Unique characteristics of individual pipelines come from over a century of evolving design, construction, maintenance, regulation and operation. These characteristics are especially true for legacy, pre-regulated pipelines. Due to the unique nature of the threats present on these assets, there is a need for unique inspection technologies and techniques that can increase pipeline integrity. Reconditioned and repaired pipe utilizing puddle weld repairs is one such threat.
An advanced analysis was completed on a 10-inch, 68-mile light products pipeline. The pipeline was constructed with reconditioned pipe that was estimated to contain tens of thousands of puddle welds. Historical in-line inspection (ILI) data generally underperformed in classifying and discriminating puddle welds versus metal loss features.
The primary objective of this project was to assess the probability of identification (POI) of a multiple dataset ILI tool utilizing multiple magnetic flux leakage (MFL) magnetization directions and residual (RES) magnetization measurements. A secondary objective was to scrutinize data for signs of coincident features. Hydrostatic testing failures showed that puddle welds with porosity and cracking were susceptible to failure and that the identification of these features would be beneficial.
Analysis of historical puddle weld investigations and newly completed multiple dataset ILI data revealed strong identification capabilities in the RES dataset. The high-field magnetizations offered secondary confirmation but often saturated out thermal effects or material differences. The final report included over 40,000 identified puddle welds and five classifications for further investigation. Field investigations for 212 features were completed and the results compared to the ILI data to assess performance. A confusion matrix was created for true positive (TP), true negative (TN), false positive (FP) and false negative (FN) conditions. The smallest TP puddle weld dimension was 0.7″ × 0.7″, and the population had a statistical sensitivity value of 98% (132 TP and 3 FP).
Three additional anomalies denoted as atypical were also investigated. The ILI signatures at these locations were consistent with previous repairs in which puddle welds with cracking were found and repaired. Two of the three features investigated were found to have cracking. Crack propagation was found to be both axial and non-axial in orientation. The results show that puddle welds can be detected and identified with extremely high accuracy. In addition, the preliminary classification results for atypical puddle welds show a high potential for identifying secondary coincident features. This paper details the stages, deliverables and results from an ILI advanced analysis focused on puddle welds.