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黄金科学技术 ›› 2020, Vol. 28 ›› Issue (2): 213-227.doi: 10.11872/j.issn.1005-2518.2020.02.139

• 矿产勘查与资源评价 • 上一篇    

基于GIS与层次分析法的综合成矿预测——以新疆库米什地区为例

陈超民1,2(),冷成彪1(),司国辉3   

  1. 1. 东华理工大学核资源与环境国家重点实验室,江西 南昌 330013
    2. 上海师范大学环境与地理科学学院,上海 200234
    3. 西安地质矿产勘查开发院有限公司,陕西 西安 710100
  • 收稿日期:2019-07-25 修回日期:2019-11-25 出版日期:2020-04-30 发布日期:2020-05-07
  • 通讯作者: 冷成彪 E-mail:ccm2222@163.com;lcb8207@163.com
  • 作者简介:陈超民(1995-),男,江西寻乌人,硕士研究生,从事遥感与GIS方面的研究工作。ccm2222@163.com
  • 基金资助:
    国家自然科学基金项目“新疆精河县色勒特果勒还原性斑岩—矽卡岩Cu-Mo矿的矿床地球化学研究”(41872097)

Comprehensive Metallogenic Prediction Based on GIS and Analytic Hierarchy Process:A Case Study of Kumishi Region in Xinjiang

Chaomin CHEN1,2(),Chengbiao LENG1(),Guohui SI3   

  1. 1. State Key Laboratory of Nuclear Resources and Environment,East China University of Technology,Nanchang 330013,Jiangxi,China
    2. School of Environmental and Geographical Sciences,Shanghai Normal University,Shanghai 200234,China
    3. Xi’an Institute of Geological and Mineral Exploration Co. ,Ltd. ,Xi’an 710100,Shaanxi,China
  • Received:2019-07-25 Revised:2019-11-25 Online:2020-04-30 Published:2020-05-07
  • Contact: Chengbiao LENG E-mail:ccm2222@163.com;lcb8207@163.com

摘要:

新疆库米什地区植被覆盖率低、基岩裸露度高,为遥感地质找矿提供了良好条件。为了提高该地区的找矿效率、实现找矿突破,系统收集了库米什地区的矿产、地质及遥感资料,并采用“掩膜+Crosta主成分分析+阈值分割”方法从ETM+遥感数据中提取了蚀变异常信息。在矿产、地质和遥感多源信息的基础上,总结出矿(化)点、岩体内外接触带、蚀变带、断层、羟基蚀变异常信息和铁染蚀变异常信息6个控矿因子,采用基于知识驱动的层次分析法建立了成矿预测模型,利用数学方法和GIS平台完成了综合成矿预测。最后,以部分未加入模型的矿点与野外实地考察结果,验证了成矿预测效果。结果表明:运用层次分析法在新疆库米什地区初步进行多源信息综合成矿预测,其结果具有一定的准确性,能够为该区进一步地质找矿工作提供参考。

关键词: 遥感, 蚀变异常提取, 主成分分析, 层次分析法, GIS, 成矿预测, 新疆库米什

Abstract:

