CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project
To characterise geological features that control the fluid flow in the subsurface from seismic data, I develop a multi-attribute analysis using an artificial neural network. The network is trained on the plume of CO2 injected into a saline aquifer as part of the CO2CRC Otway Project, using the plume...
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| Format: | Thesis |
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Curtin University
2020
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| Online Access: | http://hdl.handle.net/20.500.11937/84951 |
| _version_ | 1848764706416754688 |
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| author | Aldakheel, Mohammed |
| author_facet | Aldakheel, Mohammed |
| author_sort | Aldakheel, Mohammed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | To characterise geological features that control the fluid flow in the subsurface from seismic data, I develop a multi-attribute analysis using an artificial neural network. The network is trained on the plume of CO2 injected into a saline aquifer as part of the CO2CRC Otway Project, using the plume’s time-lapse seismic image as ground truth. The results highlight geological features controlling CO2 flow and guide static and dynamic modelling for future injection. |
| first_indexed | 2025-11-14T11:23:37Z |
| format | Thesis |
| id | curtin-20.500.11937-84951 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:23:37Z |
| publishDate | 2020 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-849512023-08-08T01:14:44Z CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project Aldakheel, Mohammed To characterise geological features that control the fluid flow in the subsurface from seismic data, I develop a multi-attribute analysis using an artificial neural network. The network is trained on the plume of CO2 injected into a saline aquifer as part of the CO2CRC Otway Project, using the plume’s time-lapse seismic image as ground truth. The results highlight geological features controlling CO2 flow and guide static and dynamic modelling for future injection. 2020 Thesis http://hdl.handle.net/20.500.11937/84951 Curtin University fulltext |
| spellingShingle | Aldakheel, Mohammed CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title | CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title_full | CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title_fullStr | CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title_full_unstemmed | CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title_short | CO2 Storage Characterization Driven by Images of a Prior Injection: CO2CRC's Otway Project |
| title_sort | co2 storage characterization driven by images of a prior injection: co2crc's otway project |
| url | http://hdl.handle.net/20.500.11937/84951 |