A NEW APPROACH IN EMPIRICAL MODELLING OF CO2 CORROSION WITH THE PRESENCE OF HAc AND H2S

• Main Author: PANCA ASMARA, YULI PANCA ASMARA
• Format: Thesis
• Language: English
• Published: 2011
• Online Access: http://utpedia.utp.edu.my/id/eprint/2815/1/THESIS_YULI_PANCA_ASMARA.pdf; http://utpedia.utp.edu.my/id/eprint/2815/

CO2 corrosion is the main threat in upstream oil and gas operations. The requirement to predict the corrosion in design and operational stage is critical. However, the presence of other corrosion species and operational parameters complicate the mechanism of the corrosion. The interaction between those factors affect the accuracy of the corrosion prediction. Although many publications on CO2 corrosion prediction had been published, most of the prediction models rely on specific algorithms to combine individual effect of the interacting species to represent the total corrosion rate. This effort is inefficient and needs a large number of experiments to process all possible corrosion data simultaneously. In order to study CO2 corrosion of carbon steel involving interactive effects of several key parameters, a proven systematic statistical method that can represent the multitude interactive effects is needed. In this research, a combination of response surface methodology (RSM) and mechanistic corrosion theories were used to construct an empirical model that relates the effects of acetic acid (HAc), temperature, and rotation speed on CO2 and CO2/H2S corrosion rate simultaneously. The corrosion experiments are based on both linear polarization resistance (LPR) and electrochemical impedance spectroscopy (EIS) methods. Flow condition is simulated using rotating cylinder electrode (RCE). The RSM regression models for the carbon steel corrosion in CO2 environments involving HAc, temperature and rotation speed as parameters have been successful developed and validated with experimental data and commercial predictive models. In the form of mathematical equations, the effects of independent variables will be easily identified and developed. The combination RSM and mechanistic theory applied in this research is efficient to determine the empirical relationship of the variables tested simultaneously. Furthermore, RSM models can be used to determine scaling temperature, limiting current density and flow dependency characters.