As defined in American Petroleum Institute Recommended Practice 1130 (API RP 1130), CPM system leak detection performance is evaluated on the basis of four distinct but interrelated metrics: sensitivity, reliability, accuracy and robustness. These performance metrics are captured to evaluate performance, manage risk and prioritize mitigation efforts.

Evaluating and quantifying sensitivity performance of a CPM system is paramount to ensure the performance of the CPM system is acceptable based on a company’s risk profile for detecting leaks. Employing API RP 1130 recommended testing methodologies including parameter manipulation techniques, software simulated leak tests and/or removal of test quantities of commodity from the pipeline are excellent approaches to understanding the leak sensitivity metric.

Good reliability (false alarm) performance is critical to ensure that control center operator desensitization does not occur through long term exposure to false alarms. Continuous tracking and analyzing of root causes of leak alarms ensures that the effects of seasonal variations or changes to operation on CPM system performance are managed appropriately. The complexity of quantifying this metric includes qualitatively evaluating the relevance of false alarms.

The interrelated nature of the above performance metrics imposes conflicting requirements and results in inherent trade-offs. Optimizing the trade-off between reliability and sensitivity involves identifying the point that thresholds must be set to obtain a balance of a desired sensitivity and false alarm rate.

This paper presents an approach to illustrate the combined sensitivity/reliability performance for an example pipeline. The paper discusses considerations addressed while determining the methodology such as stakeholder input, ongoing CPM system enhancements, sensitivity/reliability trade-off, risk based capital investment and graphing techniques. The paper also elaborates on a number of identified benefits of the selected overall methodology.

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