MIC Risk Assessment in Upstream Pipelines: An Optimized Corrosion Mitigation Approach

Microbiologically influenced corrosion (MIC), primarily driven by the presence of sulfate-reducing bacteria (SRB), poses a continuous threat to the integrity of pipeline networks. An MIC-prone environment is characterized by high levels of nutrients (such as sulfates, nitrates, and organic acids), low temperatures, low flow velocities or stagnant flow regimes, and a high bacterial cell count. In upstream operations, existing mitigation efforts include pigging, biocide batch treatment, and continuous serial dilution test methods for bacterial monitoring. To assess the existing microbial risk, a comprehensive assessment was conducted and benchmarked against peer upstream operators and the industry's best practices. A multifactorial risk model was applied, incorporating nutrient availability, flow velocity and regime, temperature, microbial activity, and hydrogen sulfide (H₂S) partial pressure as thresholds for SRB auto-toxicity. By utilizing this data-driven framework, the pipelines were successfully classified into low- and high-risk MIC categories. The study also presents evaluations of the MIC risk model, as well as a supported case studies based on historical field data and In-line Inspection (ILI) survey results. Using the results of these classifications, an improved management strategy was introduced by reducing biocide dosage frequency in low-risk segments and increasing kill contact time in high-risk segments. Various types of active monitoring were recommended as part of the optimization program, including inlet/outlet bacterial counts, bio-probes, and corrosion coupons to monitor microbially induced corrosion, as well as inspection data and DNA-based microbial analysis. This targeted approach resulted in a reduction of biocide usage by more than 80%, leading to significant annual cost savings, a reduction in OPEX, and improvements in pipeline integrity management. This integrated methodology demonstrates the effectiveness of data-driven risk assessment and tailored treatment strategies, establishing a sustainable and economically viable benchmark for MIC management in upstream pipeline operations.