Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3915-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3915-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
29 Jun 2021
Development and technical paper |
| 29 Jun 2021
| 29 Jun 2021
LoopStructural 1.0: time-aware geological modelling
Lachlan Grose
CORRESPONDING AUTHOR
School of Earth Atmosphere and Environment, Monash University,
Melbourne 3800, Australia
Laurent Ailleres
School of Earth Atmosphere and Environment, Monash University,
Melbourne 3800, Australia
Gautier Laurent
Université d'Orléans, CNRS, BRGM, ISTO, UMR 7327, Orleans,
France
Mark Jessell
Mineral Exploration Cooperative Research Centre, School of Earth
Sciences, UWA, Perth 6907, Australia
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- Unraveling the uncertainty of geological interfaces through data-knowledge-driven trend surface analysis L. Wang et al. 10.1016/j.cageo.2023.105419
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- Structural Modeling Based on Human–Computer Knowledge Interaction X. Zhan et al. 10.1007/s11770-023-1017-z
- Bayesian fusion of MT and AEM probabilistic models with geological data: examples from the eastern Gawler Craton, South Australia H. Seillé et al. 10.1080/08123985.2023.2222766
- Integration of automatic implicit geological modelling in deterministic geophysical inversion J. Giraud et al. 10.5194/se-15-63-2024
- Assessing the impact of conceptual mineral systems uncertainty on prospectivity predictions M. Lindsay et al. 10.1016/j.gsf.2022.101435
- Integrated framework for geological modeling: integration of data, knowledge, and methods H. Li et al. 10.1007/s10064-024-03794-8
- Three-dimensional geological modelling of igneous intrusions in LoopStructural v1.5.10 F. Alvarado-Neves et al. 10.5194/gmd-17-1975-2024
- The influence of variable anisotropic search parameters on implicitly-modelled volumes and estimated contained metal in a structurally-complex gold deposit B. Stoch et al. 10.1016/j.oregeorev.2022.104719
- Progressive Geological Modeling and Uncertainty Analysis Using Machine Learning H. Li et al. 10.3390/ijgi12030097
- Regional-scale 3D modelling in metamorphic belts: An implicit model-driven workflow applied in the Pennine Alps G. Arienti et al. 10.1016/j.jsg.2023.105045
- Spatial agents for geological surface modelling E. de Kemp 10.5194/gmd-14-6661-2021
- Modelling of faults in LoopStructural 1.0 L. Grose et al. 10.5194/gmd-14-6197-2021
- Three-Dimensional Geologic Modeling of the Kiruna Mining District, Sweden: Insights into the Crustal Architecture and Structural Controls on Iron Oxide-Apatite Mineralization E. Veress et al. 10.5382/econgeo.5080
- Impact of permeability anisotropy misalignment on flow rates predicted by hydrogeological models T. Poulet et al. 10.1007/s10040-023-02708-4
- AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling B. Zhang et al. 10.5194/gmd-16-3651-2023
- The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials P. Ghamisi et al. 10.1109/JSTARS.2021.3108049
- 3D structural modeling for seismic exploration based on knowledge graphs X. Zhan et al. 10.1190/geo2020-0924.1
- A new methodology using borehole data to measure angular distances between geological interfaces M. Michalak et al. 10.1007/s12145-023-01015-6
- Automated geological map deconstruction for 3D model construction using <i>map2loop</i> 1.0 and <i>map2model</i> 1.0 M. Jessell et al. 10.5194/gmd-14-5063-2021
- Utilisation of probabilistic magnetotelluric modelling to constrain magnetic data inversion: proof-of-concept and field application J. Giraud et al. 10.5194/se-14-43-2023
- Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models R. Scalzo et al. 10.5194/gmd-15-3641-2022
- Variational Gaussian processes for implicit geological modeling Í. Gonçalves et al. 10.1016/j.cageo.2023.105323
- GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling M. Hillier et al. 10.5194/gmd-16-6987-2023
- Cooperative geophysical inversion integrated with 3-D geological modelling in the Boulia region, QLD M. Rashidifard et al. 10.1093/gji/ggae179
- Structural Uncertainty Due to Fault Timing: A Multimodel Case Study from the Perth Basin K. Bardot et al. 10.1111/gwat.13429
- loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification G. Pirot et al. 10.5194/gmd-15-4689-2022
- LoopStructural 1.0: time-aware geological modelling L. Grose et al. 10.5194/gmd-14-3915-2021
27 citations as recorded by crossref.
