Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/39541
Title: Noise-Produced Patterns in Images Constructed from Magnetic Flux Leakage Data
Authors: Goldobin, D. S.
Pimenova, A. V.
Levesley, J.
Elkington, P.
Bacciarelli, M.
First Published: 22-Jun-2015
Publisher: EDP Sciences, Cambridge University Press (CUP)
Citation: Mathematical Modelling of Natural Phenomena, 2015, 10 (3), pp. 139-148 (10)
Abstract: Magnetic flux leakage measurements help identify the position, size and shape of corrosion-related defects in steel casings used to protect boreholes drilled into oil and gas reservoirs. Images constructed from magnetic flux leakage data contain patterns related to noise inherent in the method. We investigate the patterns and their scaling properties for the case of delta-correlated input noise, and consider the implications for the method’s ability to resolve defects. The analytical evaluation of the noise-produced patterns is made possible by model reduction facilitated by large-scale approximation. With appropriate modification, the approach can be employed to analyze noise-produced patterns in other situations where the data of interest are not measured directly, but are related to the measured data by a complex linear transform involving integrations with respect to spatial coordinates.
DOI Link: 10.1051/mmnp/201510311
ISSN: 0973-5348
eISSN: 1760-6101
Links: http://www.mmnp-journal.org/articles/mmnp/abs/2015/03/mmnp201510p139/mmnp201510p139.html
http://hdl.handle.net/2381/39541
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2015, EDP Sciences, Cambridge University Press (CUP). Deposited with reference to the publisher’s open access archiving policy.
Description: Mathematics Subject Classification: 78A30 / 78M34 / 60G60
Appears in Collections:Published Articles, Dept. of Mathematics

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