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Development of a Risk Ranking Tool Based on Quantitative Methods

[+] Author Affiliations
Ray Hicks, Clive Ward

Advantica Ltd., Loughborough, Leicestershire, UK

Paper No. IPC2004-0549, pp. 2577-2586; 10 pages
  • 2004 International Pipeline Conference
  • 2004 International Pipeline Conference, Volumes 1, 2, and 3
  • Calgary, Alberta, Canada, October 4–8, 2004
  • Conference Sponsors: International Petroleum Technology Institute
  • ISBN: 0-7918-4176-6 | eISBN: 0-7918-3737-8
  • Copyright © 2004 by ASME


US pipeline integrity management regulations require operators to rank the risks caused by their operations. Many operators use qualitative methods for this risk ranking process. Such methods have several benefits including simplicity and flexibility. Unfortunately, they rely heavily on engineering judgment and produce results that are very specific to the pipeline system(s) being ranked. This makes it extremely difficult to relate the outputs from different systems or companies within an organization. This paper describes the development and application of a risk ranking approach that requires less judgment and provides the user with an estimate of the true risk of operating the pipeline. Quantitative methods, based on an understanding of structural mechanics, are applied to seven of the nine threat categories listed in ASME B31.8S in order to determine the pipeline’s reliability. An assessment of risk to life is achieved by combining the output from structural mechanics models with a quantitative consequence of failure model. The software operates on a GIS platform, making it easier to demonstrate compliance with the integrity data management requirements that are now part of the relevant federal codes. Results produced from the quantitative approach have been compared to those generated by qualitative methods, in a case study. This illustrates some important differences between the two and show that a more rigorous, quantitative approach can provide the operator with significant benefits including the ability to generate meaningful results with less data. In particular, quantitative methods have the potential to allow operators to move towards a more performance-based approach to their ongoing integrity management processes.

Copyright © 2004 by ASME



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