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Title: A practical approach in pipeline corrosion modelling: Part 2 – Short-term integrity forecasting
Downloadable: Yes 
Project No.:
Research Agency:
Catalog No.: 2162s
Date of Publication: Jun 1 2009 12:00AM
Price: $25.00 US
Authors: Dr Érika S M Nicoletti*, Ricardo Dias de Souza, and Dr Sérgio da Cunha Barros
Abstract: THE PIPELINE industry is continuously being required to meet the expectations of its many stakeholders, driven by the market’s rising energy demands, and the requirements for increased profitability, operational safety, and environmentally-friendly procedures. Consequently, more-sophisticated fitness-for-purpose analyses are required in order to achieve maintenance cost reductions while keeping or improving the system’s overall reliability. In such a complex context, limit-state approaches are best fitted to achieving successful outcomes for those wide-ranging but conflicting expectations. Indeed, cutting-edge pipeline defect-assessment codes have embraced this philosophy, but none have included clear and concise guidance on the subjects of forecasting corrosion growth and estimating in-line inspection (ILI) tool measurement error.

The current work has been undertaken aiming to provide a set of guidelines on modelling and analysis procedures for corrosion metal-loss growth on ageing pipelines, using as its input corrosion-monitoring and inspection data. In the preliminary stage, ILI results and electrical-resistance probe (ERP) readings from several oil pipelines were evaluated in order to define the typical variances in pipeline corrosion. This investigative work gave rise to the development of a predictable relationship between the growth rate and its standard deviation, and a short-term forecasting model has been developed based on the premise of a steady metal-loss rate coefficient of variation. In this paper, the mathematical framework for this is detailed based on different configurations of the input data: single and multiple ILI, with or without the addition of ERP results. Additionally, two case studies are given which illustrate the model’s application and results. The model is easily implemented using commercially-available mathematical spreadsheets, and the entire procedure demands little skilled work. The results are highly reproducible, with their overall quality relying mostly on the consistency of the input data.


1. S.A.Timashev and A.V.Bushinskaya, 2009. Diligent statistical analysis of ILI data: implications, inferences and lessons learned. The Pipeline Pigging and Integrity Management Conference, Houston.
2. R.G.Mora et al., 2009. Dealing with uncertainty in pipeline integrity and rehabilitation. The Pipeline Pigging and Integrity Management Conference, Houston.
3. R.Bea et al., 2003. Reliability based fitness-for-service assessment of corrosion defects using different burst pressure predictors and different inspection techniques. 22nd International Conference on Onshore Mechanics and Arctic Engineering, June 8-13, Cancun.
4. J.M.Race, S.J.Dawson, L.Stanley, and S.Kariyawasam, 2006. Predicting corrosion rates for onshore oil and gas pipelines. International Pipeline Conference, Calgary.
5. Ahammed, 1998. Probabilistic estimation of remaining life of a pipeline in the presence of active corrosion defects. Int.J.Pressure Vessels and Piping, 75, pp 321-329.
6. A.Valor a, F.Caleyo, L.Alfonso, D.Rivas, and J.M.Hallen, 2007. Stochastic modeling of pitting corrosion: a new model for initiation and growth of multiple corrosion pits. Corrosion Science, 49, pp 559–579.
7. A.Ainouche, 2006. Future integrity management strategy of a gas pipeline using Bayesian risk analysis. 23rd World Gas Conference, Amsterdam.
8. P.J.Laycock and P.A.Scarf, 1989. Exceedances, extremes, extrapolation and order statistics for pits, pitting and other localized corrosion phenomena. Corrosion Science, 35, 1-4, pp 135-145, 193.
9. J.L.Alamilla and E.Sosa, 2008. Stochastic modelling of corrosion damage propagation in active sites from field inspection data. Corrosion Science, 50, pp 1811–1819.
10. J.L.Alamilla, D.De Leon, and O.Flores, 2005. Reliability based integrity assessment of steel pipelines under corrosion. Corrosion Engineering, Science and Technology, 40, 1.
11. S.A.Timashev, 2003. Updating pipeline remaining life through in-line inspection. International Pipeline Pigging Conference, Houston.
12. S.A.Timashev et al., 2008. Markov description of corrosion defect growth and its application to reliability based inspection and maintenance of pipelines. 7th International Pipeline Conference, Calgary.
13. G.Desjardins, 2002. Optimized pipeline repair and inspection planning using in-line inspection data. Pipeline Pigging, Integrity Assessment & Repair Conference, Houston.
14. B.Gu, R.Kania, S.Sharma, and M.Gao, 2002. Approach to assessment of corrosion growth in pipelines. 4th International Pipeline Conference, Calgary.
15. G.Desjardins, 2001. Predicting corrosion rates and future corrosion severity from in-line inspection data. Materials Performance, August, 40, 8.
16. J.Race et al., 2007. Development of a predictive model for pipeline external corrosion rates. Journal of Pipeline Engineering, 1st Quarter, pp15-29.
17. ASME B 31G: Manual for determining the remaining strength of corroded pipelines.
18. H.Plummer and J.Race, 2003. Determining pipeline corrosion growth rates. Corrosion Management, April.
19. F.Caleyo et al., 2002. A study on the reliability assessment methodology for pipelines with active corrosion defects. Int.J.of Pressure Vessels and Piping, 79, pp77-86.
20. G.Pognonec, 2008. Predictive assessment of external corrosion on transmission pipelines. IPC.
21. R.L.Burden and J.D.Faires, 1993. Numerical Analysis, 5th Ed., PWS Publishers.

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