Organic corrosion inhibitors (CIs) are widely employed in the oil and gas industry to protect carbon steel pipelines against internal corrosion. Inhibitor selection by corrosion engineers frequently relies on long testing procedures and protocols, which requires significant time and expenditure. This study aims at providing a simpler and more reliable methodology for inhibitor characterization, which can contribute to inhibitor selection in the oil and gas industry. Two model compounds, tetradecyl phosphate ester (TPE) and tetradecyl tetrahydropyrimidinium (TTHP), were chosen for this methodology development in an aqueous environment of 5 wt.% NaCl (pH = 4.5) at 25° C . Linear polarization resistance (LPR) measurements were conducted to determine the corrosion rate (CR) over a wide range of CI concentrations, from which surface saturation concentration and surface coverage (?) values were extracted. Kinetic parameters for adsorption (kA, kD, and KAD) were obtained by means of Langmuir adsorption isotherm and non-linear regression analysis. Potentiodynamic polarizations were executed to analyze the inhibition behaviors. It is concluded that both TPE and TTHP could retard anodic and cathodic reactions with no change in limiting current.


Corrosion inhibitors (CIs) are widely used in the oil and gas industry to protect carbon steel tubulars against internal corrosion. CIs can be injected continuously into a corrosive environment at very low concentrations to decrease the corrosion rate of the exposed metallic material and maintain effective corrosion protection 1. CO2 corrosion inhibitors typically consist of amphiphilic, surface-active molecules with alkyl tails typically in the range of C12 to C18 2. Such molecules have a strong tendency to adsorb onto the steel surface and form self-assembled structures 3,4.

However, the performance of these surfactant-type CIs is influenced by operating conditions, such as temperature, pressure, pH, and flow. If a corrosion inhibitor is added without considering these factors, its efficiency could be decreased and sometimes lost, which may result in unpredictable behavior and corrosion-related failures 5-7. Generally, operators in the field find it very hard to predict CIs performance in advance, if there is any change in the operating condition. Consequently, an effective corrosion prediction tool would be indeed of great value. The long term objective of this work is to develop such an inhibition prediction tool, using, as a starting point, the inhibition model proposed by Dominguez Olivo 8,9. For now, the goal of this study is to develop a methodology for CI characterization valid in a wide range of conditions, which can be used for CI selection and dosing strategy. So far, the practice of corrosion inhibitor selection for corrosion engineers in the oil and gas industry usually relies on long testing procedures and protocols 6. This practice requires excess time, which could be shortened with the development of methodology for CI characterization.

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