Preliminary Study of Pipeline Fatigue Crack Growth Prediction Utilizing Inline Inspection Data

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Pipelines are known as the safest and most economical way to transport large quantities of oil and gas products. Enbridge Pipelines Inc. operates the world's longest crude oil and liquids transportation system. Pipelines are subject to different types of defects, such as fatigue crack, corrosion, etc. If proper remediation actions are not taken, these defects can eventually result in pipeline failures including leaks or ruptures, which lead to very expensive downtime, and leakage and spillage of pipeline contents to the environment. Inline inspections (ILI) are performed periodically using smart pigging tools, to detect defects and evaluate pipeline health conditions. Fatigue cracking refers to crack growth due to fatigue caused by pressure cycling during pipeline operations. Fatigue cracking is a key hazard for liquid pipelines, which has not been well understood. In this project, we plan to perform a preliminary study of pipeline fatigue crack growth prediction utilizing inline inspection data, and develop pipe physical models and integrated fatigue crack growth model considering a single fatigue crack. The proposed tools are expected to achieve improved fatigue crack prediction accuracy, with the presence of large crack sizing error. The proposed pipeline fatigue crack growth prediction methods can contribute to preventing pipeline leaks and ruptures, reducing expensive downtime, and avoiding damage to the environment.