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dc.contributor.authorJinasena, Asanthi
dc.contributor.authorSharma, Roshan
dc.date.accessioned2022-05-10T07:20:02Z
dc.date.available2022-05-10T07:20:02Z
dc.date.created2020-08-10T09:00:44Z
dc.date.issued2020
dc.identifier.citationModeling, Identification and Control. 2020, 41 (2), 79-90.en_US
dc.identifier.issn0332-7353
dc.identifier.urihttps://hdl.handle.net/11250/2994928
dc.description.abstractReal-time estimation of the return drilling fluid during oil well drilling is investigated in this study. Online fluid level measurements from a Venturi channel which can be placed on the return flowline is used with a model-based estimator. A reduced order, 1-D, mathematical equation is used for the open flow in the Venturi channel for Newtonian or non-Newtonian fluid types. The volumetric fluid flow rate is estimated using a moving horizon estimator in real-time. The friction factor is also estimated together with the fluid flow rate. The effect of the variation of the channel slope on the flow rate estimation induced by the vibration of the channel during its operation is also studied. The method requires only two level measurements in the Venturi channel together with the channel geometry. The method is validated using a laboratory scale Venturi flow system. The proposed method shows promising potential to be used as a real-time return flow rate measurement in conventional drilling systems.en_US
dc.description.abstractAdaptive Moving Horizon Estimator for Return Flow Rate Estimation using Fluid Levels of a Venturi Channelen_US
dc.language.isoengen_US
dc.publisherNorwegian Society of Automatic Controlen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAdaptive Moving Horizon Estimator for Return Flow Rate Estimation using Fluid Levels of a Venturi Channelen_US
dc.title.alternativeAdaptive Moving Horizon Estimator for Return Flow Rate Estimation using Fluid Levels of a Venturi Channelen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber79-90en_US
dc.source.volume41en_US
dc.source.journalModeling, Identification and Controlen_US
dc.source.issue2en_US
dc.identifier.doi10.4173/MIC.2020.2.4
dc.identifier.cristin1822309
dc.relation.projectNorges forskningsråd: 255348en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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