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Research On The Prospecting For The Porphyric Copper Ore By Remote Sensing Technique In Shangri-la-Xiangyun Region

Posted on:2016-01-11Degree:MasterType:Thesis
Country:ChinaCandidate:Y F HeFull Text:PDF
GTID:2180330461956386Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
This paper selects 6 typical mineral deposits as research object including Pulang 、Xuejiping、Chundu、Tongchanggou、Baoxingchang and Xiaolongtan copper depositS. According to geological data and the feature of output background, the research objects were divided into 4 research areas. By means of summing up the known metallogenic regulars; analyzing the spectrum characteristic with Landsat 8 OLI data and ASTER remote sensing data; picking up the abnormal information of mineralized alteration and the interpreted results of OLI data on the line and circle structure in the research area with various methods; based on GIS platform, conducting the overlay analysis on the data of geological background, the interpreted data of geological structure and the result of remote sensing alteration picked up; ultimatelly, the prospecting model by remotesensing for the typical mineral deposit was formed. The research work in this paper is as below:(1)Conduct the pretreatment on radiation determining criteria of remote sense data, atmosphere calibration, geometrical revision, mixing, cutting, and remove the interfere factors on OLI and ASTER datas.(2) Pick up the information of hydroxyl group and iron dyed alteration by OLI datas;employ the model of fractal theory combined with Matlab to grade alteration information and analyze the relativity with ore body by ENVI; based on the available prospecting data, determine the alteration type of different typical mineral deposits; pick up alteration by ASTER data; finally find out the best method of pick-up.(3)Establish the mark of interpretation; take OLI data as the base map of geological structure to develop the additional interpretation work. Quantitatively analyze the interpretative results and carry out the correlation analysis with ore body.In combination with the Ore formation、Rock mass and Geological structure,to Calculate the geological complexity.Based on the GIS platform and the results of OLI data, the geological complex level that resulted from the calculation of the ore bearing strata and ore bodies by general analysis, the result of geological structure by spatial analysis, and the result of alteration information analyzes were sorted in the order of the interrelated level with ore body from large to small and then given weighting. The analytical results of the analysis of mineralization as follow:Pu Lang’s regional mineralization were close association of Ann porphyry rock body, main ditch of ore formation were Triassic’s group, the indicative mineralized alteration were iron level 2 and sericitization, focused on the linear structure bearing 60°-138°;Tochanggou was close association of quartz diorite porphyrite, main ditch of ore formation were official group in north and middle,the indicative mineralized alteration were hydroxyl 1 and pyritization, focused on the linear structure bearing 40°-92°;Baoxingchang area’s mainly rock mass wasgranite porphyry,main ditch of ore formation were mainly of ore formation of three or four paragraphs of xiangyangfather,the indicative mineralized alteration were hydroxyl 2 and green rock lithification,focused on the linear structure bearing 54°-89°;Xiaolongtan was in long porphyry mineralization,main ore formation was Triassic clay field group,indicative mineralized alteration were iron 1 and Green rock lithification,focused on the linear structure bearing 30°-42°.Based on the above results can quantify mathematical functional modely=aX1+bX2+cX3,and by this model can summarized remote sensing prospecting methods,thus perfecting the metallogenic model.That will provide a certain technical guide onmetallogenic forecast.
Keywords/Search Tags:Alteration abnormal, fractal model, geological structure, geological complex level, prospecting model by remote sensing
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