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现代地质 ›› 2012, Vol. 26 ›› Issue (2): 286-293.

• 矿床学 • 上一篇    下一篇

云南个旧高松矿田芦塘坝研究区三维预测模型及靶区优选

 严琼1,2, 陈建平1,2, 尚北川1,2   

  1. 1 中国地质大学 国土资源与高新技术研究中心,北京100083;2 中国地质大学 北京市国土资源信息研究开发重点实验室,北京100083
  • 收稿日期:2011-08-10 修回日期:2011-12-20 出版日期:2012-04-20 发布日期:2018-09-19
  • 通讯作者: 陈建平,男,教授,博士生导师,1959年出生,地球探测与信息技术专业,主要从事矿产资源定量评价研究工作。
  • 作者简介:严琼,女,硕士研究生,1986年出生,地球探测与信息技术专业,主要从事矿产资源预测与评价。Email:june1620@163.com。
  • 基金资助:

    国土资源部公益性行业科研专项经费项目“我国找矿科研基地规范与关键技术应用示范”(201011002);“找矿科研基地三维数字矿山建模技术应用示范”(201011002-10)。

The 3D Prediction Model and Division of Targets in Lutangba Study Areaof Gaosong Ore Field in Gejiu, Yunnan Province

 YAN  Qiong-1,2, CHEN  Jian-Beng-1,2, CHANG  Bei-Chuan-1,2   

  • Received:2011-08-10 Revised:2011-12-20 Online:2012-04-20 Published:2018-09-19

摘要:

通过对云南个旧芦塘坝研究区成矿信息分析,结合三维可视化技术,对其进行深部隐伏矿体预测。根据研究区的地质概况与成矿规律,确定地层和断裂是主要的控矿条件,利用三维建模软件建立该研究区的数字矿床模型,应用立方体预测模型找矿方法,提取成矿有利因子——地层、断裂、构造定量化信息、化学元素异常,将其作为预测变量,最终通过计算圈定出预测远景区进而优选出4个预测靶区。预测远景区结果表明,该研究区有较好的找矿潜力,其矿产预测方法有效性较好。构造定量化信息分析方法的应用有助于实现三维找矿。

关键词: 芦塘坝研究区, 数字矿床模型, 立方体预测模型, 构造定量化信息, 预测远景区, 云南个旧

Abstract:

analyzing oreforming information of Lutangba study area in Gejiu, Yunnan Province, authors made a prediction of blind ore body with the help of 3D visualization technology. We took the stratigraphy and fracture as mainly orecontrolling factors according to geological feature and mineralization law, constructed digital deposit model by means of  3D modeling software. Advantageous factors of oreformation are extracted, including stratigraphy, fracture, quantitative information of structures and chemical elements abnormal as predictive variable by using method of the cubic predicting model. And finally we utilized delineate prospect area and then outline 4 targets. The prospective areas show that the study area has a good potential for prospecting minerals and the method of ore prediction is very effective. The application of the analysis method which is quantitative information of structures as new prospecting variables achieve a new breakthrough in 3D prospecting minerals.

Key words: Lutangba study area; , digital deposit model, cubic predicting model, quantitative information of structure; prospect area, Gejiu, Yunnan Province