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Improved index overlay mineral potential modeling in brown- and green-fields exploration using geochemical, geological and remote sensing data

Authors :
Bijan Roshanravan
Ahmad Aryafar
Source :
Earth Science Informatics. 13:1275-1291
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

The data-driven index overlay technique is an amended version of the conventional index overlay method, which has been utilized for mineral potential modeling (MPM) in brown-fields exploration, whereby a data-driven way is utilized to determine the relative significance of both individual evidence maps and evidential values. Although this method evades exploration bias in the conventional index overlay MPM resulting from categorization of evidential maps into some optional classes, it still possesses two major issues: (i) since this technique utilizes the plots of prediction-area (P-A) for defining the importance degree of every evidential map, it carries exploration bias resulting from the use of known mineral occurrences (KMOs) and (ii) it is not applicable in green-fields areas where there may be no KMOs. In this study, we propound an improved index overlay MPM to overcome the deficiencies described above, whereby every individual evidential map is rendered a weight without expert opinion and without the use of KMOs through a modified Shannon’s entropy method. To illustrate this procedure, we applied it to the brown-fields Dolatabad district of southern Iran as a MPM case study for podiform chromite deposits. The results indicated that the improved index overlay approach outperformed the data-driven index overlay method for modeling the potential of the podiform chromite deposits. After successful testing of the improved index overlay technique, we applied it to the green-fields Birjand district of eastern Iran in order to ascertain promising zones for further detailed exploration of the targeted deposit.

Details

ISSN :
18650481 and 18650473
Volume :
13
Database :
OpenAIRE
Journal :
Earth Science Informatics
Accession number :
edsair.doi...........8863a2026ddf73ca70bee4fd0c124531
Full Text :
https://doi.org/10.1007/s12145-020-00509-x