Articles | Volume 22, issue 12
https://doi.org/10.5194/hess-22-6547-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-6547-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections
Qiyu Chen
School of Computer Science, China University of Geosciences, Wuhan 430074, China
Institute of Earth Surface Dynamics, University of Lausanne, 1015 Lausanne, Switzerland
Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430074, China
Gregoire Mariethoz
Institute of Earth Surface Dynamics, University of Lausanne, 1015 Lausanne, Switzerland
Gang Liu
CORRESPONDING AUTHOR
School of Computer Science, China University of Geosciences, Wuhan 430074, China
Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430074, China
Alessandro Comunian
Dipartimento di Scienze della Terra “A. Desio”, Università degli Studi di Milano, Milan, Italy
Xiaogang Ma
Department of Computer Science, University of Idaho, 875 Perimeter Drive MS 1010, Moscow, ID 83844-1010, USA
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Latest update: 12 Oct 2024
Short summary
One of the critical issues in MPS simulation is the difficulty in obtaining a credible 3-D training image. We propose an MPS-based 3-D reconstruction method on the basis of 2-D cross sections, making 3-D training images unnecessary. The main advantages of this approach are the high computational efficiency and a relaxation of the stationarity assumption. The results, in comparison with previous MPS methods, show better performance in portraying anisotropy characteristics and in CPU cost.
One of the critical issues in MPS simulation is the difficulty in obtaining a credible 3-D...