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    一种基于物性数据的深部三维地质建模方法

    余翔宇 徐义贤

    余翔宇, 徐义贤, 2015. 一种基于物性数据的深部三维地质建模方法. 地球科学, 40(3): 419-424. doi: 10.3799/dqkx.2015.033
    引用本文: 余翔宇, 徐义贤, 2015. 一种基于物性数据的深部三维地质建模方法. 地球科学, 40(3): 419-424. doi: 10.3799/dqkx.2015.033
    Yu Xiangyu, Xu Yixian, 2015. A 3D Geological Modeling Method Based on Geophysical Data. Earth Science, 40(3): 419-424. doi: 10.3799/dqkx.2015.033
    Citation: Yu Xiangyu, Xu Yixian, 2015. A 3D Geological Modeling Method Based on Geophysical Data. Earth Science, 40(3): 419-424. doi: 10.3799/dqkx.2015.033

    一种基于物性数据的深部三维地质建模方法

    doi: 10.3799/dqkx.2015.033
    基金项目: 

    中国地质调查项目“西准噶尔克拉玛依后山地区深部地质调查试点” 1212011220245

    中央高校基本科研业务费专项 CUGL130208

    详细信息
      作者简介:

      余翔宇(1979-), 男, 博士, 主要从事数据三维可视化, 地球物理解释模型方面研究.E-mail: yuxiangyu@sina.com

    • 中图分类号: TP391

    A 3D Geological Modeling Method Based on Geophysical Data

    • 摘要: 地质采样信息不足是制约深部三维地质建模的重要因素, 深部物性探测数据由于其易于获取而能够有效形成可视化模型.结合这一特点, 在地质调查项目工作中探索出了一种基于物性探测数据的三维地质建模方法.它首先利用岩石样品物性测量实验数据提取出物性参数及其对应地质属性的映射关系, 然后将不同地球物理方法所获取到的物性数据进行综合建模并解释, 最后将解释后的可视化模型转换为地质三维模型.实践证明, 该方法能够针对性地解决项目中的一些深部地质三维建模问题.

       

    • 图  1  实现流程

      Fig.  1.  Implementation process

      图  2  信息粒解释模型结构

      Fig.  2.  Structure of information grade (IG) interpretation model

      图  3  密度和磁化率可视化模型

      Fig.  3.  Visualization models of density and magnetic susceptibility

      图  4  格网点地质属性

      Fig.  4.  Geological property in grid points

      图  5  格网单元分解

      Fig.  5.  Grid cell decomposition

      图  6  岩性三维地质模型

      Fig.  6.  3D geological model of lithology

      表  1  样品实验数据示例

      Table  1.   A case of the experimental data

      属性 属性值
      密度(g/cm3) 2.628 7
      磁化率(10-6) 18.800 0
      电阻率(Ω·m) 4 842.850 0
      极化率(%) 0.890 1
      岩性 紫红色硅质岩
      下载: 导出CSV

      表  2  几种方法比较结果

      Table  2.   The comparison result of several methods

      方法 正确率(%) 收敛速度 稳定性
      信息粒模型 87.4 较快
      模糊聚类 83.6
      硬聚类 78.8
      神经网络 81.6
      支持向量机 86.5 较快
      下载: 导出CSV
    • Gong, J.Y., Cheng, P.G., Wang, Y.D., 2004. Three-Dimensional Modeling and Application in Geological Exploration Engineering. Computers & Geosciences, 30(4): 391-404. doi: 10.1016/j.cageo.2003.06.003
      Huang, W., Ding, L.X., Oh, S.K., et al., 2010. Identification of Fuzzy Inference System Based on Information Granulation. KSII Transactions on Internet and Information Systems, 4(4): 575-594.
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      Trampert, J., van der Hilst, R.D., 2005. Towards a Quantitative Interpretation of Global Seismic Tomography. Geophysical Monograph Series, 160(1): 47-64. doi: 10.1029/160GM05
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      Wu, Q., Xu, H., Zou, X.K., 2005. An Effective Method for 3D Geological Modeling with Multi-Source Data Integration. Computers & Geosciences, 31(1): 35-43. doi: 10.1016/j.cageo.2004.09.005
      Xu, H.B., Li, R., Zou, W., et al., 2006. Lithologic Recognition with Fuzzy Clustering. Chinese Journal of Computing Techniques for Geophysical and Geochemical Exploration, 28(4): 319-322 (in Chinese with English abstract). http://www.researchgate.net/publication/289895822_Lithologic_recognition_with_fuzzy_clustering
      Yao, Y.Y., 2001. Information Granulation and Rough Set Approximation. International Journal of Intelligent Systems, 16(1): 87-104. doi: 10.1002/1098-111X(200101)16:1<87::AID-INT7>3.0.CO;2-S
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    出版历程
    • 收稿日期:  2014-04-05
    • 刊出日期:  2015-03-15

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