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dc.contributor.advisorElfar Adalsteinsson and Brian Boling.en_US
dc.contributor.authorMaison, Julie Laure Ken_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2011-10-17T21:26:34Z
dc.date.available2011-10-17T21:26:34Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/66443
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 41).en_US
dc.description.abstractThe RF signals received from Nuclear Magnetic Resonance (NMR) measurements in logging while drilling NMR instruments are often of the same amplitude as the noise generated by the instruments. Designers of these devices are thus usually faced with the challenging task of improving the sensitivity of the measurement process either by reducing the noise generated by the system or by boosting the signal relative to the electrical noise. For NMR equipment used in earth formation evaluation, this is rendered more difficult by the measurement geometry and noise of the samples under consideration. Schlumberger's proVISION logging-while-drilling tool is one such NMR device. It makes use of the technique of NMR to evaluate the porosity of the earth's rock formations. Although the tool boosts the signal-to-noise ratio (SNR) to a level sufficient for productivity analysis, SNR improvement is a continuing goal to improve signal quality and provide better results to help optimize the drilling process. The objective of this thesis is to model the electrical noise in the detection path of the NMR signal of the proVISION tool. Intrinsic and extrinsic noise sources contributing to the overall electrical noise in the acquisition path prior to digital processing of the detected signal are accounted for by this model. The results of this analysis provide the necessary data for further SNR improvements in the system.en_US
dc.description.statementofresponsibilityby Julie Laure K. Maison.en_US
dc.format.extent41 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleElectrical noise model for detection circuitry of an NMR-based formation evaluation Toolen_US
dc.title.alternativeElectrical noise model for detection circuitry of an Nuclear Magnetic Resonance-based formation evaluation Toolen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc755719315en_US


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