Extraction of useful signals from noise using advanced time-frequency analysis in Enhanced Oil Recovery

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dc.contributor.advisorLu, Nanshu
dc.contributor.advisorDjurdjanovic, Dragan
dc.creatorKomodromos, Sotiris
dc.date.accessioned2018-03-22T21:47:46Z
dc.date.available2018-03-22T21:47:46Z
dc.date.created2017-08
dc.date.issued2017-08-04
dc.date.submittedAugust 2017
dc.date.updated2018-03-22T21:47:47Z
dc.description.abstractIn Enhanced Oil Recovery (EOR), the injected CO2 does not distribute evenly through ground layers and often is not going to the desired direction. The key issue of this research, was to extract the useful signal from noise for a novel CO2 subsurface imaging solution which uses surfaced based sensors only, in comparison with conventional seismic technology which requires downhole equipment [5, 7, 8, 19, 20]. That could potentially reduce the cost drastically due to its simplicity in installation, performance, less labor intensive and faster process of data. The extremely low signal-to-noise (S/N) ratio required the utilization of binomial time-frequency domains (TFDs) to process the collected field data as the problem involves extremely non-stationary signals. Binomial Cone-Kernel function is arguably the most advanced signal independent kernel; it allowed us to extract useful signals embedded in noise and observe repeatable waves for the first time.
dc.description.departmentEngineering Mechanics
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T25T3GG8Z
dc.identifier.urihttp://hdl.handle.net/2152/63954
dc.language.isoen
dc.subjectTube waves
dc.subjectGuided waves
dc.subjectTime-frequency domains
dc.subjectEnhanced oil recovery
dc.titleExtraction of useful signals from noise using advanced time-frequency analysis in Enhanced Oil Recovery
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentEngineering Mechanics
thesis.degree.disciplineEngineering Mechanics
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Engineering

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