Enhanced oil recovery by nanoparticles flooding: From numerical modeling improvement to machine learning prediction
Nowadays, enhanced oil recovery using nanoparticles is considered an innovative approach to increase oil production. This paper focuses on predicting nanoparticles transport in porous media using machine learning techniques including random forest, gradient boosting regression, decision tree, and ar...
Guardado en:
Autores principales: | Budoor Alwated, Mohamed F. El-Amin |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Yandy Scientific Press
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/be6dd5985fb34eff82a92eb3a1389c52 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Advances in multiscale numerical and experimental approaches for multiphysics problems in porous media
por: Yongfei Yang, et al.
Publicado: (2021) -
An assessment of methane gas production from natural gas hydrates: Challenges, technology and market outlook
por: Rashid Shaibu, et al.
Publicado: (2021) -
3D displacement discontinuity analysis of in-situ stress perturbation near a weak faul
por: Yutong Chai, et al.
Publicado: (2021) -
A review on half a century of experience in rate of penetration management: Application of analytical, semi-analytical and empirical models
por: Mohammad Najjarpour, et al.
Publicado: (2021) -
Improving basalt wettability to de-risk CO2 geo-storage in basaltic formations
por: Ahmed Al-Yaseri
Publicado: (2021)