Microbially influenced corrosion (MIC) poses a significant threat to the oil and gas industry, leading to costly failures and disruptions across production, transportation, and storage systems. Traditional microbial assessment and mitigation strategies often rely on culture-based methods, potentially underestimating the complexity of corrosion-driving microbial communities. Here, we present an integrative methodology that combines third-generation sequencing technologies, quantitative polymerase chain reaction (qPCR), physicochemical analyses of operational environments, and 3D reconstructions of defects on metallic probes or coupons, complemented by a thorough examination of design and operational parameters. By targeting both planktonic and sessile bacterial populations, this approach enables a comprehensive evaluation of corrosion-inducing potential under site-specific conditions. Crucially, shifts in microbial community composition across diverse corrosive taxa provide early warnings of elevated corrosion risk, guiding adjustments to biocides, corrosion inhibitors, and failure analyses. This framework’s inclusion of unculturable microorganisms underscores the importance of quantitative molecular methods in conjunction with or as an alternative to traditional culture-based techniques. Moreover, the integration of high-throughput sequencing data with advanced analytics supports the development of robust monitoring protocols, while the 3D mapping of metallic defects refines the detection of localized corrosion hotspots. By iteratively combining microbial profiling, defect reconstruction, and physicochemical parameters, this methodology refines monitoring strategies and defines key performance indicators (KPIs) that inform continuous optimization of corrosion management. Ultimately, this holistic and data-driven approach enhances the reliability and longevity of oil and gas infrastructure by enabling proactive, evidence-based decisions aimed at mitigating MIC effectively.
