High-performance modeling of CO2 sequestration by coupling reservoir simulation and molecular dynamics

Handle URI:
http://hdl.handle.net/10754/575765
Title:
High-performance modeling of CO2 sequestration by coupling reservoir simulation and molecular dynamics
Authors:
Bao, Kai; Yan, Mi; Lu, Ligang; Allen, Rebecca; Salam, Amgad; Jordan, Kirk E.; Sun, Shuyu ( 0000-0002-3078-864X )
Abstract:
The present work describes a parallel computational framework for CO2 sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel HPC systems. In this framework, a parallel reservoir simulator, Reservoir Simulation Toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, while the molecular dynamics simulations are performed to provide the required physical parameters. Numerous technologies from different fields are employed to make this novel coupled system work efficiently. One of the major applications of the framework is the modeling of large scale CO2 sequestration for long-term storage in the subsurface geological formations, such as depleted reservoirs and deep saline aquifers, which has been proposed as one of the most attractive and practical solutions to reduce the CO2 emission problem to address the global-warming threat. To effectively solve such problems, fine grids and accurate prediction of the properties of fluid mixtures are essential for accuracy. In this work, the CO2 sequestration is presented as our first example to couple the reservoir simulation and molecular dynamics, while the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical process in the future. Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability are observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well demonstrated with several experiments with hundreds of millions to a billion cells. To our best knowledge, the work represents the first attempt to couple the reservoir simulation and molecular simulation for large scale modeling. Due to the complexity of the subsurface systems, fluid thermodynamic properties over a broad range of temperature, pressure and composition under different geological conditions are required, for which the experimental results are limited. Although equations of state can reproduce the existing experimental data within certain ranges of conditions, their extrapolation out of the experimental data range is still limited. The presented framework will definitely provide better flexibility and predictability compared with conventional methods.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Earth Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Environmental Science and Engineering Program; Computational Transport Phenomena Lab
Publisher:
Society of Petroleum Engineers (SPE)
Journal:
SPE Reservoir Simulation Symposium
Conference/Event name:
SPE Reservoir Simulation Symposium
Issue Date:
2013
DOI:
10.2118/163621-ms
Type:
Conference Paper
ISBN:
9781627480246
Appears in Collections:
Conference Papers; Environmental Science and Engineering Program; Environmental Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Physical Sciences and Engineering (PSE) Division; Earth Science and Engineering Program; Earth Science and Engineering Program; Computational Transport Phenomena Lab; Computational Transport Phenomena Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBao, Kaien
dc.contributor.authorYan, Mien
dc.contributor.authorLu, Ligangen
dc.contributor.authorAllen, Rebeccaen
dc.contributor.authorSalam, Amgaden
dc.contributor.authorJordan, Kirk E.en
dc.contributor.authorSun, Shuyuen
dc.date.accessioned2015-08-24T09:25:35Zen
dc.date.available2015-08-24T09:25:35Zen
dc.date.issued2013en
dc.identifier.isbn9781627480246en
dc.identifier.doi10.2118/163621-msen
dc.identifier.urihttp://hdl.handle.net/10754/575765en
dc.description.abstractThe present work describes a parallel computational framework for CO2 sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel HPC systems. In this framework, a parallel reservoir simulator, Reservoir Simulation Toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, while the molecular dynamics simulations are performed to provide the required physical parameters. Numerous technologies from different fields are employed to make this novel coupled system work efficiently. One of the major applications of the framework is the modeling of large scale CO2 sequestration for long-term storage in the subsurface geological formations, such as depleted reservoirs and deep saline aquifers, which has been proposed as one of the most attractive and practical solutions to reduce the CO2 emission problem to address the global-warming threat. To effectively solve such problems, fine grids and accurate prediction of the properties of fluid mixtures are essential for accuracy. In this work, the CO2 sequestration is presented as our first example to couple the reservoir simulation and molecular dynamics, while the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical process in the future. Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability are observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well demonstrated with several experiments with hundreds of millions to a billion cells. To our best knowledge, the work represents the first attempt to couple the reservoir simulation and molecular simulation for large scale modeling. Due to the complexity of the subsurface systems, fluid thermodynamic properties over a broad range of temperature, pressure and composition under different geological conditions are required, for which the experimental results are limited. Although equations of state can reproduce the existing experimental data within certain ranges of conditions, their extrapolation out of the experimental data range is still limited. The presented framework will definitely provide better flexibility and predictability compared with conventional methods.en
dc.publisherSociety of Petroleum Engineers (SPE)en
dc.titleHigh-performance modeling of CO2 sequestration by coupling reservoir simulation and molecular dynamicsen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
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.identifier.journalSPE Reservoir Simulation Symposiumen
dc.conference.date18-20 Februaryen
dc.conference.nameSPE Reservoir Simulation Symposiumen
dc.conference.locationThe Woodlands, Texas, USAen
dc.contributor.institutionIBM, Saudi Arabiaen
kaust.authorBao, Kaien
kaust.authorAllen, Rebeccaen
kaust.authorSun, Shuyuen
kaust.authorSalam, Amgaden
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