## 1 Introduction
Case-based reasoning model and Taylor expansion method are employed to predict the corrosion rate as a function of pipeline material, pH, CO\({}_{2}\), and H\({}_{2}\)S content and temperature. The CBR-TS model was tested using a field database and a hypothetical database. NORSOK M-506 [21] developed a semi-empirical corrosion rate model using laboratory data that investigates the corrosion rates in a flow loop by varying parameters, such as temperature, solution pH, and CO\({}_{2}\) partial pressure, but it has limitations to predict the interaction between CO\({}_{2}\) and H\({}_{2}\)S.  
The aforementioned corrosion rate models do not include the interaction of chlorine ions and the corrosion effects. Whilst predictive software for pipeline corrosion is commercially available (11 commercial software packages), the results of each predictive package do not agree with each other. Even different versions of the same software have been known to give different corrosion rate results. There are many reasons for this, but it is clear that there is still a need for self-consistent predictive software for pipeline corrosion. [PERSON] [22] has reviewed the models available to predict Corrosion rate in different CO\({}_{2}\) partial pressures, temperatures, and other flow parameters, and the work concludes that all the models have limitations depending upon the philosophy used in developing these models. A general prediction of the corrosion rates is difficult as the corrodents and the environmental factors are varying in different field data. The work concludes that the prediction of corrosion rates by these models vary considerably from case to case--most models are successful in predicting their respective data, but very unsuccessful when predicting other field data. This is concluded in Figure 1 below, where six different models are analyzed by our research team, which is similar to the comparison done by [PERSON] in his work, and the results show a large deviation in corrosion prediction in all these models. In the oil industries, the corrosion rates of pipelines are intensified when the hydrocarbons phase is transported with corrosive brines, and the composition and its effects should be analyzed to predict the rates [23]. The presence of NaCl complicates the kinetics and the mechanism of pipeline corrosion depending on whether it is deaerated or aerated systems. The effect of chloride ions on corrosion rates varies depending upon the environment as it affects anodic kinetics, scale formation, CO\({}_{2}\) solubility, and pH [24]. However, in the literature, there are limited studies that provide corrosion rate models with detailed parametric studies in NaCl solutions. To improve the prediction of corrosion rates a parametric study incorporating the different parameters which affect corrosion is desirable, especially in pipelines in the industries where the flow conditions and rates are not stable. In his later work, [PERSON] et al. updated his previous work [18] to develop an H\({}_{2}\)S Corrosion model [25] which includes the kinetics of iron sulfide growth with experimental results at very low temperatures (5 \({}^{\circ}\)C to 20 \({}^{\circ}\)C) and high salinity brines (up to 25 wt% NaCl). In CO\({}_{2}\)-saturated solutions, the effect of NaCl concentration on corrosion rates in carbon steel is studied by [26] exposing the sample for 100 h by changing NaCl concentrations from 0.001 wt% to 10 wt% at room temperature. The corrosion rates were determined using Electrochemical Impedance Spectroscopy (EIS) and linear polarization method under the freely corroding condition and authors also studied anodic and cathodic kinetics using microelectrode technique. According to this study, the corrosion rate tends to decrease with NaCl concentration, which is opposite to the naturally aerated seawater. The effect of NaCl concentration on mild steel in CO\({}_{2}\)-saturated brines is studied by [24; 27] using a mechanistic model that considers mass transfer and electrochemical kinetics.