King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia; King Abdullah University of Science and Technology (KAUST), Biological and Environmental Sciences and Engineering Division (BESE), Thuwal, Saudi Arabia.
Saudi Aramco, Dhahran, Saudi Arabia.
Gene. 2021 Mar 30;774:145425. doi: 10.1016/j.gene.2021.145425. Epub 2021 Jan 12.
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 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.
在全球能源行业中，石油厂的管道和储油罐的腐蚀是一个严重的问题，因为它会导致与频繁更换部件相关的巨大经济损失，并可能导致整个原油田的潜在损坏。以前的研究表明，腐蚀主要是由微生物在目前称为微生物影响腐蚀或生物腐蚀的过程中的活动引起的。确定导致生物腐蚀的细菌对于抑制它至关重要。在这项研究中，我们使用比较宏基因组分析以及生物信息学和统计学，分析了石油厂管道腐蚀部位的微生物群落。我们分析了油田中地下水作为注入水的管道中的微生物群落。我们从油田的四个不同设施中采集了样本。宏基因组分析表明，即使是来自同一设施的样本，微生物群落结构也有很大差异。每个管道位置的杀菌剂处理和去矿物质处理等措施可能独立影响微生物群落结构。结果表明，在整个管网中进行微生物检查对于防止工业工厂的生物腐蚀至关重要。通过确定导致生物腐蚀的细菌种类，本研究提供了用于检测和分类生物腐蚀的细菌指标。此外，这些物种可以作为早期检测生物腐蚀的生物标志物。然后，可以立即和适当地进行适当的管理，例如用合适的杀菌剂处理。因此，我们的研究将作为获取与生物腐蚀相关的微生物信息的平台，以开发一种实用的方法来防止其发生。
