Microbial corrosion, a direct consequence of uncontrolled microbial activity, is one of the leading causes of pipeline failures in oil and gas industries, especially in non-scrapable pipelines such as flowlines and trunklines. With approximately 20% of corrosion challenges attributed to microbial corrosion, recent shifts in the industry – aging oilfield and increased water injection – are intensifying this problem, leading to higher water cuts in crude oil and reduced pipeline flow rates, which create favorable conditions for microbial corrosion. To address this, the present study implements a mechanistic model, calibrated and validated against experimental pit depth observations and SEM/EDS analyses. This implemented model provides a reliable predictive tool for assessing microbial-induced corrosion, aiding in optimal pipeline design and timely interventions. While many pipelines turn to chemical and physical biofilm inhibitors, leveraging such a predictive model paves the way for more proactive and cost-effective asset management, ensuring enhanced operational continuity and reduced maintenance expenditures.
Corrosion, which is the degradation of materials due to chemical or electrochemical reactions with their environment, poses significant economic and safety concerns across various industries, including infrastructure, transportation, energy, and the Oil and Gas sector 1. Biocorrosion, initiated by microbial activities, has gained significant attention due to its destructive effects on metallic structures and critical assets 2. The formation of biofilms by microbial induced bacteria such as sulfate-reducing bacteria (SRB) and acid-producing bacteria (APB) has been identified as a prominent mechanism contributing to biocorrosion in various environments such as oil and gas 3, 4.
A multidisciplinary approach integrating microbiology, corrosion science, and computational modeling has been examined and introduced as a mechanistic model. This model, based on the biocatalytic cathodic sulfate reaction theory, considers the enzymatic reduction of sulfate as a key step in the corrosion process as presented in Xu et al 5, simulated the corrosion process. It provides insights into the key factors influencing the rate and extent of corrosion in the presence of biofilms of SRB and APB.
