A probabilistic assessment methodology for pitting corrosion condition of offshore crude oil pipelines

Abstract

Pitting corrosion is considered as the main degradation form and poses a serious threat on service life of offshore crude oil pipelines. The prediction and assessment of pitting corrosion is challenging due to the uncertainties in pitting corrosion growth. This paper presents a probabilistic methodology based on Bayesian Network (BN) and Hierarchical Bayesian Analysis (HBA) to estimate the pitting corrosion condition of offshore crude oil pipelines. To capture the uncertainties in pitting corrosion growth, Continuous BN model is utilized to simulate the temporal evolution of pitting corrosion depth. HBA is employed to evaluate the time-varying probability of pitting corrosion failure. A case study is implemented to illustrate the methodology. It is observed that the methodology can serve as a useful tool for integrity management of offshore crude oil pipelines subject to pitting corrosion.