Pitting growth modelling in buried oil and gas pipelines using statistical techniques
Keywords:Pitting corrosion, Nonlinear regression, Monte Carlo simulations, Markov chains
New deterministic and stochastic predictive models are proposed for external pitting corrosion in underground pipelines. The deterministic model takes into consideration the local chemical and physical properties of the soil as well as the pipeline coating to predict the time dependence of pitting depth and rate in a range of soils. This model, based on results from a field study, was used to conduct Monte Carlo simulations that established the probability distribution of pitting depth and growth rate in the studied soils and their evolution over the life of the pipeline. In the last stage of the study, an empirical Markov chain-based stochastic model was developed for predicting the evolution of pitting corrosion depth and rate distributions from the observed properties of the soil.
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