Pipeline operators around the world use in-line inspections and corrosion control systems to manage the integrity of their systems. Determining when to inspect is a critical consideration, which depends in part on whether corrosion growth takes place between inspections. Remaining life estimates based on estimated corrosion growth rates typically form the basis for reassessment intervals.

Remaining life assessments often use assumptions about corrosion rates that, while conservative, can lead to unrealistic results. Excess conservatism leads to short reassessment intervals and unnecessary mitigation. This paper discusses how data analyses can be used to identify and verify areas where corrosion is actually taking place. By identifying and addressing these areas, operators can minimize unnecessary mitigation in low growth areas, ensure high growth areas are mitigated in a timely manner, and extend overall reassessment intervals.

This paper discusses an integrated approach to identifying corrosion activity using a combination of statistics, inspection signal comparisons, and engineering analyses. The approach relies on a full understanding of the mechanisms that cause corrosion and its growth. Pipeline operators can use this approach to calculate remaining life, prioritize repairs and mitigation, and extend reassessment intervals. This process is collectively known as Statistically Active Corrosion (SAC) 1,2,3.

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