GeoDFN

Stochastic Discrete Fracture Network Generator

Generate geologically realistic fracture networks from field statistics — with a point-and-click interface or a Python API.

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What is GeoDFN?

GeoDFN generates stochastic 2D Discrete Fracture Networks calibrated from geological field observations. Starting from outcrop statistics, it produces geologically plausible fracture network ensembles ready for flow, transport, and geomechanical simulations.

It ships in two forms — a desktop app for interactive use, and a Python library for scripting and large-scale batch generation.

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Get Started in 3 Steps

Option A — Desktop App (no Python required)

1. Click the Download button above
2. Unzip the file
3. Double-click GeoDFN.exe → your browser opens with the interface

Option B — Python API

git clone https://github.com/kamelelahe/GeoDFN.git
cd GeoDFN
pip install -r requirements.txt

import numpy as np
from GeoDFN.Classes.DFNGenerator import DFNGenerator

gen = DFNGenerator(
    domainLengthX=300, domainLengthY=600,
    sets=[{
        'I': 0.01,
        'fractureLengthPDF': 'Log-Normal',
        'fractureLengthPDFParams': {'mu': 2.4, 'sigma': 0.73, 'Lmin': 2.59, 'Lmax': 57.48},
        'spatialDistributionPDF': 'Power-law',
        'spatialDistributionPDFParams': {'alpha': 0.51, 'min distance': 1, 'max distance': 600},
        'orientationDistributionPDF': 'Von-Mises',
        'orientationDistributionPDFParams': {'kappa': 8.55, 'loc': 1.4,
                                              'thetaMin': np.radians(30), 'thetaMax': np.radians(120)},
        'bufferZone': {'method': 'constant', 'constant': 1.4},
    }],
    apertureCalculationParameters={'method': 'subLinear', 'scalingCoefficient': 0.001, 'scalingExponent': 0.5},
    DFNName='my_dfn',
    numOfRealizations=10,
)

print(f"{len(gen.realizations)} realizations generated")

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GUI or Python API?

	Desktop GUI	Python API
Best for	Visual exploration, parameter tuning, quick results	Large ensembles, batch generation, simulation pipelines
Setup	Download & double-click	pip install -r requirements.txt
Realizations	Interactive, one run at a time	Hundreds to thousands, fully automated

For synthetic dataset generation and uncertainty quantification studies, we recommend the Python API. It allows full automation over parameter spaces that would be impractical to configure manually through an interface.

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Capabilities

Feature	Options
Fracture length	Log-Normal · Power-law · Exponential · Constant
Orientation	Von-Mises · Uniform · Constant
Spatial distribution	Power-law · Log-Normal · Uniform
Aperture model	Constant · Sub-linear scaling · Barton-Bandis · Lepillier
Placement constraints	Fixed seed points · Exclusion zones · Buffer spacing
Stress correction	Multi-azimuth stress-dependent aperture
Output	Coordinates · Apertures · Statistics · Stereonets · Visualizations

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Output

Each run writes results to DFNs/<name>/:

DFNs/<name>/
├── fractureCoordinates/       # Start/end (x, y) of each fracture
├── aperture/                  # Aperture values
├── fractureSet/               # Full fracture list per set
├── orientationStereographic/  # Stereonet plots
├── outputPropertiesTotal/     # Network statistics
└── pics/                      # DFN visualizations

Results are also available in memory after generation:

fractures = gen.realizations[0][0]           # realization 0, set 0
print(fractures[0]['fracture length'])        # length in metres
print(fractures[0]['fracture aperture'])      # aperture in metres

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For Developers

Installation, tests, and building the desktop app

Install with dev dependencies

pip install -e ".[dev]"

Run tests

pytest tests/

Build the desktop app

pip install pyinstaller
python -m PyInstaller geodfn.spec --noconfirm

Distributable is generated in dist/GeoDFN/. Share the entire folder — users double-click GeoDFN.exe.

Project structure

GeoDFN/
├── Classes/
│   ├── DFNGenerator.py                      # Random-seed generator
│   ├── DFNGeneratorWithSeed.py              # Fixed seed-point generator
│   ├── DFNGeneratorWithSeedAndExclusion.py  # Generator with exclusion zones
│   ├── _validation.py                       # Input validation
│   ├── fractureLengthPDFs.py
│   ├── orientationPDFs.py
│   ├── spatialDistributionPDFs.py
│   ├── apertureCalculator.py
│   └── bufferZoneCalculator.py
├── Example-BrazilRandomSeeds.py
├── Example-BrazilFixedSeeds.py
├── Example-BrazilFixedSeedsAndExclusion.py
├── Example-BrazilAperture.py
├── Examples.ipynb
└── PercolationAnalysis.ipynb
app.py          # Streamlit GUI
launcher.py     # Desktop app entry point
geodfn.spec     # PyInstaller build spec

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Dataset

Datasets/Brazil/Apodi.txt contains fracture trace data from the Apodi carbonate formation (Potiguar Basin, NE Brazil), used to calibrate the provided examples.

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Citation

If you use GeoDFN in your research, please cite:

Kamel Targhi, E., et al. "From outcrop observations to dynamic simulations: an efficient workflow for generating ensembles of geologically plausible fracture networks and assessing their impact on flow and transport." Geoenergy 3.1 (2025): geoenergy2025-028.

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License

MIT License — © 2025 Elahe Kamel Targhi. See LICENSE for details.