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Multiple-point geostatistical simulation based on conditional conduction probability

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Abstract

Multiple-point geostatistical (MPS) simulation can enhance extraction and synthesis of various information in earth and environmental sciences. In particular, it is able to characterize the complex spatial structures of heterogeneous phenomena more accurately. In this paper, we propose a new MPS simulation method based on conditional conduction probability, namely the CCPSIM algorithm, to mitigate the uncertainty of MPS realizations. In CCPSIM, the simulated nodes will be treated differently from the original samples. The probability distributions of the simulated nodes will be used as prior conditions to calculate the probability distributions of the following nodes, and the prior conditions will be conducted during the whole simulation process. 2D and 3D synthetic tests are used to verify the applicability and advantages of CCPSIM. The results confirm that CCPSIM is able to reproduce spatial patterns of heterogeneous structures presented in categorical training images, and it reduces the uncertainty of the MPS realizations caused by the undistinguished using of the original known samples and the simulated uncertain values.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (41902304, U1711267, 41942039) and the Open Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing (KLIGIP-2018B05), Opening Fund of KLGSE and the Fundamental Research Funds for the Central Universities (CUG2019ZR03, CUGCJ1810). The source code in C++ is available on request from the corresponding author (qiyu.chen@cug.edu.cn).

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Authors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, 430074, China

    Zhesi Cui, Qiyu Chen & Gang Liu

  2. Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, 430074, China

    Zhesi Cui, Qiyu Chen & Gang Liu

  3. Department of Computer Science, University of Idaho, 875 Perimeter Drive MS 1010, Moscow, ID, 83844-1010, USA

    Xiaogang Ma

  4. Computer and Information College, Fujian Agriculture and Forestry University, Fuzhou, 350002, China

    Xiang Que

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  1. Zhesi Cui
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  2. Qiyu Chen
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  3. Gang Liu
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  5. Xiang Que
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Correspondence to Qiyu Chen or Gang Liu.

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Cui, Z., Chen, Q., Liu, G. et al. Multiple-point geostatistical simulation based on conditional conduction probability. Stoch Environ Res Risk Assess 35, 1355–1368 (2021). https://doi.org/10.1007/s00477-020-01944-4

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