Microorganisms can affect asset integrity in oil and gas systems through numerous processes, collectively termed microbiologically influenced corrosion (MIC); thus, understanding their activity is essential for effective monitoring and mitigation. Many operators use modern DNA technologies (e.g., qPCR/16S rRNA gene amplicon sequencing) as part of their routine microbial monitoring because it provides valuable information about which microbial groups are present. However, presence alone does not indicate whether those microbes are active or contributing to system risk. In contrast, metagenomics identifies all the genes in a microbe by sequencing all DNA in a sample. This information is then sorted and compared to databases, revealing which microorganisms are present and what their genes indicate they can do (e.g., sulfate reduction, biofilm formation, etc.). Metagenomics also supports the estimation of microbial replication rate, a measure of active microbes.This distinction is important for identifying microbes more likely to affect corrosion, souring, or other detrimental processes. This study complements typical microbial monitoring approaches by applying shotgun metagenomic sequencing to two common upstream sample types, produced fluid and pipeline pigging solids from a hydraulic fracturing operation, to provide deeper insights into microbial function, activity, and potential contributions to corrosion-related processes. We found clear differences between the produced water and pigging solids. The production fluid was dominated by Sulfurospirillum, a sulfur-cycling microbe capable of thiosulfate reduction and hydrogen production. Desulfomicrobium also contained genes associated with sulfide formation and production of several organic acids. Of the thirteen microbial genomes recovered, including Desulfomicrobium, Desulfovibrio, and Clostridia, several showed moderate growth rates despite many years of consistent biocide treatment. The pigging solids revealed a more diverse and metabolically capable community with genes for production of all major organic acids, including lactate, formate, propionate, and butyrate. Sulfur-cycling pathways were more abundant in the pigging solids than the produced fluid. We retrieved twenty-eight genomes, including some from rapidly growing organisms such as Acetobacterium, Clostridia, and Desulfomicrobium. These complementary results from operationally relevant sample types have important implications for corrosion risk assessment. Production fluids reflected the circulating microbial population, where activity was present but concentrated in fewer dominant microbes. In contrast, pipeline solids harbored a dense, diverse, and fast-growing community capable of producing corrosive metabolites. This case study highlights the power of metagenomics to provide an activity-focused and function-based view of microbial behavior, supporting a detailed assessment of the microbiologically influenced corrosion risk present in a system and inform targeted mitigation strategies.
