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In the study presented the CO2 corrosion penetration rate for crude oil transportation processes by pipeline, made of carbon steel, has been a major problem in many of oil and gas fields for years. Many parameters have been known to be effective for corrosion control especially in the pipeline transportation process, these parameters are pH, temperature, pressure and shear stress. The methods are used to determine the optimal parameters with obtaining the optimal value of CO2 corrosion penetration rate. This study is aimed to review of some of the previous studies that are deal with the problem of pipeline corrosion penetration rate that are taking place when transporting the oil and gas, to investigate the effect of the oil and gas transportation processes variables on the pipeline corrosion penetration rate, to develop a suitable mathematical modeling technique to model the effect of crude oil transportation processes variables and to determine the optimal values of the transportation processes variables. The response surface methodology (RSM) is utilized to mathematically model the corrosion penetration rate that takes place during crude oil transportation process by pipeline. More accurate techniques such as fuzzy logic ( FL) was developed using Matlab (2016) Toolbox that is used to predict corrosion penetration rate that is affected by the operation process parameters. Fuzzy logic model has reduced the errors by 0.1482mm/y, which means, using fuzzy logic model to predict the material corrosion penetration rate is sufficiently accurate. The optimal values from numerically calculated CPR using the fuzzy logic model with the formula by using RootSum Square (RSS), were found that CPR value is2.16 mm/y, the temperature is 44.4 ͦ C, pressure is 34.28 Pa, pH is 5.51 and shear stress is 1bar.

Modelling and Optimization of Corrosion Penetration Rate (CPR) for Crude Oil Transportation Processes by Pipeline