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In recent years, CO2 corroison in gathering and transportation pipes has been becoming more and more serious as the development of technology of CO2 flooding in oil reservoirs. Economic losses caused by corrosion accounts for arround 6% of the petroleum and chemical industry each year. The main corrosion factors in pipelines are CO2, H2S, SRB bacteria, and salinity etc, of which CO2 is the biggest one, can cause badly corrosion. This paper aimed to predicting the corrosion rate of CO2 by analyzing the mechanism and behavior of CO2 corrosion, intending to privde a reference for the operator to take actions. In this study, a set of experiments were conducted to study the behavior of CO2 corrosion under various factors by modelling the field conditions. Steel A3, the gerenal steel which is used to make tranportaion pipeline, was choosen as the experiment sample. Experiment results show that: (1) temperature affects the corrosion rate obviously, because temperature plays an important role in the formation of corrosion product membrane; (2) corrosion rate rise as the increase of CO2 partial pressure; (3) steel N80 of well pipe has better anti-corrosion performance than steel A3 of tranportation pipeline under the same corrosion condition; (4) the exsiting Cl- accelerates the CO2 corrosion rate to steel A3. In accordance with many experiments and field corrorion data, SDcorr software was developed on the basis of previous models to predict the CO2 corrorion rate. This software has two funcitons, one is for integrated corrorion analysis (ICA), and the other is for CO2 corrosion rate prediction(CCRP).The function ICA consider the mutual influence of many corrosion factors and their total effects on the corrosion rate. It can determine which factor is primary, and then give specific advises . Function CCRP was further developed based on above work and previous models, which can predict the CO2 corrosion for the steel A3 and N80. This model can consider temperature, CO2 partial pressure, pH, flow velocity, roughness of pipe well, and other factors. Compared with other predictive models and experiment results, this model gives a good and reliable predictive result for CO2 corrosion rate.
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