用户名: 密码: 验证码:
Evidential data integration to produce porphyry Cu prospectivity map, using a combination of knowledge and data-driven methods
详细信息       来源:Geophysical Prospecting    发布日期:2022年8月10日
  • 标题:Evidential data integration to produce porphyry Cu prospectivity map, using a combination of knowledge and data-driven methods
  • 关键词:Data-driven multi-index overlay;C-A and P-A plots;Porphyry Cu;Fuzzy logic;Mineral prospectivity mapping
  • 作者:Shokouh Riahi, Abbas Bahroudi, Maysam Abedi, Soheila Aslani, David R. Lentz

全文下载

内容简介线

Producing an accurate and valid mineral prospectivity map is one of the most significant parts of mineral exploration studies. For this purpose, it is needed to obtain valid evidential layers and integrate them with an accurate methodology. Knowledge and data-driven methods are two primary techniques applied to combine various evidential layers for mineral prospectivity mapping, of which each of them includes a variety of analytical techniques. In this study, in the first step, satellite data, aeromagnetic and airborne radiometric data, stream sediment geochemical data and geological data were applied to create valid remote sensing, geophysical, geochemical, lineaments and lithological evidential layers of the study area that are an essential factor in recognition porphyry copper mineralization, then in the second step, based on the known mineralization occurrences data, the evidential layers were weighted. Finally, these layers were integrated using fuzzy logic and index overlay methods in a combination of knowledge and data-driven way. Validation of each layer was done using available data in the second step. The final mineral prospectivity map was evaluated, and the confirmation of this layer detected that the final mineral prospectivity map obtained from data-driven multi-index overlay method has a higher ore prediction rate of 76%, which identifies 24% of the area as potential zones for further exploration. 

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700