The Kumishi region in Xinjiang has low vegetation coverage and high bedrock exposure,which are conducive to ore-prospecting by remote sensing.In order to improve the efficiency of ore-prospecting in this region and achieve a breakthrough in ore-prospecting,we systematically collected data of mine,geology and remote sensing in the Kumishi region.Then we extracted abnormal information of alterations from the ETM+ image by adopting the method of “Mask+Principal component analysis of Crosta+Threshold segmentation.”To check the accuracy of abnormal information of alterations,we compared the extracted alteration information with the field phenomenon of the wall-rock alteration in the Kalatage-Qigebu area and found that it was basically consistent.Based on multi-source information of mine,geology and remote sensing,six ore-controlling factors including mineralized points (ore spots),contact zones of magmatic rocks,alteration zones,faults,anomalies of hydroxyl alterations and anomalies of iron-stained alterations were selected.Since the number of deposits or ore spots in the Kumishi region was not enough to support the data-driven model,the analytic hierarchy process which belongs to a knowledge-driven decision-making method was adopted in this study.Consequently,the hierarchical model for the metallogenic prediction was established by the analytic hierarchy process which can present people’s subjective experience and thinking in digital form and realize the combination of qualitative analysis and quantitative analysis.In this model,the metallogenic prospective prediction was regarded as the target layer.The above six ore-controlling factors were considered as the criterion layer.0~300 m buffers,300~600 m buffers,and 600~1 000 m buffers were taken as the index layer in the lower layer of the first four criterion layers.The last two criterion layers were divided into three grades that were deemed as the index layer.By the combination of some previous research and expertise,some judgment matrices for each criterion layer and each index layer were constructed.In addition,we assigned values to each index layer.On this basis,some weights of each criterion layer and each index layer were calculated by the mathematical method.Meanwhile,the raster calculation and the kernel density analysis were carried out on the GIS platform to complete the comprehensive metallogenic prediction.Finally,some ore spots that were not added to the model were used to evaluate the effect of the metallogenic prediction.To test the accuracy of the predicted results,we drilled two holes in the Kalatage-Qigebu area.The scheelite mineralization in this area was preliminarily found because of the bluish-purple fluorescence of some samples under the ultraviolet light.It was confirmed more precisely by the scanning electron microscope(SEM) and the energy dispersive spectrometer(EDS).In conclusion,the results show that the application of the analytic hierarchy process in the metallogenic prediction of multi-source information in the Kumishi region has a good effect.Therefore,it can provide some references for further work in this region.

Key words: remote sensing, extraction of alteration anomalies, principal component analysis, analytic hierarchy process, GIS, metallogenic prediction, Kumishi region in Xinjiang

中图分类号: 

  • P628

图1

库米什地区地质简图(据文献[22]修改) 1.第四系;2.葡萄沟组;3.桃树园组;4.鄯善群;5.三工河组;6.阿其克布拉克组;7.底坎尔组;8.桑树园组;9.马鞍桥组;10.牙曼苏组;11.小热泉子组;12.哈孜尔布拉克组;13.阿拉塔格组;14.阿尔彼什麦布拉克组;15.阿哈布拉克群;16.中天山群星星峡组;17.加里东期变形花岗岩;18.华力西期花岗岩;19.辉橄岩;20.橄榄岩;21.断层;22.石膏矿点;23.石灰岩矿点;24.多金属矿点;25.褐铁矿化点;26.铁矿化点;27.铜矿(化)点;28.钨矿点"

表1

研究区掩膜后图像1、3、4、5波段主成分分析的特征向量及特征值"

主成分 ETM+1 ETM+3 ETM+4 ETM+5 特征值 信息量/%
PC1 0.271432 0.458413 0.523877 0.664632 4 531 404.269010 99.13
PC2 0.373363 0.434416 0.360416 -0.736195 30 152.496484 0.66
PC3 0.804067 0.004837 -0.580966 0.126218 8 510.120933 0.19
PC4 -0.374701 0.775318 -0.508066 0.018739 908.433548 0.02

表2

研究区掩膜后图像1、4、5、7波段主成分分析的特征向量及特征值"

主成分 ETM+1 ETM+4 ETM+5 ETM+7 特征值 信息量/%
PC1 0.246298 0.475324 0.607979 0.586316 5 441 535.328711 98.90
PC2 0.359951 0.686251 -0.077387 -0.627301 41 000.148234 0.75
PC3 0.679599 -0.060805 -0.612567 0.399010 13 197.824440 0.24
PC4 -0.589846 0.547202 -0.499134 0.321742 6 266.013310 0.11

图2

铁染蚀变异常分布(由ETM+遥感图像真彩色合成叠加) 1.铁染三级蚀变异常;2.铁染二级蚀变异常;3.铁染一级蚀变异常"

