摘要
鹿井地区是我国重要的花岗岩型铀矿基地,相关研究表明该地区仍然存在很大的找矿前景。文章以鹿井东部地区为例,采用地面伽马能谱、地气、天然土壤热释光和土壤210Po等联合测量方法进行铀矿找矿勘查,运用PCA-KM联合分析方法进行综合异常识别,并结合地质资料对区内综合异常的分布特征、控制因素展开研究。结果表明,PCA-KM提取的综合异常可以有效反映已知铀矿化分布,降低综合解释多解性,能够将深部铀矿化、浅部铀矿化以及碱交代作用导致的放射性异常进行分离。区内综合异常与断裂构造、地层接触带以及碱交代作用关系密切;经综合分析,最终圈定了界坑东南部、黄峰岭东部、蛇坑东南部、鹿井-金鸡岭一带为成矿有利区。
Lujing area is a famous granite-type uranium base in China.Relevant studies show that there is still a great prospecting prospect.In this paper,eastern Lujing uranium ore field was studied with the combined measurement methods of ground gamma-ray spectrometry,geogas,natural soil thermoluminescence and soil 210Po for the uranium ore prospecting and exploration,PCA-KM combined analysis method was used to identify the comprehensive anomalies,and the distribution characteristics and control factors of comprehensive anomalies were analyzed by combining the geological data.The results showed that the comprehensive anomaly extracted by PCA-KM can effectively reflect the distribution of known uranium mineralization,reduce the ambiguity of comprehensive interpretation,and separate the radioactive anomalies caused by deep uranium mineralization,shallow uranium mineralization and alkali metasomatism.The comprehensive anomalies in the area are mainly related to fault structure,stratigraphic contact zone and alkali metasomatism.The southeast of Jiekeng,the east of Huangfengling,the southeast of Shekeng and Lujing-Jinjiling area were finally delineated as favorable metallogenic prospects.
作者
于宗东
罗齐彬
杨亚新
梁旭东
吕文杰
付宸
黄培
刘禧慧
YU Zongdong;LUO Qibin;YANG Yaxin;LIANG Xudong;LYU Wenjie;FU Chen;HUANG Pei;LIU Xihui(Fundamental Science on Radioactive Geology and Exploration Technology Laboratory,East China University of Technology,Nanchang,Jiangxi 330013,China;School of Nuclear Science and Engineering,East China University of Technology,Nanchang,Jiangxi 330013,China;School of Geophysics and Measurement-control Technology,East China University of Technology,Nanchang,Jiangxi 330013,China)
出处
《世界核地质科学》
CAS
2023年第2期347-359,共13页
World Nuclear Geoscience
基金
国家自然科学基金项目(编号:41774134)
国家重点研发计划项目(编号:2017YFC0602604)
东华理工大学放射性地质与勘探技术国防重点学科实验室开放基金项目(编号:2022RGET17)联合资助
关键词
主成分分析
K均值聚类分析
放射性勘探
综合异常提取
principal component analysis
K-means cluster analysis
radioactive exploration
comprehensive anomaly extraction