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Application and Validation of Statistically Based Corrosion Growth Rates

[+] Author Affiliations
Clifford J. Maier, Steven J. Polasik, Thomas A. Bubenik

Det Norske Veritas (USA), Inc., Dublin, OH

Pamela J. Moreno

Det Norske Veritas (USA), Inc., Katy, TX

William V. Harper, David J. Stucki

Otterbein University, Westerville, OH

David A. R. Shanks, Neil A. Bates

Det Norske Veritas (Canada) Ltd., Calgary, AB, Canada

Paper No. IPC2012-90424, pp. 167-173; 7 pages
  • 2012 9th International Pipeline Conference
  • Volume 2: Pipeline Integrity Management
  • Calgary, Alberta, Canada, September 24–28, 2012
  • Conference Sponsors: International Petroleum Technology Institute, Pipeline Division
  • ISBN: 978-0-7918-4513-4
  • Copyright © 2012 by ASME


When it comes to managing the integrity of corroded pipelines, operators are confronted with many difficult decisions — one of which is the level of conservatism that is used in pipeline integrity assessments. The financial implications associated with excavation, repair, rehabilitation, and inspection programs typically balance the level of conservatism that is adopted. More conservative approaches translate into more spending, so it is important that repair strategies developed based on the integrity assessment results are effective.

As integrity assessment methodologies continue to evolve, so does the ability to account for local conditions. One development in recent years has been the ability to evaluate multiple MFL in-line inspections to determine areas of active corrosion growth, through the combined use of statistics, inspection signal comparisons, and engineering analysis. The authors have previously outlined one approach (commonly known as Statistically Active Corrosion (SAC)) that has been successfully used to identify areas of probable corrosion growth, predict local corrosion growth rates, and maximize the effectiveness of integrity assessments.[1]

Validation of the SAC-predicted corrosion growth rates is important for establishing confidence in the process. This is achieved through inspection signal comparisons, integrating close interval survey (CIS) results, and (when possible) field verification. The means by which these methods are used for validating the SAC method are described in this paper.

Copyright © 2012 by ASME
Topics: Corrosion



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