香格里拉—祥云地区斑岩铜矿遥感找矿研究

发布时间：2018-07-08 17:38

本文选题：蚀变异常 + 分型模型　；参考：《成都理工大学》2015年硕士论文

【摘要】：本文选取香格里拉—祥云县沿区六个典型铜矿床,包括普朗、雪鸡坪、春都、铜厂沟、宝兴厂和小龙潭,根据地质资料和矿产产出背景特征,划分为四个研究区。将蚀变异常信息、地质复杂度、地质构造信息作为找矿模型的找矿标志,建立每个地区的特征遥感找矿模型。根据前人总结的成矿规律,分别采用Landsat 8OLI数据和ASTER数据,运用不同方法提取矿化蚀变异常信息。同时利用OLI数据,对研究区进行线、环构造解译。最后,基于GIS平台,将地质背景数据、地质构造解译数据、遥感蚀变提取结果,进行综合空间分析,最终形成针对于典型矿床的遥感找矿模型。本文主要研究内容有:(1)对OLI和ASTER数据进行预处理,辐射定标、大气校正、几何校正、融合、裁剪等,以及干扰因素去除。(2)利用OLI数据提取羟基、铁染蚀变信息,结合Matlab软件,采用分型理论模型,对蚀变信息进行分级,并在ENVI软件中与矿体进行相关性分析,查看不同区域、不同分级蚀变信息的精准度;ASTER数据根据已有勘察资料,提取典型矿床特征矿化蚀变类型,并确定最佳提取方法。(3)建立解译标志,OLI数据做为地质构造解译底图,结合地质资料,开展补充解译工作,定量化分析解译结果,以便与矿体相关性分析结合。根据赋矿地层+岩体+地质构造计算地质复杂度。结合地质复杂度结果、地质构造空间分析结果,以及OLI数据、ASTER数据提取的蚀变统计结果,基于GIS空间分析平台,三要素叠加分析,按照与矿体相关程度大小依次排序赋权重,整理出综合成矿分析的结果:普朗-雪鸡坪-春都地区成矿与英安斑岩岩体密切共生,主要赋矿地层为三叠系图姆沟组,指示性矿化蚀变为铁染2级和绢云母化,集中于线性构造方位方位60°—138°;铜厂沟地区成矿主要与石英闪长玢岩岩体有关,主要赋矿地层为北衙组上段、中段,指示性矿化蚀变为羟基1级和黄铁矿化,集中于线性构造方位方位40°—92°;宝兴厂地区成矿主要岩体为花岗斑岩岩体,主要赋矿地层为向阳组三段、四段,指示性矿化蚀变为羟基2级和青磐岩化,集中于线性构造方位方位54°—89°;小龙潭地区成矿主要岩体为正长斑岩岩体,主要赋矿地层为三叠统白土田组,指示性矿化蚀变为铁染1级和青磐岩化,集中于线性构造方位方位30°—42°。基于以上结果,定量化数学函数式模型y=aX1+bX2+cX3,其中a、b、c分别为归一化权重值,X为找矿模型影响因子。根据模型中不同影响因子的权重高低,分析特定区域成矿规律,总结遥感找矿方法,从而不断完善成矿模型,最终达到为今后的找矿工作提供一定的技术支持。
[Abstract]:This paper selects six typical copper deposits along Shangri-Xiangyun County, including Plang, Xuejiiping, Chundu, Tongchanggou, Baoxing Chang and Xiaolongtan. According to the geological data and the characteristics of mineral production background, it is divided into four study areas. Taking the information of alteration anomaly, geological complexity and geological structure as the prospecting mark of the ore-prospecting model, the characteristic remote sensing prospecting model of each area is established. According to the metallogenic rules summarized by the predecessors, Landsat 8 OLI data and ASTER data were used to extract the information of mineralization alteration anomaly by different methods. At the same time, the Oli data are used to interpret the line and ring structure of the study area. Finally, based on GIS platform, geological background data, geological structure interpretation data, remote sensing alteration extraction results are integrated spatial analysis, and finally a remote sensing prospecting model for typical deposits is formed. The main contents of this paper are as follows: (1) pretreatment of Oli and ASTER data, radiometric calibration, atmospheric correction, geometric correction, fusion, tailoring, and interference factor removal. (2) extraction of hydroxyl groups, iron stain alteration information and Matlab software using Oli data. The classification theory model is used to classify the alteration information, and the correlation analysis between the alteration information and the orebody is carried out in the ENVI software. The ASTER data of different regions and different grading alteration information are analyzed according to the existing survey data. The typical mineralization alteration types of typical deposits are extracted, and the best extraction method is determined. (3) to establish the interpretation mark Oli data as the geological structure interpretation base map, combine the geological data, carry out supplementary interpretation work, and quantitatively analyze the interpretation results. In order to combine with ore body correlation analysis. The geological complexity is calculated according to the geological structure of ore-bearing strata. Combined with the result of geological complexity, the result of spatial analysis of geological structure, and the statistical result of alteration extracted from ASTER data of Oli data, based on GIS spatial analysis platform, the three elements are superimposed and weighted according to the relative degree of orebody. The results of comprehensive metallogenic analysis are as follows: the mineralization of Plang-Xuejiiping-Chundu area is closely associated with the Yingan porphyry body, and the main ore-bearing strata are the Triassic Tumgou formation, and the indicative mineralization erosion becomes grade 2 iron-dyed and sericite. The ore-forming area in Tongchanggou area is mainly related to quartz diorite porphyrite, and the main ore-bearing strata are the upper and middle member of Beiya formation, the indicative mineralization erosion becomes hydroxyl class 1 and pyrite mineralization. The main ore-forming rock bodies in Baoxingchang area are granitic porphyry, the main ore-bearing strata are the third member of Xiangyang formation, the fourth member, indicating mineralization erosion into hydroxyl class 2 and Qingiranlitization, and the main ore-bearing strata are the third member of Xiangyang formation, and the main ore-bearing strata are the third member of Xiangyang formation. The main ore-forming body in Xiaolongtan area is syenite porphyry, the main ore-bearing strata are Triassic Baitutian formation, and the indicative mineralization erosion is iron-dyn grade 1 and Qingiranlitization. The linear tectonic azimuth is 30 掳-42 掳. Based on the above results, the quantitative mathematical functional model yongaX1bX2cX3, in which the normalized weight value X is the influence factor of the ore-prospecting model, is obtained. According to the weight of different influence factors in the model, this paper analyzes the metallogenic law of a specific region, summarizes the method of remote sensing prospecting, and improves the ore-forming model continuously, and finally provides certain technical support for the prospecting work in the future.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P627;P618.41

【参考文献】