图3

羟基蚀变异常分布(由ETM+遥感图像真彩色合成叠加) 1.羟基三级蚀变异常;2.羟基二级蚀变异常;3.羟基一级蚀变异常"

图4

喀拉塔格—其格布区蚀变异常信息野外验证结果 (a)ETM+7,4,1波段合成图像;(b)铁染蚀变异常信息;(c)羟基蚀变异常信息;(d)地貌景观;(e)面状分布的褐铁矿化与绢英岩化;(f)条带状分布的褐铁矿化与绢英岩化"

图5

成矿预测层次结构图"

表3

各判断矩阵的计算结果"

判断矩阵 层次单排序的权重向量 W λ m a x CI RI CR
A - B (0.4361,0.2639,0.1446,0.0779,0.0463,0.0313)T 6.1023 0.0205 1.2500 0.0164
B 1- C (0.6483,0.2297,0.1220,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)T 3.0037 0.0018 0.5200 0.0035
B 2- C (0,0,0,0.6483,0.2297,0.1220,0,0,0,0,0,0,0,0,0,0,0,0)T 3.0037 0.0018 0.5200 0.0035
B 3 -C (0,0,0,0,0,0,0.6483,0.2297,0.1220,0,0,0,0,0,0,0,0,0)T 3.0037 0.0018 0.5200 0.0035
B 4- C (0,0,0,0,0,0,0,0,0,0.6483,0.2297,0.1220,0,0,0,0,0,0)T 3.0037 0.0018 0.5200 0.0035
B 5- C (0,0,0,0,0,0,0,0,0,0,0,0,0.6483,0.2297,0.1220,0,0,0)T 3.0037 0.0018 0.5200 0.0035
B 6- C (0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.6483,0.2297,0.1220)T 3.0037 0.0018 0.5200 0.0035

表4

层次总排序结果"

准则层 准则层权值bj 指标层 指标层权值ci
矿化点(B1) 0.4361 0~300 m缓冲区(C1) 0.2827
300~600 m缓冲区(C2) 0.1002
600~1 000 m缓冲区(C3) 0.0532
岩体内外接触带(B2) 0.2639 0~300 m缓冲区(C4) 0.1711
300~600 m缓冲区(C5) 0.0606
600~1 000 m缓冲区(C6) 0.0322
蚀变带(B3) 0.1446 0~300 m缓冲区(C7) 0.0937
300~600 m缓冲区(C8) 0.0332
600~1 000 m缓冲区(C9) 0.0176
断层(B4) 0.0779 0~300 m缓冲区(C10) 0.0505
300~600 m缓冲区(C11) 0.0179
600~1 000 m缓冲区(C12) 0.0095
羟基蚀变异常信息(B5) 0.0463 一级蚀变异常(C13) 0.0300
二级蚀变异常(C14) 0.0106
三级蚀变异常(C15) 0.0056
铁染蚀变异常信息(B6) 0.0313 一级蚀变异常(C16) 0.0203
二级蚀变异常(C17) 0.0072
三级蚀变异常(C18) 0.0038

图6

各类控矿因子叠加图 1.总矿(化)点;2.断层;3.总蚀变带;4.总岩体;5.羟基三级蚀变异常;6.羟基二级蚀变异常;7.羟基一级蚀变异常;8.铁染三级蚀变异常;9.铁染二级蚀变异常;10.铁染一级蚀变异常"

图7

成矿有利度图"

图8

成矿有利点核密度分布图 1.模型中使用的矿(化)点;2.预留的矿点;3.验证的矿化点;4.喀拉塔格—其格布项目区"

图9

喀拉塔格—其格布地区的白钨矿化 (a)片麻岩与石英脉接触处的白钨矿化;(b)片麻岩与石英脉接触处的白钨矿化(在紫外灯照射下);(c)、(d)钻孔岩芯中花岗岩的白钨矿化(在紫外灯照射下)"

图10

片麻状黑云母花岗岩样品SEM-EDS结果(25.0 kV,×100)"

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