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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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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.
HESS | Articles | Volume 22, issue 6
Hydrol. Earth Syst. Sci., 22, 3351–3373, 2018
https://doi.org/10.5194/hess-22-3351-2018
Hydrol. Earth Syst. Sci., 22, 3351–3373, 2018
https://doi.org/10.5194/hess-22-3351-2018

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 articles

Arpat, G. B. and Caers, J.: A multiple-scale, pattern-based approach to sequential simulation, in: Geostatistics Banff 2004, Springer, 255–264, 2005. 
Auken, E., Christiansen, A. V., Westergaard, J. H., Kirkegaard, C., Foged, N., and Viezzoli, A.: An integrated processing scheme for high-resolution airborne electromagnetic surveys, the SkyTEM system, Explor. Geophys., 40, 184–192, 2009. 
Barfod, A. A., Møller, I., and Christiansen, A. V.: Compiling a national resistivity atlas of Denmark based on airborne and ground-based transient electromagnetic data, J. Appl. Geophys., 134, 199–209, https://doi.org/10.1016/j.jappgeo.2016.09.017, 2016. 
Beamish, D.: The bedrock electrical conductivity map of the UK, J. Appl. Geophys., 96, 87–97, 2013. 
Caers, J.: Direct sequential indicator simulation, Geostats, 39–48, 2000. 
Publications Copernicus
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.
Citation