Monte Carlo molecular simulation of phase-coexistence for oil production and processing

Handle URI:
http://hdl.handle.net/10754/564331
Title:
Monte Carlo molecular simulation of phase-coexistence for oil production and processing
Authors:
Li, Jun; Sun, Shuyu ( 0000-0002-3078-864X ) ; Calo, Victor M. ( 0000-0002-1805-4045 )
Abstract:
The Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components, the Gibbs-NPT ensemble Monte Carlo method is employed in the simulation while the mole fraction of each component in each phase is modeled as a Leonard-Jones fluid. As the results of Monte Carlo simulations usually contain huge statistical error, the blocking method is used to estimate the variance of the simulation results. Additionally, in order to improve the simulation efficiency, the step sizes of different trial moves is adjusted automatically so that their acceptance probabilities can approach to the preset values.
KAUST Department:
Applied Mathematics and Computational Science Program; Earth Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Environmental Science and Engineering Program; Computational Transport Phenomena Lab; Numerical Porous Media SRI Center (NumPor)
Publisher:
Society of Petroleum Engineers (SPE)
Journal:
SPE Reservoir Characterisation and Simulation Conference and Exhibition
Conference/Event name:
SPE Reservoir Characterisation and Simulation Conference and Exhibition 2011, RCSC 2011
Issue Date:
2011
DOI:
10.2118/148282-ms
Type:
Conference Paper
ISBN:
9781618394224
Appears in Collections:
Conference Papers; Environmental Science and Engineering Program; Applied Mathematics and Computational Science Program; Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program; Computational Transport Phenomena Lab

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Junen
dc.contributor.authorSun, Shuyuen
dc.contributor.authorCalo, Victor M.en
dc.date.accessioned2015-08-04T06:23:56Zen
dc.date.available2015-08-04T06:23:56Zen
dc.date.issued2011en
dc.identifier.isbn9781618394224en
dc.identifier.doi10.2118/148282-msen
dc.identifier.urihttp://hdl.handle.net/10754/564331en
dc.description.abstractThe Gibbs-NVT ensemble Monte Carlo method is used to simulate the liquid-vapor coexistence diagram and the simulation results of methane agree well with the experimental data in a wide range of temperatures. For systems with two components, the Gibbs-NPT ensemble Monte Carlo method is employed in the simulation while the mole fraction of each component in each phase is modeled as a Leonard-Jones fluid. As the results of Monte Carlo simulations usually contain huge statistical error, the blocking method is used to estimate the variance of the simulation results. Additionally, in order to improve the simulation efficiency, the step sizes of different trial moves is adjusted automatically so that their acceptance probabilities can approach to the preset values.en
dc.publisherSociety of Petroleum Engineers (SPE)en
dc.titleMonte Carlo molecular simulation of phase-coexistence for oil production and processingen
dc.typeConference Paperen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.contributor.departmentEarth Science and Engineering Programen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentEnvironmental Science and Engineering Programen
dc.contributor.departmentComputational Transport Phenomena Laben
dc.contributor.departmentNumerical Porous Media SRI Center (NumPor)en
dc.identifier.journalSPE Reservoir Characterisation and Simulation Conference and Exhibitionen
dc.conference.date9 October 2011 through 11 October 2011en
dc.conference.nameSPE Reservoir Characterisation and Simulation Conference and Exhibition 2011, RCSC 2011en
dc.conference.locationAbu Dhabien
kaust.authorSun, Shuyuen
kaust.authorCalo, Victor M.en
kaust.authorLi, Junen
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