Articles | Volume 19, issue 8
https://doi.org/10.5194/gmd-19-3455-2026
https://doi.org/10.5194/gmd-19-3455-2026
Development and technical paper
 | 
27 Apr 2026
Development and technical paper |  | 27 Apr 2026

Curlew 1.0: Spatio-temporal implicit geological modelling with neural fields in python

Akshay V. Kamath, Samuel T. Thiele, Marie Moulard, Lachlan Grose, Raimon Tolosana-Delgado, Michael J. Hillier, Florian Wellmann, and Richard Gloaguen

Model code and software

samthiele/curlew: Curlew 1.00 Samuel T. Thiele et al. https://doi.org/10.5281/zenodo.17187731

Interactive computing environment

k4m4th/curlew_examples: curlew_examples Akshay V. Kamath and Samuel T. Thiele https://doi.org/10.5281/zenodo.19002735

Download
Short summary
We present Curlew, an open-source Python tool for constructing 3D geological models using machine learning. It integrates diverse spatial data and structural observations into a flexible, event-based framework. Curlew captures complex features like folds and faults, handles uncertainty, and supports learning from sparse or unlabelled data. We demonstrate its capabilities on synthetic and real-world examples.
Share