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

管道被认为是运输大量石油和天然气产品的最安全、最经济的方式。 Enbridge管道公司运营着世界上最长的原油和液体运输系统。管道是 容易出现不同类型的缺陷，如疲劳裂纹、腐蚀等。如果没有采取适当的补救措施 如果采用这些缺陷，最终可能导致管道故障，包括泄漏或破裂，这将导致非常 停机时间昂贵，管道内容物泄漏和溢出到环境中。在线检测(ILI) 使用智能清管工具定期执行，以检测缺陷并评估管道健康状况。 疲劳裂纹是指在管道运行过程中，由于压力循环引起的疲劳裂纹扩展。 疲劳裂纹是液体管道的一种主要危害，但人们对其认识不深。 在本项目中，我们计划对管道疲劳裂纹扩展预测进行初步研究 在线检测数据，并建立考虑疲劳裂纹扩展的管道物理模型和综合模型 一条单一的疲劳裂纹。所建议的工具有望实现更高的疲劳裂纹预测精度， 存在较大的裂纹尺寸误差。提出的管道疲劳裂纹扩展预测方法 有助于防止管道泄漏和破裂、减少昂贵的停机时间并避免损坏 对环境的影响。

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.