Collin Sutton

University of Wisconsin

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ABSTRACT:

Fractures are a primary feature controlling flow, transport, and coupled processes in geologic systems. To date, experimental image-based observations of these processes have been challenging. Here, we successfully demonstrate the use of a graph-based, laboratory-validated flow and transport model for conservative solute transport in a natural fracture. Pulse-tracer experiments with a conservative radiotracer ([18F]-FDG) spanning multiple flow regimes with simultaneous positron emission tomography (PET) imaging are used to characterize transport in a two-inch fractured Sierra granite core. Model network complexity, determined by the number of nodes and edges, significantly impacts model fit to observed data. Large graphs over-describe a fracture plane and act similarly to a porous medium while small graphs oversimplify the solute transport behavior. This work provides the first validation of graph-based flow and transport models across a range of experimental conditions and sets the groundwork for upscaling to more complex and computationally efficient fracture network models.

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ABSTRACT:

Fractures are a primary feature controlling flow, transport, and coupled processes in geologic systems. To date, experimental image-based observations of these processes have been challenging. Here, we successfully demonstrate the use of a graph-based, laboratory-validated flow and transport model for conservative solute transport in a natural fracture. Pulse-tracer experiments with a conservative radiotracer ([18F]-FDG) spanning multiple flow regimes with simultaneous positron emission tomography (PET) imaging are used to characterize transport in a two-inch fractured Sierra granite core. Model network complexity, determined by the number of nodes and edges, significantly impacts model fit to observed data. Large graphs over-describe a fracture plane and act similarly to a porous medium while small graphs oversimplify the solute transport behavior. This work provides the first validation of graph-based flow and transport models across a range of experimental conditions and sets the groundwork for upscaling to more complex and computationally efficient fracture network models.

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