Shale porosity prediction based on random forest algorithm
Precise and fast acquisition of shale porosity is important for the prediction of the spatial distribution of shale oil and the exploration target. To address the problem of low accuracy of porosity prediction using logging response equation， a porosity prediction model based on random forest algori...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Petroleum Geology and Recovery Efficiency
2023-11-01
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| Series: | Youqi dizhi yu caishoulu |
| Subjects: | |
| Online Access: | http://yqdzycsl.cnjournals.com/pgre/article/abstract/202306002?st=search |