3D/4D Geological Modeling for Mineral Exploration

doi:10.3390/books978-3-0365-7437-0

Download Url(s)

https://mdpi.com/books/pdfview/book/7321

Contributor(s)

Wang, Gongwen (editor)

Cheng, Lizhen (editor)

Li, Nan (editor)

Hou, Weisheng (editor)

Language

English

Show full item record

Abstract

With the development of high-precision geological observation technology, in situ mineral microanalysis technology, isotope geochemical analysis technology, deep geophysical exploration technology, deep drilling, real-time mining, remote sensing highresolution hyperspectral image technology, and supercomputer and industrial intelligence, geoscience has entered an era of big data and artificial intelligence in the 21st century. Three-dimensional/four-dimensional (3D/4D) geoscience modeling with the multi-disciplinary intersection of geosciences has been used as the basis for mineral exploration and the extraction of geosciences information for mineral resource assessment.

URI

https://directory.doabooks.org/handle/20.500.12854/100858

Keywords

GIS; multivariate geoscience datasets; RBFLN; metallogenic prospective area; 3D structural modeling (3D SM); 3D fault system models (FSMs); seismic attribute models; reservoir properties; facies; hydrocarbon-bearing zones; oxidation of molybdenite; ore-forming process; 3D multi-parameter geological modeling; microanalysis; Shangfanggou; continental red beds; hematite; secondary reduction zone; Danxia landform; deep prospecting; 3D metallogenic prediction; characteristic variables; stepped metallogenic model; resource potential; Jiaodong Peninsula; geological modeling; orebody modeling; coons surface interpolation; contour interpolation; polygon triangulation; 3D mineral prospectivity modeling; random forest; logistic regression; Xuancheng–Magushan area; 3D geological modeling; 3D ore-body modeling; spectral interpretation and 3D modeling; mineral exploration and deep targeting; Zhaoxian gold deposit; independent component analysis; 3D modeling; spectral feature subset selection; 3D mineral prospectivity mapping; quantitative mineral resources prediction model; maximum entropy model; Gaussian mixture model; Zaozigou gold deposit; geological and geochemical quantitative prediction model at depth; Deep auto-encoder network; Student Teacher Ore-induced Anomaly Detection; n/a