Research article
18 Jun 2018
Research article
| 18 Jun 2018
Hydrostratigraphic modeling using multiple-point statistics and airborne transient electromagnetic methods
Adrian A. S. Barfod et al.
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Cited
18 citations as recorded by crossref.
- The influence of layer and voxel geological modelling strategy on groundwater modelling results T. Enemark et al. 10.1007/s10040-021-02442-9
- 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
- A Tree‐Based Direct Sampling Method for Stochastic Surface and Subsurface Hydrological Modeling C. Zuo et al. 10.1029/2019WR026130
- AEM in Norway: A Review of the Coverage, Applications and the State of Technology E. Harrison et al. 10.3390/rs13224687
- Exploring the Model Space of Airborne Electromagnetic Data to Delineate Large‐Scale Structure and Heterogeneity Within an Aquifer System S. Kang et al. 10.1029/2021WR029699
- Contributions to uncertainty related to hydrostratigraphic modeling using multiple-point statistics A. Barfod et al. 10.5194/hess-22-5485-2018
- 3D Geological Image Synthesis From 2D Examples Using Generative Adversarial Networks G. Coiffier et al. 10.3389/frwa.2020.560598
- Hybrid Seismic-Electrical Data Acquisition Station Based on Cloud Technology and Green IoT S. Qiao et al. 10.1109/ACCESS.2020.2966510
- Choosing between Gaussian and MPS simulation: the role of data information content—a case study using uncertain interpretation data points R. Madsen et al. 10.1007/s00477-020-01954-2
- Restoring groundwater levels after tunneling: a numerical simulation approach to tunnel sealing decision-making M. Golian et al. 10.1007/s10040-021-02315-1
- Grounded electrical source ground–airborne transient electromagnetic modelling with fictitious wave field methods X. Meng et al. 10.1007/s12040-020-01391-3
- Integration of Soft Data Into Geostatistical Simulation of Categorical Variables S. Carle & G. Fogg 10.3389/feart.2020.565707
- Combining Hydraulic Head Analysis with Airborne Electromagnetics to Detect and Map Impermeable Aquifer Boundaries J. Korus 10.3390/w10080975
- Assessment of Managed Aquifer Recharge Sites Using a New Geophysical Imaging Method A. Behroozmand et al. 10.2136/vzj2018.10.0184
- Entropy and Information Content of Geostatistical Models T. Hansen 10.1007/s11004-020-09876-z
- 3D multiple-point statistics simulations of the Roussillon Continental Pliocene aquifer using DeeSse V. Dall'Alba et al. 10.5194/hess-24-4997-2020
- Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions H. Wainwright et al. 10.5194/hess-26-429-2022
- GeoStats.jl – High-performance geostatistics in Julia J. Hoffimann^[Corresponding author: juliohm@stanford.edu] 10.21105/joss.00692
17 citations as recorded by crossref.
- The influence of layer and voxel geological modelling strategy on groundwater modelling results T. Enemark et al. 10.1007/s10040-021-02442-9
- 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
- A Tree‐Based Direct Sampling Method for Stochastic Surface and Subsurface Hydrological Modeling C. Zuo et al. 10.1029/2019WR026130
- AEM in Norway: A Review of the Coverage, Applications and the State of Technology E. Harrison et al. 10.3390/rs13224687
- Exploring the Model Space of Airborne Electromagnetic Data to Delineate Large‐Scale Structure and Heterogeneity Within an Aquifer System S. Kang et al. 10.1029/2021WR029699
- Contributions to uncertainty related to hydrostratigraphic modeling using multiple-point statistics A. Barfod et al. 10.5194/hess-22-5485-2018
- 3D Geological Image Synthesis From 2D Examples Using Generative Adversarial Networks G. Coiffier et al. 10.3389/frwa.2020.560598
- Hybrid Seismic-Electrical Data Acquisition Station Based on Cloud Technology and Green IoT S. Qiao et al. 10.1109/ACCESS.2020.2966510
- Choosing between Gaussian and MPS simulation: the role of data information content—a case study using uncertain interpretation data points R. Madsen et al. 10.1007/s00477-020-01954-2
- Restoring groundwater levels after tunneling: a numerical simulation approach to tunnel sealing decision-making M. Golian et al. 10.1007/s10040-021-02315-1
- Grounded electrical source ground–airborne transient electromagnetic modelling with fictitious wave field methods X. Meng et al. 10.1007/s12040-020-01391-3
- Integration of Soft Data Into Geostatistical Simulation of Categorical Variables S. Carle & G. Fogg 10.3389/feart.2020.565707
- Combining Hydraulic Head Analysis with Airborne Electromagnetics to Detect and Map Impermeable Aquifer Boundaries J. Korus 10.3390/w10080975
- Assessment of Managed Aquifer Recharge Sites Using a New Geophysical Imaging Method A. Behroozmand et al. 10.2136/vzj2018.10.0184
- Entropy and Information Content of Geostatistical Models T. Hansen 10.1007/s11004-020-09876-z
- 3D multiple-point statistics simulations of the Roussillon Continental Pliocene aquifer using DeeSse V. Dall'Alba et al. 10.5194/hess-24-4997-2020
- Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions H. Wainwright et al. 10.5194/hess-26-429-2022
1 citations as recorded by crossref.
Latest update: 08 Aug 2022
Short summary
Three-dimensional geological models are important to securing and managing groundwater. Such models describe the geological architecture, which is used for modeling the flow of groundwater. Common geological modeling approaches result in one model, which does not quantify the architectural uncertainty of the geology.
We present a comparison of three different state-of-the-art stochastic multiple-point statistical methods for quantifying the geological uncertainty using real-world datasets.
Three-dimensional geological models are important to securing and managing groundwater. Such...