Abstract
This thesis introduces an integrated inversion methodology exploiting the complementarities between probabilistic geological modelling. petrophysical measurements and geophysical inversion. The different sources of information are integrated
into a least-square inversion framework. The modularity of the proposed workflow allows several integration avenues for single domain and joint constrained inversion. Synthetic and real word case studies were performed. Results reveal that the application of petrophysical constraints sharpens the boundaries between geological units and that geological information strongly influences the structural features of the recovered model. Results also show that geological information is the main driver for uncertainty reduction in geophysical inverse modelling.
into a least-square inversion framework. The modularity of the proposed workflow allows several integration avenues for single domain and joint constrained inversion. Synthetic and real word case studies were performed. Results reveal that the application of petrophysical constraints sharpens the boundaries between geological units and that geological information strongly influences the structural features of the recovered model. Results also show that geological information is the main driver for uncertainty reduction in geophysical inverse modelling.
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 5 Feb 2019 |
DOIs | |
Publication status | Unpublished - 2019 |
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Tomofast-x community: Zenodo Community
Giraud, J. (Creator), Ogarko, V. (Creator) & Jessell, M. (Creator), Zenodo, 23 Oct 2023
https://zenodo.org/communities/tomofastx/ and one more link, https://github.com/TOMOFAST/Tomofast-x (show fewer)
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