A mechanistic model has been developed and validated to quantify a single gas bubble growth with considering multicomponent gas diffusion in solvent(s)–CO2–heavy oil systems under nonequilibrium conditions. Experimentally, constant-composition expansion (CCE) experiments are conducted for C3H8–CO2–heavy oil systems under equilibrium and nonequilibrium conditions, respectively. Theoretically, the classic continuity equation, motion equation, diffusion–convection equation, real gas equation, and Peng–Robinson equation of state (PR EOS) are integrated into an equation matrix to dynamically predict gas bubble growth. Also, the viscous term of motion equation on the gas phase pressure is included due mainly to the viscous nature of heavy oil. The newly proposed model has been validated by using the experimentally measured gas bubble radius as a function of time with good accuracy. Combining with the experimental measurements, the critical nucleus radius and gas bubble growth are quantitatively predicted with the newly proposed model. Effects of mass transfer, supersaturation pressure, mole concentration of each component, liquid cell radius, and pressure decline rate on the gas bubble growth are examined and analyzed. In general, gas bubble growth rate is found to increase with an increase of each of the aforementioned five parameters though the contribution of individual component in a gas mixture to the bubble growth rate is different. A one-step pressure drop and the unlimited liquid volume surrounding a gas bubble are considered to be the necessary conditions to generate the linear relationship between gas bubble radius and the square root of time.
Skip Nav Destination
Article navigation
March 2017
Research-Article
Quantification of a Single Gas Bubble Growth in Solvent(s)–CO2–Heavy Oil Systems With Consideration of Multicomponent Diffusion Under Nonequilibrium Conditions
Yu Shi,
Yu Shi
Petroleum Systems Engineering,
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
Search for other works by this author on:
Daoyong Yang
Daoyong Yang
Petroleum Systems Engineering,
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
e-mail: tony.yang@uregina.ca
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
e-mail: tony.yang@uregina.ca
Search for other works by this author on:
Yu Shi
Petroleum Systems Engineering,
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
Daoyong Yang
Petroleum Systems Engineering,
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
e-mail: tony.yang@uregina.ca
Faculty of Engineering and
Applied Science,
University of Regina,
Regina, SK S4S 0A2, Canada
e-mail: tony.yang@uregina.ca
1Corresponding author.
Contributed by the Petroleum Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received August 30, 2016; final manuscript received October 27, 2016; published online November 29, 2016. Editor: Hameed Metghalchi.
J. Energy Resour. Technol. Mar 2017, 139(2): 022908 (11 pages)
Published Online: November 29, 2016
Article history
Received:
August 30, 2016
Revised:
October 27, 2016
Citation
Shi, Y., and Yang, D. (November 29, 2016). "Quantification of a Single Gas Bubble Growth in Solvent(s)–CO2–Heavy Oil Systems With Consideration of Multicomponent Diffusion Under Nonequilibrium Conditions." ASME. J. Energy Resour. Technol. March 2017; 139(2): 022908. https://doi.org/10.1115/1.4035150
Download citation file:
Get Email Alerts
Related Articles
Experimental and Theoretical Determination of Diffusion Coefficients of CO 2 -Heavy Oil Systems by Coupling Heat and Mass Transfer
J. Energy Resour. Technol (March,2017)
Machine Learning-Based Improved Pressure–Volume–Temperature Correlations for Black Oil Reservoirs
J. Energy Resour. Technol (November,2021)
A Mathematical Model of Alveolar Gas Exchange in Partial Liquid Ventilation
J Biomech Eng (February,2005)
Hydrodynamic Force and Heat/Mass Transfer From Particles, Bubbles, and Drops—The Freeman Scholar Lecture
J. Fluids Eng (March,2003)
Related Proceedings Papers
Related Chapters
Energy Balance for a Swimming Pool
Electromagnetic Waves and Heat Transfer: Sensitivites to Governing Variables in Everyday Life
Risk Mitigation for Renewable and Deispersed Generation by the Harmonized Grouping (PSAM-0310)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
Thermodynamic Performance
Closed-Cycle Gas Turbines: Operating Experience and Future Potential