Abstract
Pitting corrosion is a primary and most severe failure mechanism of oil and gas pipelines. To implement a prognostic and health management (PHM) for oil and gas pipelines corroded by internal pitting, an appropriate degradation model is required. An appropriate and highly reliable pitting corrosion degradation assessment model should consider, in addition to epistemic uncertainty, the temporal aspects, the spatial heterogeneity, and inspection errors. It should also take into account the two well-known characteristics of pitting corrosion growing behavior: depth and time dependency of pit growth rate. Analysis of these different levels of uncertainties in the amount of corrosion damage over time should be performed for continuous and failure-free operation of the pipelines. This paper reviews some of the leading probabilistic data-driven prediction models for PHM analysis for oil and gas pipelines corroded by internal pitting. These models categorized as random variable-based and stochastic process-based models are reviewed and the appropriateness of each category is discussed. Since stochastic process-based models are more versatile to predict the behavior of internal pitting corrosion in oil and gas pipelines, the capabilities of the two popular stochastic process-based models, Markov process-based and gamma process-based, are discussed in more detail.
Highlights
Corrosion is the main failure mechanism of oil and gas pipelines
Failure data, provided in the literature, shows that 57.7% of oil and gas pipeline failures in Alberta, Canada between 1980 and 2005 (Papavinasam, 2013) and 15% of all transmission pipeline incidents between 1994 and 2004 in the US were due to internal corrosion (Papavinasam et al, 2006)
This paper defines an appropriate pitting corrosion degradation model for prognostic and health management (PHM) analysis of oil and gas pipelines as a model that considers all of these four levels of uncertainty
Summary
Corrosion is the main failure mechanism of oil and gas pipelines. Of all corrosion mechanisms, pitting corrosion is of most concern in pipelines because of the high rate at which pits can grow (Velázquez, Caleyo, Valor, & Hallen, 2009). This review paper primarily discusses pitting corrosion growth prediction models applicable for PHM of oil and gas pipelines. Two main factors that cause this variability are corrosion films and oil wetting effects modeling approaches As it has been shown in (Nyborg, CO2 corrosion models for oil and gas production systems, 2010), those models that are mostly based on regression analysis and physics-of-failure analysis, cannot depict the inherent uncertainties in the corrosion process even for uniform corrosion. This paper defines an appropriate pitting corrosion degradation model for PHM analysis of oil and gas pipelines as a model that considers all of these four levels of uncertainty. To the best of the authors’ knowledge, there is no comprehensive review paper on pitting corrosion growth models applicable for prognostic and health management of oil and gas pipeline. We evaluated the published models by checking if they can model the above-mentioned characteristics and different uncertainty levels
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
