Inicio
Explorar
nav.journalClub
Tendencias
Más
Synapse
⌘+K
Synapse
Idioma
Español
Español
Correction: Samnioti, A.; Gaganis, V. Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part I. Energies 2023, 16, 6079 | Synapse
January 22, 2026
Open Access
Ver artículo completo
Correction: Samnioti, A.; Gaganis, V. Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part I. Energies 2023, 16, 6079
AS
Anna Samnioti
National Technical University of Athens
VG
Vassilis Gaganis
National Technical University of Athens
Puntos clave
The aim is to evaluate the role of machine learning in improving subsurface reservoir simulations.
Review of existing literature on machine learning applications in reservoir simulation.
Analysis of various machine learning algorithms used in the field.
Discussion of case studies demonstrating machine learning impact.
Identified several machine learning techniques that improve simulation accuracy.
Highlighted energy efficiency gains from implementing these techniques.
Showed potential for enhanced predictive modeling in reservoir management.
Resumen
Figure 1 from the original publication ...
Preguntar a la IA
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir
Ver artículo completo
Preguntar a la IA
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir
Ver artículo completo
Cite This Study
Copy
Samnioti et al. (Tue,) studied this question.
synapsesocial.com/papers/6971be8d642b1836717e32a7
https://doi.org/https://doi.org/10.3390/en19020513