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dc.contributor.authorLønøy, Bjarte
dc.contributor.authorTveranger, Jan
dc.contributor.authorPennos, Christos
dc.contributor.authorWhitaker, Fiona
dc.contributor.authorLauritzen, Stein-Erik
dc.description.abstractInfilled and collapsed cave systems are an important component of many paleokarst reservoirs. Incorporating these features into industrial reservoir models commonly relies on geostatistical modelling methods that often fail to capture key aspects of connectivity, geometry and volume of the paleokarst features realistically. The present work investigates the implementation of realistic cave geometries in geocellular models using survey data from an active karst cave as a starting point. The proposed method utilizes cave survey data to generate a dense equally spaced point-cloud representing the cave system. The point-clouds are used for geometric modelling and subsequent geocellular discretization of the karst system. The volumetric and geometric accuracy of this novel reservoir modelling method is compared to that from two established methods by benchmarking against the cave survey data. Additionally, the interlinkage between grid cell resolution, applied filter cut-off and geocellular rendering are evaluated. This study demonstrates that our proposed novel methodology can provide an excellent geometric and volumetric geocellular rendering of karst systems using cave survey data as input. Employing a combination of cave network maps and forward modelling of collapse and infill may enable model rendering of these features that more closely echoes processes controlling cave and karst breccia formation and geometric characteristics. In turn, this could offer better constraints to forecast paleokarst reservoirs architecture and properties.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.subjectGeocellular renderingen_US
dc.subjectGeocellular renderingen_US
dc.subjectKarst morphologyen_US
dc.subjectKarst morphologyen_US
dc.subjectReservoir modellingen_US
dc.titleGeocellular rendering of cave surveys in paleokarst reservoir modelsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.rights.holderCopyright 2020 The Authors.en_US
dc.source.journalMarine and Petroleum Geologyen_US
dc.relation.projectNorges forskningsråd: 267634en_US
dc.subject.nsiVDP::Geofag: 450en_US
dc.subject.nsiVDP::Geosciences: 450en_US
dc.identifier.citationMarine and Petroleum Geology. 2020, 122, 104652.en_US

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal