loading. In contrast, D2,s (decane-wall interactions) shows a nonmonotonic trend and, unexpectedly, becomes negative under certain compositions. These phenomena are linked to the strong adsorption of CO2, causing significant density heterogeneity and reduced mobility. Using a multi-task Gaussian process regression model, the M−S diffusivities can be predicted with a relative root mean square error below 10%, significantly reducing computational demand for their practical usage. The third study examines concentration gradient driven diffusio-osmosis of oil-CO2 mixtures within silica and calcite nanopores. Despite higher CO2 enrichment near calcite walls, diffusio-osmotic is only marginally stronger than in silica pores, which is attributed to the variations in interfacial fluid structures and hydrodynamic properties in different pores. Continuum simulations suggest that diffusio-osmosis becomes increasingly significant compared to Poiseuille flow as pore width decreases. The fourth study investigates the oil mixture (C10+C19) recovery from a 4 nm-wide calcite dead-end pore with and without CO2 injection. It was found that CO2 accelerates oil recovery and reduces selectivity for lighter components (e.g., C10) compared to the recovery without CO2. Such improvements are influenced by interfacial and bulk phenomena, including adsorption competition and solubilization effects. Together, these studies provide quantitative insights into CO2-oil transport mechanisms and properties in nanopores. Such insights can help develop better reservoir simulators to guide the optimization of CO2 injection-based enhanced oil recovery in unconventional reservoirs.