Postdoctoral Fellowship: EAR-PF: Reactive transport in fractured networks: a bipartite graph approach for rapid and accurate prediction

Fractured rocks beneath Earth’s surface play a vital role in supplying clean water, extracting energy resources, and storing carbon dioxide and hydrogen. Water and other fluids move through these fractures where they react with the surrounding rock resulting in changes to the fluid chemistry in ways that influence engineered and natural Earth systems. This postdoctoral fellowship project will help advance the ability to predict the chemical reactions between water and rocks by analyzing data from a deep underground laboratory in South Dakota in conjunction with a new computer model approach. In addition to the scientific research, the project supports hands-on educational outreach to K–12 students, open-source educational tools, and professional development for the postdoctoral fellow, including fieldwork and mentoring experience. The project supports NSF’s mission by advancing geoscience, helping society address challenges like the energy transition, water sustainability, and environmental protection, and by facilitating student participation in geoscience and hydroscience.

Fractured subsurface systems play a critical role in transporting reactive fluids and solutes but are notoriously complex to model accurately at the field scale. The postdoctoral fellowship work supported by this project will develop ways to move beyond that complexity with a reduced-order, bipartite graph-based framework that captures essential flow, transport, and geochemical interactions in fractured rock by leveraging extensive experimental data from previously funded projects. The approach integrates core characterization, geochemical sampling, tracer tests, and electrical resistivity tomography from the Sanford Underground Research Facility to investigate geochemical processes in fractured rock through laboratory experiments. The field and laboratory results will be used to refine and validate both high-fidelity discrete fracture network models and reduced-order bipartite graph models. By overcoming the computational cost of full-physics fracture modeling, this project aims to enable faster, more robust uncertainty quantification and site-specific predictions of reactive transport. Ultimately, this work should advance mechanistic understanding of reactive fracture-rock matrix exchange and improve the ability to predict and manage subsurface systems and related applications such as carbon dioxide sequestration, formation of and exploration for critical minerals, geothermal reservoirs, and managed aquifer water recharge.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2518475
Principal Investigator: Collin Sutton
Funds Obligated: $395,218
State: CO