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 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.