Articles | Volume 16, issue 23
https://doi.org/10.5194/gmd-16-6987-2023
https://doi.org/10.5194/gmd-16-6987-2023
Development and technical paper
 | 
29 Nov 2023
Development and technical paper |  | 29 Nov 2023

GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling

Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard

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Cited articles

Atzmon, M. and Lipman, Y.: Sal: Sign agnostic learning of shapes from raw data, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, 2565–2574, https://doi.org/10.1109/CVPR42600.2020.00264, 2020. 
Bédard, K., Marsh, A., Hillier, M., Music, T.: 3D geological model of the Western Canadian Sedimentary Basin in Saskatchewan, Canada, Geological Survey of Canada, Open File 8969, https://doi.org/10.4095/331747, 2023. 
Bi, Z., Wu, X., Geng, Z., and Li, H.: Deep relative geologic time: a deep learning method for simultaneously interpreting 3- D seismic horizons and faults, J. Geophys. Res.-Sol. Ea., 126, e2021JB021882, https://doi.org/10.1029/2021JB021882, 2021. 
Bi, Z., Wu, X., Li, Z., Chang, D., and Yong, X.: DeepISMNet: three-dimensional implicit structural modeling with convolutional neural network, Geosci. Model Dev., 15, 6841–6861, https://doi.org/10.5194/gmd-15-6841-2022, 2022. 
Boisvert, J. B., Manchuk, J. G., and Deutsch, C. V.: Kriging in the Presence of Locally Varying Anisotropy Using Non-Euclidean Distances, Math. Geosci., 41, 585–601, https://doi.org/10.1007/s11004-009-9229-1, 2009. 
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Short summary
Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
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