Multiple Geo-information GIS Integration And Metallogenic Prediction On Calcrete Type Uranium In Yilgarn Area Of Western Australia

This paper is based on the project, The distribution regular pattern of uranium resources and the strategic constituency of Australian uranium metallogenic domain, and choose Yilgarn district in Western Australia as the target place. On the basis of multiple Geo-information data as the foundation, such as:geology, remote sensing, gravity, aeromagnetic and airborne gamma spectra. The general thoughts are: “typical deposits—metallogenic essential factor—prediction factor—abnormal information extraction—metallogenic prediction”. The author makes use of GIS technology to process and analyze comprehensively the multiple Geo-information data, and search for information about digging mine from many approaches. Then the author carries out the research about metallogenic prediction of Calcrete Type Uranium, and delineates the uranium minerogenic prospect ivezone.This paper focused on the following research:1. To study the typical Calcrete Type Uranium deposit in this area. Based on analyzing and inducting the deposit’s geologic characteristic, mineralization characteristic and deposit’s contributing factors, the author set up the clue for prospecting, and extracting prediction factor.2. Based on the GIS platform, this article built the “Multiple Geo-information Thematic GIS system of Calcrete Type Uranium in Yilgarn”. So those thematic data of multiple geonomy in geology, remote sensing, and gravity, aeromagnetic and airborne gamma spectra are highly collected and effectively organized, and are visualized expression.3. The author reasonably selects data and do some comprehensive process and analyze, making Metallogenic prediction factor well expressed and reflected.(1)Interpret and delineate the Tertiary river by high-resolution remote sensing image;(2)Through MODIS, the author extracted the vegetation index and surface temperature which could reflect the information of climatic environment in this area, and delineated the climatic region which is beneficial to Uranium mineralization and to protect mineralization.(3)Interpret and delineate the region of greenstone belt by Aeromagnetic data, and delineated the region of vanadium source by Buffer analysis.(4)Extract and delineate the region of granite by gravity data;(5)Extract the original uranium and Uranium enrichment coefficient by airborne gamma spectral data, making weak prospecting information be expressed. The next step is the analysis of the overlay chart of original uranium- granite and the information map of Uranium enrichment coefficient, then delineate the source region and enrichment region of Uranium.4. Based on geoscience statistical analysis and supervised classification of feature space territory of Bayesian Decision Theory, extracted metallogenic indicative information of airborne gamma spectral in research area.5. According to level register and theories on Scientific targeting at mineral deposits came up with Zhao Peng-da, build the model of metallogenic prediction with Calcrete Type Uranium, regard the area which abnormal information frequently appeared and the most overlapping areas of sundry abnormal information as the most favorable area to exist Uranium deposit. The author delineated 14 minerogenic prospect of Calcrete Type Uranium based on this model; include 9 first class prospective area and 5 secondary prospective area.