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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Main Authors: Haitong Yang, Chunlei Yu, Shiqi Wang, Allegra Hosford Scheirer, Xiang-Zhao Kong, Hui Zhao, Xuewu Yang, Shuoliang Wang, Liangliang Jiang
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
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.
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issn 2662-4435
language English
publishDate 2025-04-01
publisher Nature Portfolio
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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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