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Application of In-Line Inspection and Failure Data to Reduce Subjectivity of Risk Model Scores for Uninspected Pipelines

[+] Author Affiliations
Yannick Beauregard

NOVA Chemicals, Calgary, AB, Canada

Aaron Woo, Terry Huang

TransCanada Pipelines, Calgary, AB, Canada

Paper No. IPC2018-78735, pp. V002T07A028; 6 pages
doi:10.1115/IPC2018-78735
From:
  • 2018 12th International Pipeline Conference
  • Volume 2: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain Based Design; Risk and Reliability; Northern Offshore and Production Pipelines
  • Calgary, Alberta, Canada, September 24–28, 2018
  • Conference Sponsors: Pipeline Division
  • ISBN: 978-0-7918-5187-6
  • Copyright © 2018 by ASME

abstract

Pipeline risk models are used to prioritize integrity assessments and mitigative actions to achieve acceptable levels of risk. Some of these models rely on scores associated with parameters known or thought to contribute to a particular threat. For pipelines without in-line inspection (ILI) or direct assessment data, scores are often estimated by subject matter experts and as a result, are highly subjective. This paper describes a methodology for reducing the subjectivity of risk model scores by quantitatively deriving the scores based on ILI and failure data.

This method is applied to determine pipeline coating and soil interaction scores in an external corrosion likelihood model for uninspected pipelines. Insights are drawn from the new scores as well as from a comparison with scores developed by subject matter experts.

Copyright © 2018 by ASME

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