Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia
Determining the spatial relationships between various geological features and mineralisation is not only important for understanding the ore genesis of mineral deposits, but can also help to guide mineral exploration by providing predictive mineral maps. In this GIS-based study, we quantify the spat...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Elsevier Science BV
2013
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/49347 |
| _version_ | 1848758221620117504 |
|---|---|
| author | Liu, Yingchao Li, Zheng-Xiang Laukamp, C. West, Geoff Gardoll, Stephen |
| author_facet | Liu, Yingchao Li, Zheng-Xiang Laukamp, C. West, Geoff Gardoll, Stephen |
| author_sort | Liu, Yingchao |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Determining the spatial relationships between various geological features and mineralisation is not only important for understanding the ore genesis of mineral deposits, but can also help to guide mineral exploration by providing predictive mineral maps. In this GIS-based study, we quantify the spatial relationships between gold mineralisation and plausible controlling factors in the central part of the St Ives area, Western Australia. We weigh plausible control factors including rock types, lithological boundaries and faults, using gold occurrences in drill-cores, and then apply the weights to the geological data to generate a predictive map for the entire St Ives area. The three major findings of this study are: (1) all major gold deposits are controlled by faults, and small-scale fault systems have a stronger correlation with gold mineralisation than large faults; (2) felsic to intermediate intrusive rocks show strong correlations with gold mineralisation, whereas metamorphic mafic rocks (greenstones) possibly acted as part of the broad regional environment for the mineral province rather than as a factor controlling the exact locations of the deposits; and (3) our predictive mapping indicates that the southeast part of the St Ives goldfield has a high potential for discovering new gold mineralisation. |
| first_indexed | 2025-11-14T09:40:33Z |
| format | Journal Article |
| id | curtin-20.500.11937-49347 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:40:33Z |
| publishDate | 2013 |
| publisher | Elsevier Science BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-493472017-09-13T16:07:58Z Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia Liu, Yingchao Li, Zheng-Xiang Laukamp, C. West, Geoff Gardoll, Stephen mapping St Ives area Quantified spatial relationships Predictive GIS-based modelling Gold mineralisation Determining the spatial relationships between various geological features and mineralisation is not only important for understanding the ore genesis of mineral deposits, but can also help to guide mineral exploration by providing predictive mineral maps. In this GIS-based study, we quantify the spatial relationships between gold mineralisation and plausible controlling factors in the central part of the St Ives area, Western Australia. We weigh plausible control factors including rock types, lithological boundaries and faults, using gold occurrences in drill-cores, and then apply the weights to the geological data to generate a predictive map for the entire St Ives area. The three major findings of this study are: (1) all major gold deposits are controlled by faults, and small-scale fault systems have a stronger correlation with gold mineralisation than large faults; (2) felsic to intermediate intrusive rocks show strong correlations with gold mineralisation, whereas metamorphic mafic rocks (greenstones) possibly acted as part of the broad regional environment for the mineral province rather than as a factor controlling the exact locations of the deposits; and (3) our predictive mapping indicates that the southeast part of the St Ives goldfield has a high potential for discovering new gold mineralisation. 2013 Journal Article http://hdl.handle.net/20.500.11937/49347 10.1016/j.oregeorev.2013.03.007 Elsevier Science BV restricted |
| spellingShingle | mapping St Ives area Quantified spatial relationships Predictive GIS-based modelling Gold mineralisation Liu, Yingchao Li, Zheng-Xiang Laukamp, C. West, Geoff Gardoll, Stephen Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title | Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title_full | Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title_fullStr | Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title_full_unstemmed | Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title_short | Quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, St Ives Goldfield, Western Australia |
| title_sort | quantified spatial relationships between gold mineralisation and key ore genesis controlling factors, and predictive mineralisation mapping, st ives goldfield, western australia |
| topic | mapping St Ives area Quantified spatial relationships Predictive GIS-based modelling Gold mineralisation |
| url | http://hdl.handle.net/20.500.11937/49347 |