DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring
Abstract Subsurface technologies including Carbon Capture, Utilization and Storage, geothermal systems, and hydrogen storage face persistent technical-economic barriers in monitoring precision and cost-effectiveness. Here we present a DNA sequencing method to track microbial communities in subsurfac...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Communications Earth & Environment |
| Online Access: | https://doi.org/10.1038/s43247-025-02271-8 |
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| author | Haitong Yang Chunlei Yu Shiqi Wang Allegra Hosford Scheirer Xiang-Zhao Kong Hui Zhao Xuewu Yang Shuoliang Wang Liangliang Jiang |
| author_facet | Haitong Yang Chunlei Yu Shiqi Wang Allegra Hosford Scheirer Xiang-Zhao Kong Hui Zhao Xuewu Yang Shuoliang Wang Liangliang Jiang |
| author_sort | Haitong Yang |
| collection | DOAJ |
| description | Abstract Subsurface technologies including Carbon Capture, Utilization and Storage, geothermal systems, and hydrogen storage face persistent technical-economic barriers in monitoring precision and cost-effectiveness. Here we present a DNA sequencing method to track microbial communities in subsurface fluid flow. It addresses three main challenges: the lack of large-scale time-lapse monitoring, the absence of microbial tracer selection, and the oversight of front propagation velocity. The method is applied across all stages of a reservoir’s circulating water injection lifecycle, including initial injection, ongoing circulation, post-injection monitoring, and production. The injection and production well samples are analyzed to select stable microbial tracers, enabling flow-front velocity-integrated mapping of subsurface fluid pathways via principal coordinate analysis. The accuracy is validated through physical simulation experiments and the Kalman filter method, enabling 44-day time-lapse, large-scale dynamic monitoring of 1300m-deep subsurface fluid flow pathways. This study helps reduce uncertainties in geoenergy development, supporting the goal of a net-zero emission world. |
| format | Article |
| id | doaj-art-aff3678ebedb4495b9e7e91e3569a8bf |
| institution | OA Journals |
| issn | 2662-4435 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Earth & Environment |
| spelling | doaj-art-aff3678ebedb4495b9e7e91e3569a8bf2025-08-20T02:27:11ZengNature PortfolioCommunications Earth & Environment2662-44352025-04-016111610.1038/s43247-025-02271-8DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoringHaitong Yang0Chunlei Yu1Shiqi Wang2Allegra Hosford Scheirer3Xiang-Zhao Kong4Hui Zhao5Xuewu Yang6Shuoliang Wang7Liangliang Jiang8School of Energy Resources, China University of Geosciences (Beijing)Exploration and Development Research Institute of Sinopec Shengli Oilfield BranchSchool of Energy Resources, China University of Geosciences (Beijing)Department of Geological Sciences, Stanford UniversityGeothermal Energy & Geofluids Group, Institute of Geophysics, ETH ZurichGeological Research Institute of the Third Oil Production Plant of Changqing Oilfield Branch of China National Petroleum CorporationGeological Research Institute of the Third Oil Production Plant of Changqing Oilfield Branch of China National Petroleum CorporationSchool of Energy Resources, China University of Geosciences (Beijing)Department of Chemical and Petroleum Engineering, University of CalgaryAbstract Subsurface technologies including Carbon Capture, Utilization and Storage, geothermal systems, and hydrogen storage face persistent technical-economic barriers in monitoring precision and cost-effectiveness. Here we present a DNA sequencing method to track microbial communities in subsurface fluid flow. It addresses three main challenges: the lack of large-scale time-lapse monitoring, the absence of microbial tracer selection, and the oversight of front propagation velocity. The method is applied across all stages of a reservoir’s circulating water injection lifecycle, including initial injection, ongoing circulation, post-injection monitoring, and production. The injection and production well samples are analyzed to select stable microbial tracers, enabling flow-front velocity-integrated mapping of subsurface fluid pathways via principal coordinate analysis. The accuracy is validated through physical simulation experiments and the Kalman filter method, enabling 44-day time-lapse, large-scale dynamic monitoring of 1300m-deep subsurface fluid flow pathways. This study helps reduce uncertainties in geoenergy development, supporting the goal of a net-zero emission world.https://doi.org/10.1038/s43247-025-02271-8 |
| spellingShingle | Haitong Yang Chunlei Yu Shiqi Wang Allegra Hosford Scheirer Xiang-Zhao Kong Hui Zhao Xuewu Yang Shuoliang Wang Liangliang Jiang DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring Communications Earth & Environment |
| title | DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| title_full | DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| title_fullStr | DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| title_full_unstemmed | DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| title_short | DNA-sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| title_sort | dna sequencing method maps subsurface fluid flow paths for enhanced monitoring |
| url | https://doi.org/10.1038/s43247-025-02271-8 |
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