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Curlew

Geological models with neural fields

Install / Use

/learn @samthiele/Curlew
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

curlew

A toolkit for building 2- and 3- dimensional geological models using neural fields.

<img src="https://github.com/samthiele/curlew/blob/main/icon.png?raw=true" width="200">

Getting started

Installation

To install directly from github try: pip install git+https://github.com/samthiele/curlew.git.

This should run on most systems: numpy, pytorch and tqdm are the only required dependencies. Matplotlib is handy too, but not required.

Tutorials

To help get up to speed with curlew, we maintain a set of CoLab tutorial notebooks here. Additional examples (used to make figures in the paper listed below) can be found here.

Documentation

Documentation is automatically built and served through GitHub pages.

Support and feedback

Please use GitHub issues to report bugs. For broader ideas or questions, don't hesitate to use the discussions page.

Contributing and appreciation

Please star this repository if you found it useful. If you have fixed bugs or added new features then we welcome pull requests.

Authors and acknowledgment

curlew has been developed by Sam Thiele and Akshay Kamath, with valuable input from Mike Hillier, Lachlan Grose, Richard Gloaguen and Florian Wellmann.

If you use curlew we would appreciate it if you:

  1. Cite the following paper (for academic work)
Kamath, A.V., Thiele, S.T., Moulard, M., Grose, L., Tolosana-Delgado, R., Hillier, M.J., Wellmann, R., & Gloaguen, R. Curlew 1.0: Implicit geological modelling with neural fields in python. Geoscientific Model Development (preprint online soon) 
  1. Star this repository so that we get a rough idea of our user base

  2. Leave a GitHub issue if you have questions or comments (Issues do not strictly need to be related to bug reports).

View on GitHub
GitHub Stars40
CategoryDevelopment
Updated6d ago
Forks5

Languages

Python

Security Score

90/100

Audited on Mar 31, 2026

No findings