Работы, цитирующие эту работу

Работ: 6

Работа: Modeling thermal-induced wellhead growth through the lifecycle of a well

1. Predictive modeling of oil rate for wells under gas lift using machine learning

   Fang Ma, Farag M. A. Altalbawy, Pinank Patel +9

   СтатьяReservoir Engineering and Simulation MethodsScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000733

2. Leveraging a novel nanocomposite for enhanced drilling fluid efficiency

   Yaqin Tian, Farag M. A. Altalbawy, Nikunj Rachchh +8

   СтатьяDrilling and Well EngineeringScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001593

3. Reliable estimation via hybrid gradient boosting machine for mud loss volume in drilling operations

   Xiaozhi Lu, Farag M. A. Altalbawy, Tarak Vora +9

   СтатьяDrilling and Well EngineeringScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002187

4. Predicting filter cake thickness in drilling fluids using machine learning techniques

   Minghui OU, Mohammed Al-Bahra, Raman Kumar +10

   СтатьяDrilling and Well EngineeringPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.008047

5. Application of hybrid gradient boosting machine to reliably predict rate of penetration

   Jianing Zhang, Farag M. A. Altalbawy, Tarak Vora +10

   СтатьяHigh-Velocity Impact and Material BehaviorPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.008755

6. Effect of titanium dioxide–Saponin–zirconium nanocomposites on the rheological and filtration properties of water-based drilling fluids

   Yang Wang, Farag M. A. Altalbawy, Nikunj Rachchh +9

   СтатьяDrilling and Well EngineeringPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.010066