LUO Jian-ming1,2, ZHANG Qi1, SONG Bing-tian1, WANG Xiao-wei1, YANG Zhong-ming1, ZHAO Yan-qing1,2, LIU Sheng-you1,2
1. Geological Survey of Gansu Province, Lanzhou 730000, China;
2. Bureau of Geology and Mineral Exploration and Development of Gansu Provinvial, Lanzhou 730000, China
Abstract：By changing the format from aeromagnetic measured data to geochemical exploration data, the quantitative prediction model for regional Au prospecting targets has been established by using multi-variate statistics analysis based on integrated geophysical and geochemical data. The model shows that aeromagnetic measured data is more powerful than geochemical Au elemental data on Au prospection. The model has been used to compare the similarity between all researching area units and known ore mineralized districts. 53 districts with high similarities are chosen as the Top-Class target zones (25 square kilometers). Among them, 18 districts (34%)contain gold ore deposit, the others (66%)would have good potential for Au exploration. Such results changed the previous understanding on aeromagnetic survey that aeromagnetic data is not efficient for Au prospection. On the contrary, big data show great potential in digging valuable information hided in massive data. Only if we change the way of thinking, we can dig out useful information about gold prospection by using quantitative or mathematical method on big data.
Key words：big data integrated geophysical and geochemical survey data quantitative prediction model prospective zone
Bulletin of Mineralogy, Petrology and Geochemistry Vol.36, No.6, 2017, page 886-890