Input and benchmarking data for flow simulations in discrete fracture networks

Area of Science:

• Geosciences
• Computational Science
• Numerical Simulation

Background:

• Discrete Fracture Networks (DFNs) are crucial for modeling fluid flow in fractured rock masses.
• Accurate simulation of DFNs requires robust numerical methods for handling complex geometries.
• Existing data sets for DFN simulations are limited, hindering method development and validation.

Purpose of the Study:

• To provide a comprehensive data set for discrete fracture network (DFN) simulations.
• To facilitate the study of conforming, non-conforming, and non-matching discretization couplings.
• To support research on numerical schemes for fractured porous media.

Main Methods:

• Generation of geometrical input data for DFNs with increasing complexity.
• Inclusion of a DFN extruded from a real fracture outcrop in Western Norway.
• Simulation of DFNs using multiple numerical schemes.

Main Results:

• Provision of convergence histories for different numerical schemes.
• Generation of plots over lines and upscaled output quantities.
• Data set covers a range of fracture network complexities and numerical treatments.

Conclusions:

• The data set enables detailed analysis of discretization coupling effects in DFN simulations.
• Researchers can use this data to validate and compare numerical methods for fractured media.
• The study contributes to advancing the simulation accuracy and reliability of DFNs.