Modelling of microbiologically influenced corrosion in harsh environments

Abstract

Microbiologically influenced corrosion (MIC) is one of the main causes of internal corrosion in oil pipelines and corrosion in oil wells. While many theories have been proposed to explain MIC, much about this form of corrosion remains poorly understood. At the heart of what is unclear about MIC is the role of surface deposits and biofilms in the process. To understand MIC, it is necessary to understand the changes that occur in surface deposits/biofilms. This can be achieved by two modelling approaches: deterministic modelling and molecular modelling. This thesis work employs the deterministic modelling approach to investigate the changes that occur in the electrochemistry of the biofilm as MIC occurs, which is then used to develop a predictive, time-dependent model of MIC. It also uses molecular modelling to examine the atomistic interactions that occur on the surface of steel materials. Both models are validated using published data from the literature.