With the increased acceptance of the use of probabilistic fitness-for-service methods, considerable effort has been dedicated to the estimation of the corrosion rate distribution parameters. The corrosion rate is typically computed from the difference in anomaly size over a specific time interval. The anomaly sizes are measured through either in-line inspection or direct assessment. Sizing accuracies for inline inspection methods are reasonably well established and in many cases the sizing uncertainty is non-negligible. In many approaches that are proposed in the literature the time-averaged corrosion rates are computed without explicitly considering the effect of the sizing uncertainties and as a result considerable interpretation and engineering judgment is required when estimating corrosion rates. This paper highlights some of the effects of the sizing uncertainties and the resulting biases that occur in the subsequent reliability calculations. These assessments are used to determine the most appropriate course of action: repair, replacement, or time of next inspection. The cost for repair or replacement of subsea pipelines is much higher than for onshore pipelines. For subsea applications, it is therefore paramount that the risk calculations, and therefore the corrosion rate estimates, be as accurate as possible. In subsea applications, the opportunity to repair individual defects is often limited due to practical constraints and there is merit in an approach that focuses on entire spools or pipeline segments. The proposed statistical analysis method is ideally suited to this application although the principles behind the analysis apply equally well to onshore lines subject to either internal or external corrosion threats.

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