Leveraging boosting machine learning for drilling rate of penetration (ROP) prediction based on drilling and petrophysical parameters
Drilling optimization requires accurate drill bit rate-of-penetration (ROP) predictions. ROP decreases drilling time and costs and increases rig productivity. This study employs random forest (RF), gradient boosting modeling (GBM), extreme gradient boosting (XGBoost), and adaptive boosting (Adaboost...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2025-06-01
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| Series: | Artificial Intelligence in Geosciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666544125000176 |
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