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

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.