Carbon steel corrosion is a commonly encountered issue in pipelines transporting hydrocarbons containing corrosive agents such as CO2, H2S and water. As a result, several corrosion prediction models have been put forward over the years although no standard model exists for corrosion prediction in the industry. Two of such models are the Norsok model for predicting sweet generalized corrosion and the Papavinasam model for predicting localised corrosion which are both insufficient to accurately predict CO2 corrosion due to their underlying operational limitations.
In this project, both of the above-mentioned models have been modified and improved so as to reduce the model limitations. The Norsok model is improved by accounting for 3 phase flow in calculating the wall shear stress and introduction of correction factors owing to oil wetting and formation of protective layers in steel pipes during transportation of hydrocarbon. The Papavinasam model was improved by using the Weibull distribution to account for time effect in corrosion predictions.
The corrosion rates at different operating conditions have been predicted using the improved models for both sweet and sour flow streams, validated against available field data and analysed with errors of <15% realized. Parametric studies were also carried out using the modified models thus indicating that temperature, pressure and pH affect the corrosion rate the most.
The predicted corrosion rates obtained from this improved models fairly agreed with the measured field values available for validation purposes. The improved models are user-friendly and readily available and are thus applicable for use in the oil and gas industry for corrosion studies and mitigation.
