Computational modelling of iron-ore mineralisation with stratigraphic permeability anisotropy
This study develops a computational framework to model fluid transport in sedimentary basins, targeting iron ore deposit formation. It offers a simplified flow model, accounting for geological features and permeability anisotropy as driving factors. A new finite element method lessens computational...
| Main Author: | |
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| Format: | Thesis |
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Curtin University
2023
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| Online Access: | http://hdl.handle.net/20.500.11937/93844 |
| _version_ | 1848765797169627136 |
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| author | Giraldo Avila, Juan Felipe |
| author_facet | Giraldo Avila, Juan Felipe |
| author_sort | Giraldo Avila, Juan Felipe |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study develops a computational framework to model fluid transport in sedimentary basins, targeting iron ore deposit formation. It offers a simplified flow model, accounting for geological features and permeability anisotropy as driving factors. A new finite element method lessens computational effort, facilitating robust predictions and cost-effective exploration. This methodology, applicable to other mineral commodities, enhances understanding of genetic models, supporting the search for new mineral deposits amid the global energy transition. |
| first_indexed | 2025-11-14T11:40:57Z |
| format | Thesis |
| id | curtin-20.500.11937-93844 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:40:57Z |
| publishDate | 2023 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-938442023-11-28T05:40:03Z Computational modelling of iron-ore mineralisation with stratigraphic permeability anisotropy Giraldo Avila, Juan Felipe This study develops a computational framework to model fluid transport in sedimentary basins, targeting iron ore deposit formation. It offers a simplified flow model, accounting for geological features and permeability anisotropy as driving factors. A new finite element method lessens computational effort, facilitating robust predictions and cost-effective exploration. This methodology, applicable to other mineral commodities, enhances understanding of genetic models, supporting the search for new mineral deposits amid the global energy transition. 2023 Thesis http://hdl.handle.net/20.500.11937/93844 Curtin University fulltext |
| spellingShingle | Giraldo Avila, Juan Felipe Computational modelling of iron-ore mineralisation with stratigraphic permeability anisotropy |
| title | Computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| title_full | Computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| title_fullStr | Computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| title_full_unstemmed | Computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| title_short | Computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| title_sort | computational modelling of iron-ore mineralisation with
stratigraphic permeability anisotropy |
| url | http://hdl.handle.net/20.500.11937/93844 |