Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 41). === The RF signals received from Nuclear Magnetic Resonance (NMR) measurements in logging wh...

Full description

Bibliographic Details
Main Author: Maison, Julie Laure K
Other Authors: Elfar Adalsteinsson and Brian Boling.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/66443
id ndltd-MIT-oai-dspace.mit.edu-1721.1-66443
record_format oai_dc
spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-664432019-05-02T16:36:07Z Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool Electrical noise model for detection circuitry of an Nuclear Magnetic Resonance-based formation evaluation Tool Maison, Julie Laure K Elfar Adalsteinsson and Brian Boling. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 41). The 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. by Julie Laure K. Maison. M.Eng. 2011-10-17T21:26:34Z 2011-10-17T21:26:34Z 2011 2011 Thesis http://hdl.handle.net/1721.1/66443 755719315 eng M.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. http://dspace.mit.edu/handle/1721.1/7582 41 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Electrical Engineering and Computer Science.
spellingShingle Electrical Engineering and Computer Science.
Maison, Julie Laure K
Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 41). === The 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. === by Julie Laure K. Maison. === M.Eng.
author2 Elfar Adalsteinsson and Brian Boling.
author_facet Elfar Adalsteinsson and Brian Boling.
Maison, Julie Laure K
author Maison, Julie Laure K
author_sort Maison, Julie Laure K
title Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
title_short Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
title_full Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
title_fullStr Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
title_full_unstemmed Electrical noise model for detection circuitry of an NMR-based formation evaluation Tool
title_sort electrical noise model for detection circuitry of an nmr-based formation evaluation tool
publisher Massachusetts Institute of Technology
publishDate 2011
url http://hdl.handle.net/1721.1/66443
work_keys_str_mv AT maisonjulielaurek electricalnoisemodelfordetectioncircuitryofannmrbasedformationevaluationtool
AT maisonjulielaurek electricalnoisemodelfordetectioncircuitryofannuclearmagneticresonancebasedformationevaluationtool
_version_ 1719044038818004992