A Unique Stochastic Model of Markov and Poisson Process for Predicting Pitting Corrosion and Scale Growth in Oil/Gas Production Pipeline
Pitting corrosion and scale deposition are common problems found during the production phase of oil/gas reservoir. The existence of scale or corrosion in production pipeline can lead to production decrease and safety problem. In order to set an effective and efficient preventive action, an accurate prediction model is needed to describe how severe the scale and the corrosion are. This paper provides a method for predicting both pitting corrosion and scale growth in oil/gas pipeline using the combination of Poisson and Markov process. Experimental data using iron plate in white water system were used to confirm and simulate the proposed model to predict pitting corrosion. A field data of waxy oil pipe in unburied and bare system was used to verify the suitability of proposed model for evaluating the scale growth. The results of the model for pitting corrosion and scale growth are then compared with Gumbel Distribution Model results. Both pitting corrosion and scale growth was simulated using different partitions scenario. The best scenario, based on the minimum error, for pitting corrosion is 20 partitions and 50 partitions for scale growth. Moreover, it is said that pitting corrosion and scale growth can be approached using the same stochastic model. Failure time for each case is also predicted using the model.
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