Articles | Volume 18, issue 8
https://doi.org/10.5194/hess-18-2943-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-2943-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Aug 2014
Research article |
| 07 Aug 2014
The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling
Department of Geosciences and Natural Resource Management, Copenhagen University, Copenhagen, Denmark
T. O. Sonnenborg
Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
F. Jørgensen
Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
K. H. Jensen
Department of Geosciences and Natural Resource Management, Copenhagen University, Copenhagen, Denmark
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18 citations as recorded by crossref.
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- Hydrogeological conceptual model building and testing: A review T. Enemark et al. 10.1016/j.jhydrol.2018.12.007
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. 10.5194/hess-25-2759-2021
- CHDS: conflict handling in direct sampling for stochastic simulation of spatial variables H. Soltan Mohammadi et al. 10.1007/s00477-020-01801-4
- Combining 3D geological modelling techniques to address variations in geology, data type and density – An example from Southern Denmark F. Jørgensen et al. 10.1016/j.cageo.2015.04.010
- Combining Clustering Methods With MPS to Estimate Structural Uncertainty for Hydrological Models T. Vilhelmsen et al. 10.3389/feart.2019.00181
- Fracture-vuggy carbonate reservoir characterization based on multiple geological information fusion Y. Wang et al. 10.3389/feart.2023.1345028
- Three-dimensional geological modelling of AEM resistivity data — A comparison of three methods A. Høyer et al. 10.1016/j.jappgeo.2015.02.005
- Integrating deterministic lithostratigraphic models in stochastic realizations of subsurface heterogeneity. Impact on predictions of lithology, hydraulic heads and groundwater fluxes M. Bianchi et al. 10.1016/j.jhydrol.2015.10.072
- Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections Q. Chen et al. 10.5194/hess-22-6547-2018
- An integrated approach to lithofacies characterization of a sandstone reservoir using the Single Normal Simulation equation: A Case study M. Nagendra Babu et al. 10.1016/j.petrol.2021.109626
- Multiple point statistical simulation using uncertain (soft) conditional data T. Hansen et al. 10.1016/j.cageo.2018.01.017
- Quantifying spatial uncertainty in rock through geostatistical integration of borehole data and a geologist's cross-section D. Boyd et al. 10.1016/j.enggeo.2019.105246
- Multiple-point statistical modeling of three-dimensional glacial aquifer heterogeneity for improved groundwater management N. Kawo et al. 10.1007/s10040-023-02658-x
- Simulation of Earth textures by conditional image quilting K. Mahmud et al. 10.1002/2013WR015069
- PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization M. Pourfard et al. 10.1016/j.cageo.2016.12.012
- Integrating multiple scales of hydraulic conductivity measurements in training image-based stochastic models K. Mahmud et al. 10.1002/2014WR016150
15 citations as recorded by crossref.
- Modelling a real-world buried valley system with vertical non-stationarity using multiple-point statistics X. He et al. 10.1007/s10040-016-1486-8
- Smart Interpretation – automatic geological interpretations based on supervised statistical models M. Gulbrandsen et al. 10.1007/s10596-017-9621-8
- Hydrogeological conceptual model building and testing: A review T. Enemark et al. 10.1016/j.jhydrol.2018.12.007
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. 10.5194/hess-25-2759-2021
- CHDS: conflict handling in direct sampling for stochastic simulation of spatial variables H. Soltan Mohammadi et al. 10.1007/s00477-020-01801-4
- Combining 3D geological modelling techniques to address variations in geology, data type and density – An example from Southern Denmark F. Jørgensen et al. 10.1016/j.cageo.2015.04.010
- Combining Clustering Methods With MPS to Estimate Structural Uncertainty for Hydrological Models T. Vilhelmsen et al. 10.3389/feart.2019.00181
- Fracture-vuggy carbonate reservoir characterization based on multiple geological information fusion Y. Wang et al. 10.3389/feart.2023.1345028
- Three-dimensional geological modelling of AEM resistivity data — A comparison of three methods A. Høyer et al. 10.1016/j.jappgeo.2015.02.005
- Integrating deterministic lithostratigraphic models in stochastic realizations of subsurface heterogeneity. Impact on predictions of lithology, hydraulic heads and groundwater fluxes M. Bianchi et al. 10.1016/j.jhydrol.2015.10.072
- Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections Q. Chen et al. 10.5194/hess-22-6547-2018
- An integrated approach to lithofacies characterization of a sandstone reservoir using the Single Normal Simulation equation: A Case study M. Nagendra Babu et al. 10.1016/j.petrol.2021.109626
- Multiple point statistical simulation using uncertain (soft) conditional data T. Hansen et al. 10.1016/j.cageo.2018.01.017
- Quantifying spatial uncertainty in rock through geostatistical integration of borehole data and a geologist's cross-section D. Boyd et al. 10.1016/j.enggeo.2019.105246
- Multiple-point statistical modeling of three-dimensional glacial aquifer heterogeneity for improved groundwater management N. Kawo et al. 10.1007/s10040-023-02658-x
3 citations as recorded by crossref.
- Simulation of Earth textures by conditional image quilting K. Mahmud et al. 10.1002/2013WR015069
- PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization M. Pourfard et al. 10.1016/j.cageo.2016.12.012
- Integrating multiple scales of hydraulic conductivity measurements in training image-based stochastic models K. Mahmud et al. 10.1002/2014WR016150
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