FluvGAN: Python scripts to test generating and inverting fluvial deposits using GANs

DOI:10.4121/3469c879-f443-4fcf-83a2-b6df56e96714.v1
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DOI: 10.4121/3469c879-f443-4fcf-83a2-b6df56e96714

Datacite citation style

Rongier, Guillaume; Peeters, Luk (2025): FluvGAN: Python scripts to test generating and inverting fluvial deposits using GANs. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/3469c879-f443-4fcf-83a2-b6df56e96714.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

FluvGAN is a set of Python scripts to test generating and inverting fluvial deposits using generative adversarial networks (GANs) in the context of predicting the physical properties of the subsurface. It builds upon FluvDepoSet (https://doi.org/10.25919/4fyq-q291) - a dataset of 3D representations of fluvial deposits simulated with CHILD (https://github.com/childmodel/child), a landscape evolution model - for training, and upon voxgan (https://github.com/grongier/voxgan), a Python package making it easier to define and train GANs with PyTorch.


Installation

You can install all the packages needed to run all the scripts using conda and the file environment.yml included in this repository:

conda env create -f environment.yml

In addition, the file environment_cluster.yml contains the full list of packages with which the scripts were run on a cluster with a Linux system:

conda env create -f environment_cluster.yml

This environment misses some packages to visualize the results, because those steps were not done on the cluster, and it misses voxgan, because it was used during voxgan's development (now you can install it using pip, see https://github.com/grongier/voxgan).


Usage

FluvGAN is subdivided into three compressed folders:

  • scripts.zip contains all the Python scripts and Jupyter notebooks to train and test the GANs and to generate some figures showcasing the results.
  • data.zip contains the well & seismic data used for testing GAN inversion; the training and testing samples need to be downloaded from FluvDepoSet at https://doi.org/10.25919/4fyq-q291, which can be done using the script fluvgan_0_data.py.
  • outputs.zip contains all the outputs from all the scripts, including the pretrained GAN models; the outputs' names follow the same convention as the scripts, and the scripts showcase how to reuse those outputs using Python.

You can find more information in the file README.md.


License

Copyright notice: Technische Universiteit Delft hereby disclaims all copyright interest in the program fluvgan written by the Author(s). Prof.dr.ir. S.G.J. Aarninkhof, Dean of the Faculty of Civil Engineering and Geosciences

© 2025, Guillaume Rongier, Luk Peeters

This work is licensed under a MIT OSS licence, see the file LICENSE for more information.

History

  • 2025-10-15 first online, published, posted

Publisher

4TU.ResearchData

Format

Python scripts (.py), Jupyter notebooks (.ipynb), PyTorch models (.pt), arrays (.npy or .nc), text files (.csv)

Organizations

TU Delft, Faculty of Civil Engineering & Geosciences, Department of Geoscience and Engineering, Applied Geology

DATA

Files (7)