Corrosion in pipelines and reservoir tanks in oil plants is a serious problem in the global energy industry because it causes substantial economic losses associated with frequent part replacement and can lead to potential damage to entire crude oil fields. Previous studies revealed that corrosion is mainly caused by microbial activities in a process currently termed microbiologically influenced corrosion (MIC) or biocorrosion. Identifying the bacteria responsible for biocorrosion is crucial for its suppression. In this study, we analyzed the microbial communities present at corrosion sites in oil plant pipelines using comparative metagenomic analysis along with bioinformatics and statistics. We analyzed the microbial communities in pipelines in an oil field in which groundwater is used as injection water. We collected samples from four different facilities in the oil field. Metagenomic analysis revealed that the microbial community structures greatly differed even among samples from the same facility. Treatments such as biocide administration and demineralization at each location in the pipeline may have independently affected the microbial community structure. The results indicated that microbial inspection throughout the pipeline network is essential to prevent biocorrosion at industrial plants. By identifying the bacterial species responsible for biocorrosion, this study provides bacterial indicators to detect and classify biocorrosion. Furthermore, these species may serve as biomarkers to detect biocorrosion at an early stage. Then, appropriate management such as treatment with suitable biocides can be performed immediately and appropriately. Thus, our study will serve as a platform for obtaining microbial information related to biocorrosion to enable the development of a practical approach to prevent its occurrence.