ABSTRACT:

We present the Point cLoud Algorithm for NEtwork Extraction of Discrete Fracture Networks (PLANE-DFN), a point cloud–based algorithm for automatic fracture network extraction designed to support discrete fracture network (DFN) modeling workflows. PLANE-DFN segments three-dimensional fracture planes from raw point cloud data using RANdom SAmple Consensus (RANSAC) coupled with statistical outlier removal and density-based clustering to isolate individual fracture features. Each candidate plane is constrained against site-specific structural constraints based on strike and dip. After segmentation, each fracture is converted into a 2-D convex polygon suitable for meshing and simulation. The PLANE-DFN algorithm is validated by comparing geometric and flow and transport data against data from dfnWorks simulations with ensembles of plane-fit networks. We find that the flow and transport in plane-fit networks are comparable to dfnWorks-generated networks when realistic network geometry is maintained. The PLANE-DFN algorithm provides an automated and streamlined workflow to transform point clouds of data into DFN network geometry.

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.