LukasMosser/PorousMediaGan
Reconstruction of three-dimensional porous media using generative adversarial neural networks
This project helps geoscientists and engineers working with subsurface rock formations to generate realistic 3D models of porous media, such as sandstone or beadpacks. By inputting real CT scan data of a porous material, it produces new, statistically similar 3D porous media structures. This is ideal for researchers studying fluid flow, reservoir behavior, or material properties who need to explore various microstructures.
189 stars. No commits in the last 6 months.
Use this if you need to create numerous synthetic 3D pore-scale models that capture the complex geometry of real rock samples for simulation and analysis.
Not ideal if you need to analyze existing images or perform direct simulations without generating new microstructures, or if you lack access to CT scan data for training.
Stars
189
Forks
68
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 02, 2019
Commits (30d)
0
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