A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning
The identification of underground formation lithology can serve as a basis for petroleum exploration and development. This study integrates Extreme Gradient Boosting (XGBoost) with Bayesian Optimization (BO) for formation lithology identification and comprehensively evaluated the performance of the...
Enregistré dans:
| Auteurs principaux: | , , , , |
|---|---|
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI AG
2020-07-01
|
| Collection: | Energies |
| Sujets: | |
| Accès en ligne: | https://www.mdpi.com/1996-1073/13/15/3903 |
| Tags: |
Pas de tags, Soyez le premier à ajouter un tag!
|