成矿环境空间结构的模糊建模

张振飞; 夏庆霖

成矿环境空间结构的模糊建模

张振飞^{1, 2,},
夏庆霖^{1, 2}

1.
国土资源部信息工程与资源定量评价重点实验室, 湖北武汉 430074
2.
中国地质大学数学地质遥感地质研究所, 湖北武汉 430074

基金项目:

国家自然科学基金项目 40272122

国土资源部重点攻关项目 20010305

详细信息

作者简介:
张振飞(1961-), 男, 副教授, 主要从事数学地质及矿产勘查研究.E-mail: Z_sds_cug@163.com

中图分类号: P628
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- 被引次数: 0
出版历程
- 收稿日期: 2004-06-23
- 刊出日期: 2005-01-25

Modeling the Spatial Patterns of Mineralization Environments Using Fuzzy Sets

ZHANG Zhen-fei^{1, 2
,},
XIA Qing-lin^{1, 2}

1.
Key Laboratory of Information Engineering and Resources Appraisal, Chinese Ministry of Land and Resources, Wuhan 430074, China
2.
Institute of Mathematical Geology and Remote Sensing Geology, China University of Geosciences, Wuhan 430074, China

摘要

摘要: 为了提高矿产预测的精度和可靠性, 必须分析和利用与矿床有关的空间结构信息.提出了一种用模糊集建立成矿环境空间结构模型的方法.成矿环境空间结构是地质变量在矿床周围的分布, 可用变量与空间点之间的模糊关系来描述.同一地区的同类矿床, 其空间结构具有一定相似性, 通过这种相似性的极大化可对结构模型进行优化.优化的结构模型是一种包含了方向和距离关系的特殊的空间关联规则集, 也是模糊推理矿产预测的推理规则库.通过模糊推理进行结构相似性的比较, 可对任意点上的找矿有利性进行预测.以云南东川地区铜矿预测的实例说明了该方法具有良好的应用效果.
- 模糊推理 /
- 空间数据挖掘 /
- 矿产预测 /
- 空间结构
Abstract: The utilization of spatial structural information is essential for mineral prediction. This paper proposes a method for the fuzzy modeling of spatial patterns of mineralization environments (SPME). SPME is the spatial distribution of geological factors and geophysical, geochemical responses (geo-variables) on/around a deposit, described by fuzzy relations of the geo-variables to spatial points. SPME related to deposits of the same genetic type in a given region are to some extent structurally similar. Based on a set of known deposits in the region, a model of SPME of the region can be built, and by maximizing the structural similarity between those known deposits, the model can be optimized. The model serves as a fuzzy deduction rule base. To evaluate the prospecting potential of any point in the region, a pattern is built on the point and the structural similarity of the pattern to the model is calculated by fuzzy deduction. A case study of copper mineral deposit prediction in the Dongchuan region of Yunnan, China, shows that the method is highly effective.
- fuzzy deduction /
- spatial data mining /
- mineral resources prediction /
- spatial pattern

HTML全文

图 1 研究区(东川地区) 及其铜矿床(点) 分布(据云南地调院2002年资料编)

研究区范围: 东经102°38′00″~103°37′00″, 北纬26°01′00″~26°37′00″.带下划线者为所选的模型矿床

Fig. 1. Location of study area and locations of copper mineral occurrences

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图 2 子区域内点的分布

Fig. 2. Distribution of points in a subregion

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图 3 不同子区域半径和方向上模型优化指标的分布

Fig. 3. Variation of the optimum index with radius and orientation of the subregion

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图 4 各变量在空间结构的不同点上的稳定程度

Fig. 4. Stability of variables on points of the spatial pattern

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图 5 东川铜矿找矿有利度等值线

图框位置及比例尺与图 1一致

Fig. 5. Contour map of prospecting favorability of copper mineral deposits of Dongchuan region

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表 1 地质变量

Table 1. Geo-variables

参考文献(18)

Cox, D. P., Singer, D. A., 1986. Mineral deposit models. US Geological Survey Bulletin, 1693: 379.
De Geoffroy, J. G., Wignall, T. K., 1985. Designing optimal strategies for mineral exploration. Plenum Press, New York, 1-363.
Henley, R. W., Berger, B. R., 1993. What is an exploration model anyway—An analysis of the cognitive development and use of models in mineral exploration. In: Kirkham, R. V., Sinclair, W. D., Thorpe, R. I., et al., eds., Mineral deposits modeling. Special Paper 40, Geological Association of Canada, Ottava, 41-50.
Koperski, K., Han, J., 1995. Discovery of spatial association rules in geographic information databases. In: Egenhofer, M. J., Herring, J. R., eds., Advances in spatial databases, LNCS 951. Springer-Verlag, Heidelberg, 47.
Mu, X. Z., Xi, X. H., 1996. The advances in geochemical exploration of solid ore resources and the achievements gained. Geophysical & Geochemical Exploration, 20(4): 241-249(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-WTYH604.000.htm
Sun, K. X., Shen, Y. R., Liu, G. Q., et al., 1991. Proterozoic iron and copper deposits in Middle Yunnan. China University of Geosciences Press, Wuhan, 169(in Chinese).
Tan, Y. B., Chen, G. F., 2000. A Gaussian clustering method based on maximum fuzzy entropy. Journal of UEST of China, 29(3): 269-272(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DKDX200003020.htm
Yang, L. B., Gao, Y. Y., 2003. Fuzzy mathematics: Principle and applications. South China University of Technology Press, Guangzhou, 1-422(in Chinese).
Zhang, Z. F., 2001. GIS-supported cell cluster methods of mineral resources prediction. Shaanxi Science and Technology Press, Xi'an, 1-140(in Chinese).
Zhang, Z. F., Hu, G. D., Zeng, Z. R., 1999. Quantitative analogy between spatial geological structures in mineral resources prediction—Cell cluster concept and application. Earth Science—Journal of China University of Geosciences, 24(6): 661-664(in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DQKX199906021.htm
Zhao, P. D., Chen, J. P., Chen, J. G., 2001. Mineral diversity and mineralization spectrum. Earth Science—Journal of China University of Geosciences, 26(2): 111-117(in Chinese with English abstract).
牟绪赞, 奚小环. 1996, 固体矿产地球化学勘查进展与成果. 物探与化探, 20(4): 241-249. https://www.cnki.com.cn/Article/CJFDTOTAL-WTYH604.000.htm
孙克祥, 沈远仁, 刘国庆, 等, 1991. 滇中元古宙铁铜矿床. 武汉: 中国地质大学出版社, 1-169.
谭扬波, 陈光福, 2000. 一种基于最大模糊熵的高斯聚类算法. 电子科技大学学报, 29(3): 269-272. doi: 10.3969/j.issn.1001-0548.2000.03.012
杨纶标, 高英仪, 2003. 模糊数学原理及应用(第三版). 广州: 华南理工大学出版社, 1-422.
张振飞, 2001. GIS支持的矿产预测单元簇法. 西安: 陕西科学技术出版社, 1-140.
张振飞, 胡光道, 曾章仁, 1999. 矿产预测中空间地质结构的定量类比———单元簇的概念及其应用. 地球科学———中国地质大学学报, 24(6): 661-664. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX199906021.htm
赵鹏大, 陈建平, 陈建国, 2001. 成矿多样性与成矿谱系. 地球科学———中国地质大学学报, 26(2): 111-117. https://cdmd.cnki.com.cn/Article/CDMD-10491-1013354295.htm