Well Integrity Mapping Using Hybrid Model Based on Physics of Failure and Data-Driven Methods

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dc.contributor.advisorEhlig-Economides, Christine
dc.contributor.committeeMemberVipulanandan, Cumaraswamy
dc.contributor.committeeMemberSamuel, Robello
dc.creatorDas, Bibek
dc.creator.orcid0000-0002-8252-6860
dc.date.accessioned2019-09-13T18:54:32Z
dc.date.available2019-09-13T18:54:32Z
dc.date.createdMay 2017
dc.date.issued2017-05
dc.date.submittedMay 2017
dc.date.updated2019-09-13T18:54:32Z
dc.description.abstractPresence of H2S in high pressure and high temperature wells with pressures greater than 15,000 psi or temperatures of 350 °F can lead to strength reduction of casing strings and advance the time to failure. Casing strings also get damaged during drilling. The objective of this study is to develop a hybrid model based on Physics of failure and data driven algorithms that can estimate remaining useful life of production casing in high pressure, high temperature, and sour well conditions. A unique degradation modeling and prognostics framework and analysis are presented in this study. A simulation tool is built for the analysis. The production casing grades P-110, Q-125 and V-150 undergo reduction in strength due to wear during drilling, stress and hydrogen induced cracking over a period of ten years. The failure probability of reduced strength of casing changes with time. The remaining useful life is calculated for the depths of interest and time along with 95% confidence intervals. The model can be expanded later to include actual tests or monitored well data.
dc.description.departmentPetroleum Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10657/4514
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectCasing Integrity
dc.subjectHydrogen Induced Crack
dc.subjectCasing Wear
dc.subjectDegradation
dc.subjectPredictive analytics
dc.subjectMachine learning
dc.titleWell Integrity Mapping Using Hybrid Model Based on Physics of Failure and Data-Driven Methods
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentPetroleum Engineering, Department of
thesis.degree.disciplinePetroleum Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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