Abstract
In order to assess the risk of pipeline failure due to a leak or burst, information about the current state of the pipeline must be combined with a corrosion rate that models how quickly the anomalies grow. Information about the current state of the pipeline can be inferred from inspections and is a critical ingredient in the integrity management decision making process. Inline inspection results are subject to various sources of uncertainty. This paper specifically addresses the effects of sizing uncertainties on integrity decisions. In-line inspection sizing accuracies are currently assumed to be independent of the actual feature size. This paper explores the practical consequences of this assumption through the rules of mathematical statistics. The paper highlights that – due to random sizing errors –the deepest feature call often represents an overestimate of the true feature depth and discusses some of the implications thereof on integrity management decisions such as excavation, repair or replacement. 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. This paper highlights some of the effects of these uncertainties and the resulting biases that occur in the exceedance probability calculations based on these statistical corrosion rate models.
The intent of this paper is to demonstrate the significant consequences when interpreting the largest anomalies in the ILI results under the current sizing error assumptions. It is the intent to bring this to the industry’s attention and foster a constructive discussion about the adequacy of the current practice or the need for more detailed sizing uncertainty models.
