Abstract
Corrosion growth analysis is a vital part of the integrity and risk assessment of corroded pipelines. The results are used to schedule pipeline inspections and maintenance actions. Corrosion growth is often determined from noisy in-line inspection results where the sizing errors can have a significant impact on the measured size and growth of the corrosion features. If the inspection results are on average unbiased, the top percentiles of measured features have a statistical trend of being oversized as shown in the paper. This trend has been confirmed in pipeline practice. The statistical bias effect leads to suboptimal inspection and maintenance requirements if it is not removed in the corrosion growth analysis. Three deterministic and probabilistic models, which account for the sizing bias inherent in in-line inspection data, are introduced for the corrosion growth analysis. The models are tailored toward pipelines subject to internal corrosion with high feature densities. A numerical example is provided based on a subsea pipeline to demonstrate the ramifications of the oversizing bias and the proposed corrosion growth models.
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