Modeling Pore-Scale Oil-Gas Systems Using Gradient Theory with Peng-Robinson Equation of State

Handle URI:
http://hdl.handle.net/10754/613012
Title:
Modeling Pore-Scale Oil-Gas Systems Using Gradient Theory with Peng-Robinson Equation of State
Authors:
Fan, Xiaolin; Kou, Jisheng; Qiao, Zhonghua; Sun, Shuyu ( 0000-0002-3078-864X )
Abstract:
This research addresses a sequential convex splitting method for numerical simulation of multicomponent two-phase fluids mixture in a single-pore at constant temperature, which is modeled by the gradient theory with Peng-Robinson equation of state. The gradient theory of thermodynamics and variational calculus are utilized to obtain a system of chemical equilibrium equations which are transformed into a transient system as a numerical strategy on which the numerical scheme is based. The proposed numerical algorithm avoids computing Hessian matrix arising from the second-order derivative of homogeneous contribution of free energy; it is also quite robust. This scheme is proved to be unconditionally component-wise energy stable. The Raviart-Thomas mixed finite element method is applied to spatial discretization.
KAUST Department:
Earth Science and Engineering
Citation:
Modeling Pore-Scale Oil-Gas Systems Using Gradient Theory with Peng-Robinson Equation of State 2016, 80:1364 Procedia Computer Science
Publisher:
Elsevier BV
Journal:
Procedia Computer Science
Conference/Event name:
International Conference on Computational Science 2016
Issue Date:
1-Jun-2016
DOI:
10.1016/j.procs.2016.05.434
Type:
Conference Paper
ISSN:
18770509
Sponsors:
The research of Fan and Sun reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S1877050916309140
Appears in Collections:
Conference Papers

Full metadata record

DC FieldValue Language
dc.contributor.authorFan, Xiaolinen
dc.contributor.authorKou, Jishengen
dc.contributor.authorQiao, Zhonghuaen
dc.contributor.authorSun, Shuyuen
dc.date.accessioned2016-06-14T09:13:27Z-
dc.date.available2016-06-14T09:13:27Z-
dc.date.issued2016-06-01-
dc.identifier.citationModeling Pore-Scale Oil-Gas Systems Using Gradient Theory with Peng-Robinson Equation of State 2016, 80:1364 Procedia Computer Scienceen
dc.identifier.issn18770509-
dc.identifier.doi10.1016/j.procs.2016.05.434-
dc.identifier.urihttp://hdl.handle.net/10754/613012-
dc.description.abstractThis research addresses a sequential convex splitting method for numerical simulation of multicomponent two-phase fluids mixture in a single-pore at constant temperature, which is modeled by the gradient theory with Peng-Robinson equation of state. The gradient theory of thermodynamics and variational calculus are utilized to obtain a system of chemical equilibrium equations which are transformed into a transient system as a numerical strategy on which the numerical scheme is based. The proposed numerical algorithm avoids computing Hessian matrix arising from the second-order derivative of homogeneous contribution of free energy; it is also quite robust. This scheme is proved to be unconditionally component-wise energy stable. The Raviart-Thomas mixed finite element method is applied to spatial discretization.en
dc.description.sponsorshipThe research of Fan and Sun reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).en
dc.publisherElsevier BVen
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1877050916309140en
dc.rightsArchived with thanks to Procedia Computer Science, Under a Creative Commons license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectConvex Splittingen
dc.subjectGradient theoryen
dc.subjectOil-gas systemsen
dc.subjectPeng-Robinson equation of stateen
dc.subjectMixed finite element methodsen
dc.titleModeling Pore-Scale Oil-Gas Systems Using Gradient Theory with Peng-Robinson Equation of Stateen
dc.typeConference Paperen
dc.contributor.departmentEarth Science and Engineeringen
dc.identifier.journalProcedia Computer Scienceen
dc.conference.date6-8 June 2016en
dc.conference.nameInternational Conference on Computational Science 2016en
dc.conference.locationSan Diego, California, USAen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionHubei Engineering University, CNen
dc.contributor.institutionThe Hong Kong Polytechnic University, HKen
kaust.authorFan, Xiaolinen
kaust.authorSun, Shuyuen
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