Magnetic flux leakage data analysis for oil and gas pipeline integrity management
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Peng, Xiang
issued: 2021-05-14T21:22:14Z
issued: 2021
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Corrosion is a significant cause of oil and gas pipeline failures. In the pipeline industry, in-line inspection (ILI) using magnetic flux leakage (MFL) technique is conducted periodically to detect and assess pipeline corrosion. The ILI data is a critical input of the pipeline integrity management (PIM) program, where the decision on the pipeline integrity maintenance is made. This thesis research aims to facilitate the decision-making process in the PIM program from the perspective of MFL data analysis. First, the concept of parameterization is put forward to obtain a contextual representation of the corrosion defect. In the PIM program, this high-level representation can help structural engineers to retrieve similar corrosion defects that could pose serious threats to the pipeline integrity. Three parameterization models, i.e., principal component analysis, convolutional auto-encoder, and shape context, are proposed to achieve the contextual defect representation. Then, a computational framework is proposed to automatically match the multiple inspection results from different tools, i.e., axial MFL and circumferential MFL. Due to their complementary detection capabilities, the matched multi-modal MFL data can be further integrated to obtain more comprehensive defect assessment. The proposed framework employs a sliding window searching approach and a Gaussian mixture model to align the coordinate systems of two data sets. In the aligned coordinate system, an accurate matching is achieved with a modified density-based spatial clustering of applications with noise algorithm, which considers both the location and the size information of the corrosion defect. Last but not least, the detection performance of MFL inspection is assessed quantitatively. It aims to figure out which defect can be reliably detected and which may be missed in the MFL inspection. Therefore, even the undetected defects could also be considered in the PIM program. A probability of detection (POD)…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/78354
note: MAGNETIC FLUX LEAKAGE DATA ANALYSISFOR OIL AND GAS PIPELINE INTEGRITYMANAGEMENTbyXiang PengB.Eng., China University of Mining and Technology, 2014M.Sc., Beihang University, 2017A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE COLLEGE OF GRADUATE STUDIES(Electrical Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)May 2021© Xiang Peng, 2021The following individuals certify that they have read, and recommend to the Col-lege of Graduate Studies for acceptance, the thesis/dissertation entitled:MAGNETIC FLUX LEAKAGE DATA ANALYSIS FOR OIL AND GAS PIPELINEINTEGRITY MANAGEMENTsubmitted by Xiang Peng in partial fulfillment of the requirements of the degreeof Doctor of Philosophy.Dr. Zheng Liu, School of Engineering, The University of British ColumbiaSupervisorDr. Kasun Hewage, School of Engineering, The University of British ColumbiaSupervisory Committee MemberDr. Hadi Mohammadi, School of Engineering, The University of British ColumbiaSupervisory Committee MemberDr. Liwei Wang, School of Engineering, The University of British ColumbiaUniversity ExaminerDr. Yiming Deng, College of Engineering, Michigan State UniversityExternal ExamineriiAbstractCorrosion is a significant cause of oil and gas pipeline failures. In the pipelineindustry, in-line inspection (ILI) using magnetic flux leakage (MFL) technique isconducted periodically to detect and assess pipeline corrosion. The ILI data isa critical input of the pipeline integrity management (PIM) program, where thedecision on the pipeline integrity maintenance is made. This thesis research aimsto facilitate the decision-making process in the PIM program from the perspectiveof MFL data analysis.First, the concept of parameterization is put forward to obtain a contextual rep-resentation of the corrosion defect. In the PIM program, this high-level represen-tation can help structural engineers to retrieve similar corrosion defects that couldpose serious threats to the pipel…
has type: Thesis/Dissertation
date issued: 2021-09
is shown at: 10.14288/1.0397495
language: eng
degree discipline: Electrical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Liu, Zheng (Professor of engineering)
type: Text
identifier URI: http://hdl.handle.net/2429/78354