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dc.contributor.authorAlmklov, Petter Grytten
dc.contributor.authorØsterlie, Thomas
dc.contributor.authorHaavik, Torgeir K
dc.date.accessioned2017-10-02T06:53:58Z
dc.date.available2017-10-02T06:53:58Z
dc.date.created2012-06-18T10:02:30Z
dc.date.issued2012
dc.identifier.citationJournal of experimental and theoretical artificial intelligence (Print). 2012, 24 (3), 329-350.nb_NO
dc.identifier.issn0952-813X
dc.identifier.urihttp://hdl.handle.net/11250/2457597
dc.description.abstractThis article discusses how data are made to represent subsurface phenomena in petroleum production. Drawing on studies of the subsurface disciplines in an oil company, and the multitude of sensor data employed there, we suggest that sensor data as representational artifacts are punctuated along three axes. We refer to this as spatial, temporal and aspectual punctuation. Whereas, the first two refer to the positioning of data in space and time, the latter refers to the sensors’ response to single aspects of the interaction with a subsurface phenomenon. We show how extrapolation of punctuated data is a crucial element of the work of understanding the subsurface. It is when the punctuated data points are creatively extrapolated along the three axes of punctuation that ideas and models of the subsurface phenomena take shape. Consequently, we argue that the processes of punctuation and extrapolation are the keys to understand how knowledge about the subsurface is created at the onshore office. Punctuation gives mobility whereas extrapolation is necessary to establish reference between the punctuated data and the inaccessible oil reservoir. We specifically discuss the implications this has for reservoir models as representational artifacts.nb_NO
dc.language.isoengnb_NO
dc.publisherTaylor & Francisnb_NO
dc.titlePunctuation and extrapolation: representing a subsurface oil reservoirnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersionnb_NO
dc.source.pagenumber329-350nb_NO
dc.source.volume24nb_NO
dc.source.journalJournal of experimental and theoretical artificial intelligence (Print)nb_NO
dc.source.issue3nb_NO
dc.identifier.doi10.1080/0952813X.2012.695448
dc.identifier.cristin929980
dc.relation.projectNorges forskningsråd: 213115nb_NO
dc.description.localcodeThis is a Manuscript of an article published by Taylor & Francis in Journal of Experimental and Theoretical Artificial Intelligence on 04 Sep 2012, available online: http://www.tandfonline.com/doi/abs/10.1080/0952813X.2012.695448nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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