A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems

Yuting Wu, Daniel J. Holland, Mick D. Mantle, Andrew G. Wilson, Sebastian Nowozin, Andrew Blake, Lynn F. Gladden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a Bayesian approach for inferring the chemical composition of liquids in porous media obtained using nuclear magnetic resonance (NMR). The model analyzes NMR data automatically in the time domain, eliminating the operator dependence of a conventional spectroscopy approach. The technique is demonstrated and validated experimentally on both pure liquids and liquids imbibed in porous media systems, which are of significant interest in heterogeneous catalysis research. We discuss the challenges and practical solutions of parameter estimation in both systems. The proposed Bayesian NMR approach is shown to be more accurate and robust than a conventional spectroscopy approach, particularly for signals with a low signal-to-noise ratio (SNR) and a short life time.

Original languageEnglish (US)
Title of host publication2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2515-2519
Number of pages5
ISBN (Electronic)9780992862619
StatePublished - Nov 10 2014
Event22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugal
Duration: Sep 1 2014Sep 5 2014

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Conference

Conference22nd European Signal Processing Conference, EUSIPCO 2014
CountryPortugal
CityLisbon
Period9/1/149/5/14

Keywords

  • Bayesian inference
  • NMR spectroscopy
  • chemical quantification
  • porous media

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Wu, Y., Holland, D. J., Mantle, M. D., Wilson, A. G., Nowozin, S., Blake, A., & Gladden, L. F. (2014). A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems. In 2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014 (pp. 2515-2519). [6952943] (European Signal Processing Conference). European Signal Processing Conference, EUSIPCO.