Journal of Jilin University(Earth Science Edition) ›› 2017, Vol. 47 ›› Issue (3): 925-932.doi: 10.13278/j.cnki.jjuese.201703306

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Uncertainty Analysis of Geological Boundaries in 3D Cross-Section Based on Monte Carlo Simulation

Hou Weisheng1,2, Yang Qiaochu1,2, Yang Liang1,2, Cui Chanjie1,2   

  1. 1. School of Earth Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China;
    2. Guangdong Provincial Key Laboratory of Mineral Resource Exploration & Geological Processes, Guangzhou 510275, China
  • Received:2016-08-02 Online:2017-05-26 Published:2017-05-26
  • Supported by:
    Supported by the National Natural Science Foundation of China (41102207, 41472300), the Fundamental Research Funds for the Central Universities (12lgpy19) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (20100171120001)

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Abstract: Geological boundaries in 3D cross-sections are important data for constructing 3D geological models, and their uncertainties will affect the geometry and attributes distribution in final models. The approaches based on the assumption of single error distribution for uncertainty analysis cover up other characteristics caused by other different error distributions. To break the single error distribution assumptions, based on the Monte Carlo simulation method, this paper simulated the sampling acquisition with different error probability distributions and spatial uncertainty of geological boundaries in 3D geological cross-section. Based on the coupling relationship between spatial position and geological attributes, a term of "geological attribute probability" was proposed to quantitatively visualize uncertainty of geological boundaries. Combined with concrete geological cross-section, this paper discussed the spatial uncertainty distribution of geological boundaries that followed multiple error probability distribution functions. The concrete example shows that the presented approach can overcome the defects of single error distribution assumption. Combined with the geological attribute probability, the approach can also reveal the coupling relationship between inner uncertainties existed in modeling input data and feature shape of models.

Key words: uncertainty analysis, Monte Carlo simulation, geological boundaries, geological attribute probability, 3D geological cross-section

CLC Number: 

  • P628.1
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