On the Influence of Pipeline Inspection Uncertainties on the POF 100 Metal Loss Anomaly Classification

In-line pipeline inspection is a very important procedure for integrity management. Performed by different inspection tools, such as Magnetic Flux Leakage (MFL) pigs, the monitoring of pipe wall thickness degradation is fundamental for ensuring safe and uninterrupted operations. The quality of inspection results can be ensured through data conditioning and analysis according to international standards, such as the widely used standard practice 100 from Pipeline Operators Forum (POF 100). This standard aims to provide specifications and requirements for in-line inspection of pipelines. Among several contributions, the POF 100 establishes a classification system for metal loss anomalies based on pipeline wall thickness and on defect dimensions. This classification is presented in most inspection reports. Nonetheless, the meaning and the practical usage of this information is somewhat unclear, mainly when inspection uncertainties are considered. Each measured dimension of an identified anomaly is subject to these uncertainties, which can jeopardize the accuracy of metal loss classification. Thus, the influence of uncertainties should not be neglected. This study aims to analyze the influence of inspection uncertainties on the assertiveness of the POF 100 metal loss anomaly classification.