Abstract
In this thesis, practical and theoretical improvements to the Monte Carlo simulation for Uncertainty Estimation (MCUE) method applied to 3D geological modeling are made.
Pole vector Bayesian sampling is proposed as a more rigorous alternative than dip vector sampling for planar features.
A complete MCUE Markov Chain procedure for drillhole path and log uncertainty propagation is proposed and demonstrated. Topological analysis is introduced as a powerful tool to mitigate plausible model heterogeneity.
Overall, MCUE is evidenced as a robust, cost/time efficient and flexible uncertainty propagation method in 3D geological modeling with high potential for improvement.
Pole vector Bayesian sampling is proposed as a more rigorous alternative than dip vector sampling for planar features.
A complete MCUE Markov Chain procedure for drillhole path and log uncertainty propagation is proposed and demonstrated. Topological analysis is introduced as a powerful tool to mitigate plausible model heterogeneity.
Overall, MCUE is evidenced as a robust, cost/time efficient and flexible uncertainty propagation method in 3D geological modeling with high potential for improvement.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 19 Nov 2018 |
DOIs | |
Publication status | Unpublished - 2018 |