Nanoscale Transport of Multicomponent Fluids in Shales
| dc.contributor.author | Zhang, Hongwei | en |
| dc.contributor.committeechair | Qiao, Rui | en |
| dc.contributor.committeemember | Bai, Xianming | en |
| dc.contributor.committeemember | Boreyko, Jonathan Barton | en |
| dc.contributor.committeemember | Tafti, Danesh K. | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2025-01-03T09:01:12Z | en |
| dc.date.available | 2025-01-03T09:01:12Z | en |
| dc.date.issued | 2025-01-02 | en |
| dc.description.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. | en |
| dc.description.abstractgeneral | Recovering oil from unconventional reservoirs—types of underground rock formations that trap oil in extremely tiny pores, much smaller than the thickness of a strand of hair—is one of the biggest challenges in the petroleum industry. The narrow pore size greatly increases the fraction of the oil flow, and many pores are not even connected, which stops oil to flow out on its own, making it much harder to extract from these reservoirs. Injecting gases into the reservoirs, like carbon dioxide (CO2), has become a promising solution. This method not only helps to push the oil out but also allows part of the injected CO2 to be stored underground, reducing its impact on the atmosphere. To make this process work better, we need in depth understandings of how oil and gas move in these tiny rock spaces. Four studies have been conducted to elucidate the transport phenomena in CO2 injection-based enhanced oil recovery. The first study finds that the exchange between trapped oil and CO2 is significantly influenced by how oil and CO2 stick to the walls of these tiny pores. However, it is observed that commonly used characterization methods do not always work well in the prediction of recovery behavior, indicating the need for a better framework to describe this process. To address this problem, we have brought up a new framework in the second study, which considers both the interactions between oil and CO2 and the interactions with the pore wall. Given the high computational costs, a machine learning model is trained with the data collected to make future predictions faster and cheaper. The third study quantifies the strength of a new type of flow. This flow can be comparable in magnitude to pressure difference-driven flow in tiny pores. Lastly, the recovery of an oil mixture composed of light and heavy hydrocarbons is explored. It was discovered that gas injection not only increases the overall oil recovery rate but also decreases the selectivity toward lighter hydrocarbons. These discoveries pave the way for improved models and strategies to optimize the gas injection process to recover oil from these challenging reservoirs, ultimately meeting the energy needs while supporting efforts to reduce atmospheric CO2 levels. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:42195 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/123884 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | unconventional reservoirs | en |
| dc.subject | interfacial phenomena | en |
| dc.subject | diffusivity | en |
| dc.subject | oil-gas mixture | en |
| dc.title | Nanoscale Transport of Multicomponent Fluids in Shales | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |