Prediction of CO2 corrosion growth in submarine pipelines

Abstract

The paper presents a probabilistic-based methodology for the assessment of a pipeline containing internal corrosion defects. Two different models have been used to predict the future CO2 corrosion rates namely a linear growth and the deWaard-Milliams models. A probabilistic approach is used to analyse the behaviour of corrosion data obtained from in-line intelligent (ILI) pigging inspections. The outcomes are parameters represented by their corresponding statistical distribution. Due to the availability of these statistical parameters, a Monte Carlo simulation is used to calculate the probability of failure of the pipeline due to bursting failure. The existence of corrosion may reduce the maximum capacity of the pipe, as such causing leakage and bursting when the operational pressure supersedes its threshold. From the analysis of the result, failure probability based on theoretical linear growth model exhibit slightly longer lifetime of the pipeline with three years interval compared to deWaard-Milliams model. This is due to higher mean value of corrosion growth rate estimated using the empirical deWaard-Milliams model. Both results are very useful in prolonging the lifetime of pipelines by having knowledge of the past to schedule the future maintenance work.