CONDITION MONITORING ASSET INTEGRITY MANAGAMENT: A DATA-DRIVEN APPROACH
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Date
2021-05
Authors
Altynbekov, Nurdaulet
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
Pipelines are considered as an essential asset within oil and gas industry as it is the
safest way of transporting it. Therefore, it is vital for plants to maintain integrity of their
pipelines. This asset’s weakness is that they are prone to deteriorate due to various factors:
corrosion development, crack growth, etc. To tackle these issues, the real-time condition
monitoring asset integrity management models are of high demand. That type of model will
enable operators to observe the operational risk online and decide on an optimum inspection
period at any time. This paper proposes a methodology where the integrity of pipeline is
dependent on two defects at a time: corrosion depth growth and crack depth aggregation.
One of the defects, corrosion depth, is based on dynamic Bayesian network model, whereas
another defect is associated with estimations in stress corrosion cracking. The mentioned is
employed to estimate probability of failures of the pipeline. The estimated overall
probability of failure started rising at month 77, while increasing until 0.27 in the following
31 months. Further, estimation of the consequence of corrosion based on API RP 581
standards is provided within this study. Incorporating probability of failure along with
consequence of failure, the real time operational risk is estimated. The risk started increasing
abruptly at month 77, and within 2.6 years of period the risk of failure was about $475’000.
Next, the optimal inspection interval is assessed via introducing utility function and
maximum acceptable risk line. The optimum period for performing maintenance operations
was at month 78, after which risk was considerably reduced. The proposed methodology is
manifested through hypothetical data generated within MS Excel software.
Description
Keywords
Type of access: Gated Access, Research Subject Categories::TECHNOLOGY, gas industry, oil industry, pipelines
Citation
"Altynbekov, N. (2021). Condition Monitoring Asset Integrity Managament: A Data-Driven Approach (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstan"