105 citations as recorded by crossref.

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2. Integrating Deep Learning and Deterministic Inversion for Enhancing Fault Detection in Electrical Resistivity Surveys S. Kong et al. 10.3390/app13106250
3. Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit N. Güdük et al. 10.3390/geosciences11040150
4. Impact of In-Situ Density Spatial Model Methods on Resource Tonnages in Highly Intruded Coal Deposits K. Maxwell et al. 10.1007/s11053-021-09989-0
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7. Subdivide and Conquer: Adapting Non-Manifold Subdivision Surfaces to Surface-Based Representation and Reconstruction of Complex Geological Structures M. Moulaeifard et al. 10.1007/s11004-022-10017-x
8. Towards the geological parametrization of seismic tomography V. Tsai et al. 10.1093/gji/ggad140
9. Estimation of Aquifer Storativity Using 3D Geological Modeling and the Spatial Random Bagging Simulation Method: The Saskatchewan River Basin Case Study (Central Canada) M. Hamdi & K. Goïta 10.3390/w15061156
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12. Modelling of faults in LoopStructural 1.0 L. Grose et al. 10.5194/gmd-14-6197-2021
13. Geodynamic Modeling With Uncertain Initial Geometries A. Spang et al. 10.1029/2021GC010265
14. Impact of structural uncertainty on tracer test design in faulted geothermal reservoirs A. Dashti et al. 10.1016/j.geothermics.2022.102607
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17. Uncertainty assessment for 3D geologic modeling of fault zones based on geologic inputs and prior knowledge A. Krajnovich et al. 10.5194/se-11-1457-2020
18. Lithospheric strength and elastic properties for Mars from InSight geophysical data K. Crane & J. Rich 10.1016/j.icarus.2023.115581
19. 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
20. Incremental Emplacement of the Sierra Nevada Batholith Constrained by U-Pb Ages and Potential Field Data H. Sehsah et al. 10.1086/722724
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24. Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models H. Olierook et al. 10.1016/j.gsf.2020.04.015
25. Actors, actions, and uncertainties: optimizing decision-making based on 3-D structural geological models F. Stamm et al. 10.5194/se-10-2015-2019
26. Knowledge-driven stochastic modeling of geological geometry features conditioned on drillholes and outcrop contacts X. Wei et al. 10.1016/j.cageo.2024.105779
27. Modeling the Uncertainty in the Layout of Geological Units by Implicit Boundary Simulation Accounting for a Preexisting Interpretive Geological Model R. Ferrer et al. 10.1007/s11053-021-09964-9
28. An integrated modeling scheme for characterizing 3D hydrogeological heterogeneity of the New Jersey shelf A. Thomas et al. 10.1007/s11001-022-09475-z
29. Estimating uncertainties in 3-D models of complex fold-and-thrust belts: A case study of the Eastern Alps triangle zone S. Brisson et al. 10.1016/j.acags.2023.100115
30. Towards a workflow to evaluate geological layering uncertainty onCO2injection simulation C. Legentil et al. 10.1016/j.acags.2023.100118
31. Deformation scale using harmonic curvature analysis: A case study from the Hamersley Province D. Nathan et al. 10.1016/j.jsg.2021.104302
32. GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling M. Hillier et al. 10.5194/gmd-16-6987-2023
33. PySubdiv 1.0: open-source geological modeling and reconstruction by non-manifold subdivision surfaces M. Moulaeifard et al. 10.5194/gmd-16-3565-2023
34. 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
35. Efficiency and robustness in Monte Carlo sampling for 3-D geophysical inversions with Obsidian v0.1.2: setting up for success R. Scalzo et al. 10.5194/gmd-12-2941-2019
36. GeoBO: Python package for Multi-Objective Bayesian Optimisation and Joint Inversion in Geosciences S. Haan 10.21105/joss.02690
