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Graph-based flow modeling approach adapted to multiscale discrete-fracture-network models.

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Graph models of fractured rock (discrete fracture networks) can predict fluid flow. An intersection graph, with a new conductance model, accurately estimates flow, offering a faster alternative to traditional methods.

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Area of Science:

  • Geosciences
  • Computational modeling
  • Fluid dynamics

Background:

  • Fractured rocks are complex systems often modeled using discrete fracture networks (DFNs).
  • Graph representations simplify DFNs by focusing on connectivity, enabling property assignments like conductance.
  • Predicting fluid flow in DFNs is crucial for understanding subsurface processes.

Purpose of the Study:

  • To evaluate graph representations as efficient substitutes for DFNs in predicting fluid flow.
  • To introduce and refine a conductance model for graph-based flow prediction.
  • To compare the performance of fracture graphs versus intersection graphs.

Main Methods:

  • Developed two graph types: fracture graphs and intersection graphs.
  • Introduced an edge conductance expression incorporating fracture surface area and transmissivity.
  • Implemented a correction factor for intersection graphs based on fracture intersection counts.
  • Validated the graph models against high-fidelity DFN simulations.

Main Results:

  • Including fracture size in conductance calculations improved flow prediction accuracy.
  • Fracture graphs consistently underestimated flow, while intersection graphs overestimated it.
  • The corrected intersection graph model showed good agreement with DFN simulations across various network types.

Conclusions:

  • The intersection graph, with the proposed conductance model, provides a robust and accurate method for predicting fluid flow in fractured rocks.
  • This graph-based approach offers a computationally efficient alternative to traditional DFN simulations for flow analysis.