Application of corrosion rate prediction software in sour gas gathering and transportation pipeline

Aiming at the material corrosion in gathering and transportation system in sour gas fields, this article analyzed contrastively several classical and widely used corrosion rate prediction models. Essential factors such as partial pressure of CO₂, partial pressure of H₂S, liquid flow rate, temperature have been taken in consideration to develop a semi-empirical prediction model for corrosion rate. The undetermined coefficients in the model are determined by the experimental data. Based on this corrosion prediction model, a prediction software has been developed by back propagation(BP) neural-network algorithm. The software is utilized to predict corrosion rate of the pipeline material in a certain gas field in Sichuan/Chongqing area. The prediction result compared with coupon test result under the same parameter condition, the prediction accuracy of software is higher than 90%, which means it has a good application effect.