37. An algorithm for identifying stratigraphic piles from interpreted boreholes L. Schorpp et al. 10.3389/feart.2024.1461658
38. The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials P. Ghamisi et al. 10.1109/JSTARS.2021.3108049
39. 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
40. An automatic geological 3D cross-section generator: Geopropy, an open-source library A. Hassanzadeh et al. 10.1016/j.envsoft.2022.105309
41. Variational Gaussian processes for implicit geological modeling Í. Gonçalves et al. 10.1016/j.cageo.2023.105323
42. Combining implicit geological modeling, field surveys, and hydrogeological modeling to describe groundwater flow in a karst aquifer F. D’Affonseca et al. 10.1007/s10040-020-02220-z
43. A greedy sensor selection algorithm for hyperparameterized linear Bayesian inverse problems with correlated noise models N. Aretz et al. 10.1016/j.jcp.2023.112599
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45. Constraining 3D geometric gravity inversion with a 2D reflection seismic profile using a generalized level set approach: application to the eastern Yilgarn Craton M. Rashidifard et al. 10.5194/se-12-2387-2021
46. 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
47. GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data J. Guo et al. 10.5194/gmd-17-957-2024
48. The Geodynamic World Builder: A planetary structure creator for the geosciences M. Fraters et al. 10.21105/joss.06671
49. Automated Hierarchical 3D Modeling of Quaternary Aquifers: The ArchPy Approach L. Schorpp et al. 10.3389/feart.2022.884075
50. 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
51. Virtual Reality Modelling of Garden Geography and Geology Based on 3D Modelling Technology Q. Zhang 10.1088/1742-6596/1952/2/022053
52. 3D simulation of complex fractures with a simple mesh J. Wu 10.1002/nme.6986
53. Characteristics and controls of an offshore freshened groundwater system in the Shengsi region, East China Sea A. Thomas et al. 10.3389/feart.2023.1198215
54. Integrated framework for geological modeling: integration of data, knowledge, and methods H. Li et al. 10.1007/s10064-024-03794-8
55. LoopStructural 1.0: time-aware geological modelling L. Grose et al. 10.5194/gmd-14-3915-2021
56. A Scenario-Based Simulation Model for Earthwork Cost Management Using Unmanned Aerial Vehicle Technology T. Rachmawati et al. 10.3390/su15010503
57. Geophysical model generation with generative adversarial networks V. Puzyrev et al. 10.1186/s40562-022-00241-y
58. 3D Modeling of Large-Scale Geological Structures by Linear Combinations of Implicit Functions: Application to a Large Banded Iron Formation L. Yang et al. 10.1007/s11053-021-09901-w
59. Uncertainties and robustness with regard to the safety of a repository for high-level radioactive waste: introduction of a research initiative K. Kurgyis et al. 10.1007/s12665-023-11346-8
60. Unraveling the uncertainty of geological interfaces through data-knowledge-driven trend surface analysis L. Wang et al. 10.1016/j.cageo.2023.105419
61. Bedding Scale Correlation on Mars in Western Arabia Terra A. Annex et al. 10.1029/2023JE007776
62. 3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models G. Piris et al. 10.3390/en14217338
63. Can Agents Model Hydrocarbon Migration for Petroleum System Analysis? A Fast Screening Tool to De-Risk Hydrocarbon Prospects B. Steffens et al. 10.3390/en15030902
64. Towards an open-source landscape for 3-D CSEM modelling D. Werthmüller et al. 10.1093/gji/ggab238
65. Horizon-assisted lithologic modeling: understanding Mississippi Embayment and Coastal Lowlands aquifer systems in Louisiana and southwestern Mississippi, USA S. Yang et al. 10.1007/s10040-024-02804-z
66. Implicit modelling and dynamic update of tunnel unfavourable geology based on multi-source data fusion using support vector machine B. Yang et al. 10.1080/17499518.2023.2239778
67. Three-dimensional hydrogeological parametrization using sparse piezometric data D. Rambourg et al. 10.5194/hess-26-6147-2022
68. Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0) Z. Yin et al. 10.5194/gmd-13-651-2020
69. Spatial agents for geological surface modelling E. de Kemp 10.5194/gmd-14-6661-2021
70. 2.5-D Deep Learning Inversion of LWD and Deep-Sensing EM Measurements Across Formations With Dipping Faults K. Noh et al. 10.1109/LGRS.2021.3128965
71. Developing a 3D hydrostratigraphical model of the emerged part of the Pelotas Basin along the northern coast of Rio Grande do Sul state, Brazil L. Marquetto et al. 10.1007/s12665-024-11609-y
72. Modelo estructural estocástico de bofedal mediante interpolación 3D de las conductividades eléctricas con gempy, microcuenca apacheta, 2021. J. Huaman Musaja 10.57063/ricay.v3i2.95
73. A probabilistic geologic model of the Krafla geothermal system constrained by gravimetric data S. Scott et al. 10.1186/s40517-019-0143-6
74. Integration of automatic implicit geological modelling in deterministic geophysical inversion J. Giraud et al. 10.5194/se-15-63-2024
75. Integrated Geologic Modeling of Fault-Block Reservoir: A Case Study of Ss Oil Field Z. Xiao et al. 10.1155/2022/6864786
76. Delineation of LNAPL plumes in a clay-rich site in Gyeongsangnam-do Province, South Korea: integration of geophysical survey data with borehole data and soil sampling information B. Kim et al. 10.1007/s10661-023-12202-9
77. Constraining stochastic 3-D structural geological models with topology information using approximate Bayesian computation in GemPy 2.1 A. Schaaf et al. 10.5194/gmd-14-3899-2021
78. Maximising the value of hyperspectral drill core scanning through real-time processing and analysis S. Thiele et al. 10.3389/feart.2024.1433662
79. Towards automatic and rapid 3D geological modelling of urban sedimentary strata from a large amount of borehole data using a parallel solution of implicit equations X. Wang et al. 10.1007/s12145-023-01164-8
80. Using an Open-Source Tool to Develop a Three-Dimensional Hydrogeologic Framework of the Kobo Valley, Ethiopia S. Mekonen et al. 10.3390/geosciences14010003
81. Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study A. Pollack et al. 10.1016/j.geothermics.2021.102129
82. Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles C. Fandel et al. 10.5194/hess-27-4205-2023
83. A method to construct statistical prior models of geology for probabilistic inversion of geophysical data R. Madsen et al. 10.1016/j.enggeo.2023.107252
84. A machine learning model for structural trend fields Í. Gonçalves et al. 10.1016/j.cageo.2021.104715
85. 数据和知识融合的Bayesian-MCMC三维地质建模 L. Wang et al. 10.3799/dqkx.2023.069
86. Geophysical tomography as a tool to estimate the geometry of soil layers: relevance for the reliability assessment of dikes J. Chavez Olalla et al. 10.1080/17499518.2021.1971252
87. Estimation of CO 2 saturation maps from synthetic seismic data using a deep-learning method with a multi-scale approach G. Pantaleo et al. 10.1144/geoenergy2023-057
88. GeophysicalModelGenerator.jl: A Julia package to visualise geoscientific data and create numerical model setups B. Kaus et al. 10.21105/joss.06763
89. A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China B. Zhang et al. 10.1016/j.oregeorev.2023.105788
90. Efficient geo-electromagnetic modeling techniques for complex geological structures: A karst MT example M. Liu et al. 10.1016/j.cageo.2024.105557
91. A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstration T. Sun & S. Grimmond 10.5194/gmd-12-2781-2019
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93. Construction and Usefulness Verification of Modeling Method of Subsurface Soil Layers for Numerical Analysis of Urban Area Ground Motion H. Motoyama & M. Hori 10.3390/geohazards3020013
94. From Maps to Models - Tutorials for structural geological modeling using GemPy and GemGIS A. Jüstel et al. 10.21105/jose.00185
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