Investigating the performance of transient model based leak detection system for liquid pipelines

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Canada's pipeline network is massive with approximately 3 million barrels of crude oil transported every day. Even with extensive federal and provincial regulation, and pipeline companies undertaking many measures to maintain and monitor their pipelines to ensure safe operations, there is always a possibility that a pipeline leak could occur. Oil pipeline leaks can result in significant environmental impacts and huge economic losses, which highlights the need for effective leak detection to facilitate fast response to a leak event. The occurrence of a leak causes a transient event, in the form of pressure waves that propagate in both directions along the pipe. The presence of a leak can be detected by analyzing the hydraulic behaviour of the pipeline system using a computer model. Computer model based leak detection techniques are extensively used in the energy pipeline industry but their effectiveness is often limited by the ability of the computer models to accurately reproduce the complexities of real-world pipeline systems, and by inaccurate and insufficient measured data. Enbridge Pipelines Inc. uses computer model based leak detection systems on almost all of their liquid pipelines. One current challenge with model based leak detection systems is that they do not perform as well under transient conditions, as they do under normal operating conditions. A second concern is that installing additional pipeline instrumentation may not improve leak detectability as expected. The goal of this research project is to investigate specific challenges related to computer model based leak detection systems. We propose to conduct extensive diagnostic testing of the commercial software upon which Enbridge's leak detection systems are built, to determine the factors that have the most impact on leak detection. In addition, we will investigate the sensitivity of leak detectability to field measurements. We also propose to develop a leak detection model which will serve as a "toolbox" to assist with better understanding of the computer model based leak detection method, identify enhancements, and explore new challenges with this type of system.