Lawrence Berkeley National Laboratory

Abstract Quantitative predictions of natural and induced phenomena in fractured rock is one of the great challenges in the Earth and Energy Sciences with far‐reaching economic and environmental impacts. Fractures occupy a very small volume of a subsurface formation but often dominate fluid flow, solute transport and mechanical deformation behavior. They play a central role in CO 2 sequestration, nuclear waste disposal, hydrogen storage, geothermal energy production, nuclear nonproliferation, and hydrocarbon extraction. These applications require predictions of fracture‐dependent quantities of interest such as CO 2 leakage rate, hydrocarbon production, radionuclide plume migration, and seismicity; to be useful, these predictions must account for uncertainty inherent in subsurface systems. Here, we review recent advances in fractured rock research covering field‐ and laboratory‐scale experimentation, numerical simulations, and uncertainty quantification. We discuss how these have greatly improved the fundamental understanding of fractures and one's ability to predict flow and transport in fractured systems. Dedicated field sites provide quantitative measurements of fracture flow that can be used to identify dominant coupled processes and to validate models. Laboratory‐scale experiments fill critical knowledge gaps by providing direct observations and measurements of fracture geometry and flow under controlled conditions that cannot be obtained in the field. Physics‐based simulation of flow and transport provide a bridge in understanding between controlled simple laboratory experiments and the massively complex field‐scale fracture systems. Finally, we review the use of machine learning‐based emulators to rapidly investigate different fracture property scenarios and accelerate physics‐based models by orders of magnitude to enable uncertainty quantification and near real‐time analysis. Plain Language Summary Some of the greatest challenges currently facing humanity have roots in the Earth and Energy Sciences. Policymakers rely on scientific research to answer questions related to the transition to green renewable energy, mitigate the climate crisis, and ensure global stability with reliable energy and water resources. A common thread in addressing these societal issues with far‐reaching economic and environmental impacts is the prediction of flow and transport in subsurface systems in the Earth, particularly in fractured rock. The need to predict, optimize and ultimately control fractured subsurface systems is an increasingly important topic, with 80% of the US energy resources and 50% of its drinking water supply coming from the subsurface. In this review, we describe the state‐of‐the‐art research on flow and transport in fracture systems and the path forward for the integration of field observations, laboratory experiments, predictive modeling, and uncertainty quantification to enable more efficient and environmentally prudent usage of critical subsurface resources. Key Points Understanding and predicting fractured systems requires integrating field and lab experiments, simulation and uncertainty quantification Densely monitored field sites and in situ lab experiments provide quantitative measures of flow and transport that can constrain models Physics‐based models with machine‐learning emulators enable uncertainty quantification of flow and transport in complex fracture networks