Predicting Localized Corrosion in Geothermal Systems

Abstract Localized corrosion poses a critical challenge for geothermal systems due to the presence of high temperatures and corrosive species such as chlorides, acid gases, and dissolved oxygen. Models that can accurately predict the risk of localized corrosion are thus essential for effective asset management. This study extends the Mixed-Solvent Electrolyte (MSE) corrosion model to predict the risk of localized corrosion to conditions relevant for geothermal systems. The model incorporates two key electrochemical potentials, i.e., the corrosion potential (Ecorr) and repassivation potential (Erp), predicting localized corrosion risk when Ecorr exceeds Erp. The focus of this study is improving predictions for Erp. The previously developed MSE Erp model is extended to account for the effect of reduced sulfur species, such as H2S and S2O32-, which are present in some geothermal systems and can either promote or inhibit localized corrosion depending on the environmental conditions. To improve Erp predictions, high temperature electrochemical data, which are scarce in the literature, were obtained for alloys frequently used in geothermal systems. This data was then used to develop parameters and to validate the model’s accuracy under geothermal conditions.