3D computational simulation-based mineral prospectivity modeling for exploration for concealed Fe–Cu skarn-type mineralization within the Yueshan orefield, Anqing district, Anhui Province, China

Xiaohui Li, Mingming Zhang, Simon M. Jowitt, Alison Ord, Taofa Zhou, Wenqiang Dai

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The Yueshan orefield is one of the best-known Fe–Cu orefields in China and is located within the central Yangtze metallogenic belt ofin Anhui Province, China. The recent discovery of the skarn-type Zhuchong Fe–Cu deposit at depth within the orefield has highlighted the prospectivity of this area to host deep-seated skarn-type mineralization. However, the effectiveness of traditional geophysical exploration techniques is reduced with increasing depth. This, combined with recent developments in 3D mineral prospectivity modeling has led to the use of a 3D targeting approach for exploration for deep-seated and concealed mineralization in this area. However, to date the usefulness of this approach has been limited by a lack of an approach that could generate more useful 3D predictive maps. This study presents a 3D computational simulation based mineral prospectivity modeling approach that identified several exploration targets for concealed and deep-seated skarn-type mineralization within the Yueshan orefield. These prospective targets include areas of known mineralization as well as a number of new targets for future mineral exploration. In addition, the analysis of the resulting data using a capture-efficiency curve indicates that these 3D computational simulation approaches can provide additional predictive information for mineral exploration, indicating that 3D computational simulation should have a key role in the development and use of future 3D prospectivity modeling techniques during exploration targeting.

Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalOre Geology Reviews
Volume105
DOIs
Publication statusPublished - 1 Feb 2019

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@article{88a0ae49f51048df9b26f92d0283012d,
title = "3D computational simulation-based mineral prospectivity modeling for exploration for concealed Fe–Cu skarn-type mineralization within the Yueshan orefield, Anqing district, Anhui Province, China",
abstract = "The Yueshan orefield is one of the best-known Fe–Cu orefields in China and is located within the central Yangtze metallogenic belt ofin Anhui Province, China. The recent discovery of the skarn-type Zhuchong Fe–Cu deposit at depth within the orefield has highlighted the prospectivity of this area to host deep-seated skarn-type mineralization. However, the effectiveness of traditional geophysical exploration techniques is reduced with increasing depth. This, combined with recent developments in 3D mineral prospectivity modeling has led to the use of a 3D targeting approach for exploration for deep-seated and concealed mineralization in this area. However, to date the usefulness of this approach has been limited by a lack of an approach that could generate more useful 3D predictive maps. This study presents a 3D computational simulation based mineral prospectivity modeling approach that identified several exploration targets for concealed and deep-seated skarn-type mineralization within the Yueshan orefield. These prospective targets include areas of known mineralization as well as a number of new targets for future mineral exploration. In addition, the analysis of the resulting data using a capture-efficiency curve indicates that these 3D computational simulation approaches can provide additional predictive information for mineral exploration, indicating that 3D computational simulation should have a key role in the development and use of future 3D prospectivity modeling techniques during exploration targeting.",
keywords = "3D modeling, Computational simulation, Mineral prospectivity modeling, Skarn-type deposit, Yueshan orefield",
author = "Xiaohui Li and Mingming Zhang and Jowitt, {Simon M.} and Alison Ord and Taofa Zhou and Wenqiang Dai",
year = "2019",
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doi = "10.1016/j.oregeorev.2018.12.003",
language = "English",
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3D computational simulation-based mineral prospectivity modeling for exploration for concealed Fe–Cu skarn-type mineralization within the Yueshan orefield, Anqing district, Anhui Province, China. / Li, Xiaohui; Zhang, Mingming; Jowitt, Simon M.; Ord, Alison; Zhou, Taofa; Dai, Wenqiang.

In: Ore Geology Reviews, Vol. 105, 01.02.2019, p. 1-17.

Research output: Contribution to journalArticle

TY - JOUR

T1 - 3D computational simulation-based mineral prospectivity modeling for exploration for concealed Fe–Cu skarn-type mineralization within the Yueshan orefield, Anqing district, Anhui Province, China

AU - Li, Xiaohui

AU - Zhang, Mingming

AU - Jowitt, Simon M.

AU - Ord, Alison

AU - Zhou, Taofa

AU - Dai, Wenqiang

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AB - The Yueshan orefield is one of the best-known Fe–Cu orefields in China and is located within the central Yangtze metallogenic belt ofin Anhui Province, China. The recent discovery of the skarn-type Zhuchong Fe–Cu deposit at depth within the orefield has highlighted the prospectivity of this area to host deep-seated skarn-type mineralization. However, the effectiveness of traditional geophysical exploration techniques is reduced with increasing depth. This, combined with recent developments in 3D mineral prospectivity modeling has led to the use of a 3D targeting approach for exploration for deep-seated and concealed mineralization in this area. However, to date the usefulness of this approach has been limited by a lack of an approach that could generate more useful 3D predictive maps. This study presents a 3D computational simulation based mineral prospectivity modeling approach that identified several exploration targets for concealed and deep-seated skarn-type mineralization within the Yueshan orefield. These prospective targets include areas of known mineralization as well as a number of new targets for future mineral exploration. In addition, the analysis of the resulting data using a capture-efficiency curve indicates that these 3D computational simulation approaches can provide additional predictive information for mineral exploration, indicating that 3D computational simulation should have a key role in the development and use of future 3D prospectivity modeling techniques during exploration targeting.

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