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Deterministic QRA Model and Implementation Experience via an Integrity Management Software Tool

[+] Author Affiliations
Jane Dawson, Inessa Yablonskikh

PII Pipeline Solutions, Cramlington, Northumberland, UK

Iain Colquhoun

PII Pipeline Solutions, Calgary, AB, Canada

Russell Wenz, Tuan Nguyen

PII Pipeline Solutions, Kansas City, KS

Paper No. IPC2010-31236, pp. 457-468; 12 pages
doi:10.1115/IPC2010-31236
From:
  • 2010 8th International Pipeline Conference
  • 2010 8th International Pipeline Conference, Volume 4
  • Calgary, Alberta, Canada, September 27–October 1, 2010
  • Conference Sponsors: International Petroleum Technology Institute and the Pipeline Division
  • ISBN: 978-0-7918-4423-6 | eISBN: 978-0-7918-3885-3
  • Copyright © 2010 by ASME

abstract

Current risk assessment practice in pipeline integrity management tends to use semi-quantitative index-based or model-based methodologies. This approach has been found to be very flexible and provide useful results for identifying high-risk areas and for prioritizing physical integrity assessments. However, as pipeline operators progressively adopt an operating strategy of continual risk reduction with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels is becoming evident. Whereas reliability-based quantitative risk assessments can be and are routinely carried out on a site-specific basis, they require significant amounts of quantitative data for the results to be meaningful. This need for detailed and reliable data tends to make these methods unwieldy for system-wide risk assessment applications. This paper describes methods for estimating risk quantitatively through the calibration of semi-quantitative estimates to failure rates for peer pipeline systems. By applying point value probabilities to the failure rates, deterministic quantitative risk assessment (QRA) provide greater rigor and objectivity than can usually be achieved through the implementation of semi-quantitative risk assessment results. The method permits a fully quantitative approach to suit the operator’s data availability and quality, and analysis needs. The paper also discusses experiences of implementing this type of risk model in Pipeline Integrity Management System (PIMS) software and the use of and integration of data via existing pipeline geographical information systems (GIS).

Copyright © 2010 by ASME

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