Markov chain model for predicting pitting corrosion damage in offshore pipeline

Abstract

Pitting is a type of corrosion which the growth prediction is governed by the uncertainties that can cause inaccuracy in the outcome. This paper studies the fitness of Markov Chain model in representing the pitting growth behaviour. This work focuses on the prediction of pitting corrosion damage in offshore pipeline based on Markov Chain model. Data of pitting corrosion was obtained from repeated In-line Inspection (ILI) survey. Historical data of corrosion pit was projected and compared with actual data from later inspection. Based on the results, Markov Chain model has over predicted the growth of corrosion pit with larger dispersion. The predicted distribution of corrosion pit is highly governed by extreme data as compared to distribution of actual data. The discrepancies in prediction result are due to the assumption made on the exponential factor of power law model whereby the factor was set to v = 1 so that the corrosion progress can behaves linearly. Regardless the inaccuracy of prediction, the Markov Chain model is found promising in predicting corrosion progress in pipelines. If more information in regards to environment and pipeline operation can be made available, the overall projection can be improved. © 2014 Asian Network for Scientific Information.