The Use of Response Surface Methodology to Predict CO2 Corrosion Model Empirically

Recently, empirical models have been used to predict corrosion rate in several CO2 parameters conditions. However, most of the empirical model did not predict the corrosion rate efficiently. Most of those predictions models determined effects of variables by holding constant individual variables values and changing the values of another variable to obtain the regression model. As consequence, the experiments will be larger and costly. In this paper, the use of RSM was proposed to solve those limitations. RSM is a design of experiment that can be used to optimize the experiments and reduce the number of experimental running. The experiments studied effects of temperature, rotation speed, and Acetic Acid (HAc) on CO2 corrosion. Performance of the regression model calculated by the RSM was verified with experiments. The experiments were conducted in saturated solution of CO2 with 3% NaCl solution and various concentrations (0, 70, 170, 270 and 340 ppm) of HAc. Temperature range of 22 to 80oC and rotation speed range from 1000 to 6000 rpm were used in the experiments. All of the experiments were set in pH 4. MINITAB® version 15 was used for data analysis. In conclusion, a quadratic model is a proposal pattern to predict the effects of temperature, HAc and rotation speed in CO2 environments.