scope:

Smart pigs are used extensively as part of integrity management plans for oil and gas pipelines to detect metal loss defects, with magnetic flux leakage (MFL) technology being the most-widely used.

The MFL signal gives an inferred defect size, not a direct measurement-when the signal is translated into a defect size, it has associated sizing tolerances and confidence levels.

The complexity of signal analysis means that these sizing tolerances and confidence levels are difficult to determine and apply in practice. They have a major effect when assessing the significance of the defect, and when calculating corrosion growth rates from the results of multiple inspections over time.

This paper describes how sizing algorithms are constructed and how the quoted tolerances are derived. Probability theory can be used to estimate the likelihood that a defect is smaller or deeper than the reported value.

Finally, the effect of defect sizing tolerances and their confidence levels on corrosion growth projections is illustrated, and how they must be taken into account in any defect assessment is emphasised.