Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6069-2017
https://doi.org/10.5194/hess-21-6069-2017
Research article
 | 
01 Dec 2017
Research article |  | 01 Dec 2017

Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies

Anne-Sophie Høyer, Giulio Vignoli, Thomas Mejer Hansen, Le Thanh Vu, Donald A. Keefer, and Flemming Jørgensen

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Cited articles

Carrera, J.: An overview of uncertainties in modelling groundwater solute transport, J. Contam. Hydrol., 13, 23–48, 1993.
Chiles, J.-P. and Delfiner, P.: Geostatistics: Modeling spatial uncertainty, Wiley, New York, 1999.
Christensen, N. K., Minsley B. J., and Christensen S.: Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error, Water Resour. Res., 53, 1019–1038, 2017.
Christiansen, A. V. and Auken, E.: A global measure for depth of investigation, Geophysics, 77, WB171–WB177, 2012.
Chugunova, T. L. and Hu, L. Y.: Multiple-point simulations constrained by continuous auxiliary data, Math. Geosci., 40, 133–146, 2008.
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Short summary
We present a novel approach for 3-D geostatistical simulations. It includes practical strategies for the development of realistic 3-D training images and for incorporating the diverse geological and geophysical inputs together with their uncertainty levels (due to measurement inaccuracies and scale mismatch). Inputs consist of well logs, seismics, and an existing 3-D geomodel. The simulation domain (45 million voxels) coincides with the Miocene unit over 2810 km2 across the Danish–German border.