摘要
常规的地球化学采样介质和遥感信息难以鉴别深部矿信息,地球物理信息可以反映深部矿的信息,但传统地球物理信息解释的多解性,影响了深部找矿靶区预测的精度和效果。为了消除物探信息的多解性,提高深部找矿靶区预测精准度,本文应用大数据思想和方法对甘肃省西秦岭大桥地区航磁数据进行深度挖掘,构建基于航磁信息的金找矿靶区定量预测系列模型,结合地质矿产信息,圈定并优选出金找矿靶区31处,其中Ⅰ级靶区6处(见矿率为16.9%),Ⅱ级矿靶区10处(见矿率为31.32%),Ⅲ级Au找矿靶区15处(见矿率为20%)。覆盖区的圈定找矿靶区,经验证发现了金工业矿体;靶区累积面积占研究区面积的2.4%,极大程度地缩小了找矿范围。研究认为基于航磁信息建立的找矿靶区定量预测系列模型,对研究区大桥式金矿找矿靶区的确定有着很高的准确性。
Conventional geochemical sampling medium does not contain deep deposit information,and the remote sensing information is only the characteristics of surface images,which is difficult to identify deep deposit information.Geophysical information can well reflect the information of deep deposit and it is the best information choice for deep metallogenic prediction.However,the interpretation of geophysical information are multi-resolution,which has always seriously affected the accuracy and accuracy of deep prospecting target prediction.Big data is triggering a profound revolution in the field of Geoscience.New methods and technologies such as big data and artificial intelligence represented by statistical analysis methods and machine learning algorithms have been gradually applied to metallogenic prediction and achieved good prediction results.The Western Qinling area of Gansu Province is an important polymetallic metallogenic accumulation area in China,which has accumulated rich geological data.It is of great significance to carry out quantitative prediction of gold prospecting target by deep mining geological data with big data method for gold exploration and expansion of gold reserves in Western Qinling area of Gansu Province.In order to eliminate the multi solution of geophysical information and improve the prediction accuracy of deep prospecting target,big data ideas and methods were applied to deep mining of aeromagnetic data from Daqiao area in west Qinling of Gansu Province,and established the aeromagnetic database,the aeromagnetic information research unit database and the known ore unit database respectively.Through the discriminant analysis of aeromagnetic database and known ore unit database,a series of quantitative prediction models of prospecting target were constructed,and deep prospecting targets were delineated,combined with geological and mineral information to optimize the grade prospecting targets.A total of 31 gold prospecting targets have been delineated in the study area,including 6 ClassⅠtargets(seeing ore rate 16.9%),10 ClassⅡore targets(seeing mine rate 31.32%)and 15 ClassⅢtargets(seeing ore rate 20%).Gold industrial ore bodies have been found in the prospecting target in the overburden area.The cumulative area of the target accounts for 2.4%of the area of the study area,which greatly reduces the scope of prospecting.The study believes that the series of quantitative prediction models for prospecting targets established based on aeromagnetic information have high accuracy in determining prospecting targets for Daqiao-type gold deposits in the study area.It provides a new idea and method for the metallogenic prediction of deep and concealed deposit.
作者
王怀涛
王晓伟
罗云之
宋秉田
罗建民
徐磊
WANG Huaitao;WANG Xiaowei;LUO Yunzhi;SONG Bingtian;LUO Jianmin;XU Lei(Geology Survey of Gansu Province,Lanzhou 730000,Gansu,China;Geoscience Big Data Exploration Engineering Technology Innovation Center of Gansu Provincial Bureau of Geology and Mineral Exploration and Development,Lanzhou 730000,Gansu,China;Geoscience Big Data Engineering Research Center of Gansu Province,Lanzhou 730000,Gansu,China)
出处
《黄金科学技术》
CSCD
2021年第6期771-780,共10页
Gold Science and Technology
基金
中国地质调查局地质调查项目“西秦岭成矿带典型矿区智能矿产地质调查评价试点示范”(编号:WKZB1911BJM300369/018)资助。
关键词
航磁信息
大数据
定量预测模型
深部找矿靶区
大桥金矿
西秦岭
aeromagnetic information
big data
quantitative prediction model
deep prospecting target
Daqiao gold deposit
Western Qinling
