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dc.contributor.authorWillersrud, Anders
dc.contributor.authorBlanke, Mogens
dc.contributor.authorImsland, Lars Struen
dc.contributor.authorPavlov, Alexey
dc.date.accessioned2015-03-13T23:37:26Z
dc.date.accessioned2015-03-26T14:17:28Z
dc.date.available2015-03-13T23:37:26Z
dc.date.available2015-03-26T14:17:28Z
dc.date.issued2015
dc.identifier.citationJournal of Process Control 2015nb_NO
dc.identifier.issn0959-1524
dc.identifier.urihttp://hdl.handle.net/11250/280278
dc.description- author preprintnb_NO
dc.description.abstractDownhole abnormal incidents during oil and gas drilling cause costly delays, and may also potentially lead to dangerous scenarios. Different incidents will cause changes to different parts of the physics of the process. Estimating the changes in physical parameters, and correlating these with changes expected from various defects, can be used to diagnose faults while in development. This paper shows how estimated friction parameters and flow rates can be used to detect and isolate the type of incident, as well as isolating the position of a defect. Estimates are shown to be subjected to non-Gaussian, $t$-distributed noise, and a dedicated multivariate statistical change detection approach is used that detects and isolates faults by detecting simultaneous changes in estimated parameters and flow rates. The properties of the multivariate diagnosis method are analyzed, and it is shown how detection and false alarm probabilities are assessed and optimized using data-based learning to obtain thresholds for hypothesis testing. Data from a 1400 m horizontal flow loop is used to test the method, and successful diagnosis of the incidents drillstring washout (pipe leakage), lost circulation, gas influx, and drill bit nozzle plugging are demonstrated.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.titleFault diagnosis of downhole drilling incidents using adaptive observers and statistical change detectionnb_NO
dc.typeJournal articlenb_NO
dc.typePeer revieweden_GB
dc.date.updated2015-03-13T23:37:26Z
dc.identifier.doi10.1016/j.jprocont.2014.12.010
dc.identifier.cristin1200688
dc.relation.projectNorges forskningsråd: 223254nb_NO


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