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dc.contributor.authorDouglas, Craig C.
dc.contributor.authorQin, Guan
dc.contributor.authorCollier, Nathan
dc.contributor.authorGong, Bin
dc.date.accessioned2015-05-10T14:30:59Z
dc.date.available2015-05-10T14:30:59Z
dc.date.issued2011-05-22
dc.identifier.citationIntelligent fracture creation for shale gas development 2011, 4:1745 Procedia Computer Science
dc.identifier.issn18770509
dc.identifier.doi10.1016/j.procs.2011.04.189
dc.identifier.urihttp://hdl.handle.net/10754/552550
dc.description.abstractShale gas represents a major fraction of the proven reserves of natural gas in the United States and a collection of other countries. Higher gas prices and the need for cleaner fuels provides motivation for commercializing shale gas deposits even though the cost is substantially higher than traditional gas deposits. Recent advances in horizontal drilling and multistage hydraulic fracturing, which dramatically lower costs of developing shale gas fields, are key to renewed interest in shale gas deposits. Hydraulically induced fractures are quite complex in shale gas reservoirs. Massive, multistage, multiple cluster treatments lead to fractures that interact with existing fractures (whether natural or induced earlier). A dynamic approach to the fracturing process so that the resulting network of reservoirs is known during the drilling and fracturing process is economically enticing. The process needs to be automatic and done in faster than real-time in order to be useful to the drilling crews.
dc.publisherElsevier BV
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S187705091100247X
dc.rightsArchived with thanks to Procedia Computer Science. http://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectsensor-model feedback
dc.subjectdynamic data-driven application system
dc.subjectDDDAS
dc.subjectmultiscale methods
dc.subjectreservoir simulation
dc.titleIntelligent fracture creation for shale gas development
dc.typeConference Paper
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalProcedia Computer Science
dc.conference.date2011-06-01 to 2011-06-03
dc.conference.name11th International Conference on Computational Science, ICCS 2011
dc.conference.locationSingapore, SGP
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionUniversity of Wyoming School of Energy Resources, Laramie, WY 82071, USA
dc.contributor.institutionPeking University Department of Energy and Resource Engineering, Beijing 100871, China
kaust.personCollier, Nathan
refterms.dateFOA2018-06-14T02:27:47Z
dc.date.published-online2011-05-22
dc.date.published-print2011


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