Graduate Studies
Application of PC-SAFT Equation of State to Bitumen/Solvent Systems
Abstract
dc:description.abstractSolvent-assisted process is promising to recovery Canada's bitumen recourses, but the prediction techniques for the solubility, density and viscosity of bitumen and solvent mixtures in reservoir simulation are not well developed. This thesis works to develop the application methodology of the simplified Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) to bitumen and solvent mixtures. New binary interaction coefficient correlation and bitumen characterization method are developed to model the solubility, density and viscosity of such mixtures. These results are also integrated into the reservoir simulation of solvent-assisted recovery. Using the developed method, the average absolute relative deviations (AARDs) are 6.6% for the solubility, 2.3% for the density and 14.6% for the viscosity. In addition, the reservoir simulation results indicate good agreement with the sandpack production data using solvents. This thesis has developed the methodology to model the phase behavior and recovery process of bitumen and solvent using PC-SAFT.
Degree
thesis:*- Name thesis:degree_name
- Master of Science (MSc)
- Discipline thesis:degree_discipline
- Chemical and Petroleum Engineering
- Grantor dc:publisher.institution
- Graduate Studies
- Year dc:date.issued
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Ma, Mingxu
- Advisors dc:contributor.advisor
-
- Chen, Shengnan (Nancy)
- Abedi, Jalal
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- OAI identifier oai:identifier
- oai:ucalgary.scholaris.ca:11023/2320