A risk-based maintenance decision model for subsea pipeline considering pitting corrosion growth

Abstract

Pitting corrosion growth of subsea pipeline can cause pipeline leak, resulting in the huge economic losses. This study presents a risk-based model to implement the optimal maintenance decision-making of subsea pipelines subject to pitting corrosion. Firstly, a pitting corrosion growth prediction model is built using DeWaard 95 model and dynamic Bayesian network (DBN). Subsequently, the probability of failure, i.e., PoF and consequence of failure, i.e., CoF for pipeline are estimated to obtain the risk profile of corroded pipeline. The maintenance cycle of pipeline is estimated based on total utility function and the acceptable risk. Eventually, a Bayesian influence diagram (BID) model and expected utility theory (EEU) are implemented to determine maintenance decision of corroded pipelines. The methodology is illustrated by a case study, which indicates that it can be a useful tool for maintenance decisions for subsea pipeline subject to pitting corrosion growth.