- Unraveling the uncertainty of geological interfaces through data-knowledge-driven trend surface analysis L. Wang et al. 10.1016/j.cageo.2023.105419
- Towards a workflow to evaluate geological layering uncertainty on CO2 injection simulation C. Legentil et al. 10.1016/j.acags.2023.100118
- Structural Modeling Based on Human–Computer Knowledge Interaction X. Zhan et al. 10.1007/s11770-023-1017-z
- Bayesian fusion of MT and AEM probabilistic models with geological data: examples from the eastern Gawler Craton, South Australia H. Seillé et al. 10.1080/08123985.2023.2222766
- Integration of automatic implicit geological modelling in deterministic geophysical inversion J. Giraud et al. 10.5194/se-15-63-2024
- Assessing the impact of conceptual mineral systems uncertainty on prospectivity predictions M. Lindsay et al. 10.1016/j.gsf.2022.101435
- Integrated framework for geological modeling: integration of data, knowledge, and methods H. Li et al. 10.1007/s10064-024-03794-8
- Three-dimensional geological modelling of igneous intrusions in LoopStructural v1.5.10 F. Alvarado-Neves et al. 10.5194/gmd-17-1975-2024
- The influence of variable anisotropic search parameters on implicitly-modelled volumes and estimated contained metal in a structurally-complex gold deposit B. Stoch et al. 10.1016/j.oregeorev.2022.104719
- Progressive Geological Modeling and Uncertainty Analysis Using Machine Learning H. Li et al. 10.3390/ijgi12030097
- Regional-scale 3D modelling in metamorphic belts: An implicit model-driven workflow applied in the Pennine Alps G. Arienti et al. 10.1016/j.jsg.2023.105045
- Spatial agents for geological surface modelling E. de Kemp 10.5194/gmd-14-6661-2021
- Modelling of faults in LoopStructural 1.0 L. Grose et al. 10.5194/gmd-14-6197-2021
- Three-Dimensional Geologic Modeling of the Kiruna Mining District, Sweden: Insights into the Crustal Architecture and Structural Controls on Iron Oxide-Apatite Mineralization E. Veress et al. 10.5382/econgeo.5080
- Impact of permeability anisotropy misalignment on flow rates predicted by hydrogeological models T. Poulet et al. 10.1007/s10040-023-02708-4
- AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling B. Zhang et al. 10.5194/gmd-16-3651-2023
- The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials P. Ghamisi et al. 10.1109/JSTARS.2021.3108049
- 3D structural modeling for seismic exploration based on knowledge graphs X. Zhan et al. 10.1190/geo2020-0924.1
- A new methodology using borehole data to measure angular distances between geological interfaces M. Michalak et al. 10.1007/s12145-023-01015-6
- Automated geological map deconstruction for 3D model construction using <i>map2loop</i> 1.0 and <i>map2model</i> 1.0 M. Jessell et al. 10.5194/gmd-14-5063-2021
- Utilisation of probabilistic magnetotelluric modelling to constrain magnetic data inversion: proof-of-concept and field application J. Giraud et al. 10.5194/se-14-43-2023
- Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models R. Scalzo et al. 10.5194/gmd-15-3641-2022
- Variational Gaussian processes for implicit geological modeling Í. Gonçalves et al. 10.1016/j.cageo.2023.105323
- GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling M. Hillier et al. 10.5194/gmd-16-6987-2023
- Cooperative geophysical inversion integrated with 3-D geological modelling in the Boulia region, QLD M. Rashidifard et al. 10.1093/gji/ggae179
- Structural Uncertainty Due to Fault Timing: A Multimodel Case Study from the Perth Basin K. Bardot et al. 10.1111/gwat.13429
- loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification G. Pirot et al. 10.5194/gmd-15-4689-2022
1 citations as recorded by crossref.
Latest update: 17 Jul 2024
Short summary
LoopStructural is an open-source 3D geological modelling library with a model design allowing for multiple different algorithms to be used for comparison for the same geology. Geological structures are modelled using structural geology concepts and techniques, allowing for complex structures such as overprinted folds and faults to be modelled. In the paper, we demonstrate automatically generating a 3-D model from map2loop-processed geological survey data of the Flinders Ranges, South Australia.
LoopStructural is an open-source 3D geological modelling library with a model design allowing...
