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Adsorption-Mediated Fluid Transport at the Nanoscale

Injecting CO2 into unconventional reservoirs to enhance oil recovery has been widely studied due to its potential to improve the profitability of these reservoirs. CO2 Huff-n-Puff is emerging as a promising method, but exploiting its full potential is challenging due to difficulties in optimizing its operations. The latter arises from the limited understanding of CO2 and oil transport in unconventional reservoirs.
This dissertation used molecular dynamics simulations to study the storage and transport of oil and CO2 in unconventional reservoirs in single nanopores. The first study examined the modulation of oil flow in calcite pores by CO2. It is discovered that CO2 molecules adsorb strongly on calcite walls and can change decane permeability through 8 nm-wide pores by up to 30%. They impede decane flow at moderate adsorption density but enhance flow as adsorption approaches saturation. The second study investigated the CO2 transport in 4 nm-wide calcite pores during the soaking phase of Huff-n-Puff operations. CO2 entering the pore can become adsorbed on pore walls and diffuse on them or diffuse as free CO2 molecules. The accumulation of CO2 follows a diffusion behavior with an effective diffusivity ~50% smaller than bulk CO2. Two dimensionless groups are proposed to gauge the importance of surface adsorption and diffusion in CO2 storage and transport in nanopores. The third study examined the extraction of decane initially sealed in a 4 nm-wide calcite pore through exchange with CO2 and CH4 in a reservoir. The CO2-decane exchange is significantly driven by the evolution of adsorbed oil and gas initially, but a transition to dominance by free oil and gas occurs later; for CH4-decane exchange, the opposite occurs. The net gas accumulation and decane extraction follow the diffusive law, but their effective diffusivities do not always align well with the self-diffusion coefficients of CO2, CH4, and decane in the nanopore.
The three studies identified the essential roles of gas/oil adsorption in their net transport in nanopores and, thus, unconventional reservoirs. Delineating these roles and formulating dimensionless groups to gauge their importance help develop better models for enhanced oil recovery from unconventional reservoirs by CO2 injection. / Doctor of Philosophy / Unconventional reservoirs are hydrocarbon-bearing formations with ultralow permeabilities, and they have emerged as a critical source of liquid petroleum production in the United States over the past decade. However, because oil is trapped in nanoscale pores in these reservoirs, the oil recovery rate is low. Therefore, many methods have been developed to enhance the oil recovery from unconventional reservoirs. One of the popular methods is to inject gas into reservoirs to enhance oil recovery. Improving this method's efficacy requires a fundamental understanding of the thermodynamic and transport phenomena underlying its operation is needed.
This dissertation used molecular dynamics simulations to study the storage and transport of oil and CO2 in unconventional reservoirs at the single nanopore scale. Three series of studies have been performed to elucidate how CO2 modulates the flow of oil inside nanopores, how CO2 enters a nanopore filled with oil, and how oil is extracted from the nanopore by the ingression of CO2. These studies showed that when CO2 molecules adsorb strongly on a nanopore's walls, they can either enhance or impede the permeation of oil through the pore. The ingression of CO2 into an oil-filled nanopore and the concurrent oil extraction can be described by the same equation for the conduction of heat in one-dimensional objects. The CO2 ingression and oil extraction rates are heavily affected by the adsorption of CO2 and oil on the nanopore's walls. These results highlight the important effects of surface adsorption on the storage and transport of gas and oil in nanopores and, thus, unconventional oil reservoirs. Incorporating these effects into oil recovery models will improve their predictive power, and thus help model-guided optimization of oil recovery.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/109712
Date20 April 2022
CreatorsMoh, Do Yoon
ContributorsMechanical Engineering, Qiao, Rui, Chen, Cheng, Boreyko, Jonathan B., Paul, Mark R.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
LanguageEnglish
Detected LanguageEnglish
TypeDissertation
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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