RANDOM FORESTS-BASED SENSITIVITY ANALYSIS FOR RESERVOIR HISTORY MATCHING
Sensitivity analysis is typically required to screen unwanted history matching parameters so that computational cost can be reduced. Random Forests (RF) is a well-known statistical learning tool that maps a list of input parameters onto a predicted response.
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Online Access: | http://utpedia.utp.edu.my/18960/1/AFTER_REVIVA.pdf http://utpedia.utp.edu.my/18960/ |
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