A Predictive Model for Microbial Induced Corrosion (MIC) in Sub-sea Production Pipelines: Part 1—Abiotic Corrosion Model

Abstract

Abstract Microbial Induced Corrosion (MIC) is a very aggressive form of corrosion with many proposed mechanisms but as yet there is no internationally agreed mechanism for its action. Rapid pitting attack can quickly lead to equipment failure, which is a particular problem in the petrochemical industry where the effects of MIC are prevalent. MIC is a highly complex process but it is believed that Sulphate Reducing Bacteria (SRB) perform a major role. SRB present in anaerobic layers of biofilms at the metal surface can be detected at corrosion sites in the field by the presence of sulphide films. The models currently used to predict MIC offer only a semi-quantitative assessment of MIC and are often unpredictable as they do not often include knowledge of SRB activity or biofilm growth rates. The aim of this investigation is to develop a physical model for the prediction of corrosion rates associated with MIC in subsea production pipelines. The model will include abiotic and biotic corrosion parameters and is based on heterogeneous reactions at the steel surface, a species concentration profile described by the Nernst diffusion layer model, and overall anodic and cathodic current densities balancing each other. Presented in this publication is an initial abiotic model based on a simple corrosion system of pipeline steel exposed to an electrolyte of deaerated low conductivity water. The corrosion system is examined experimentally using potentiodynamic polarisation techniques, a glass corrosion cell and a three electrode potentiostat system. An abiotic model is then developed for this corrosion system and the model prediction compared to the experimental data. The model is shown to be in reasonable agreement with the experimental data.