Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow

Fluid flow characteristics are important to assess reservoir performance. Unfortunately, laboratory techniques are inadequate to know these characteristics, which is why numerical methods were developed. Such methods often use computed tomography (CT) scans as input but this technique is plagued by...

Descripción completa

Detalles Bibliográficos
Autores principales: Janssens, Nick, Huysmans, Marijke, Swennen, Rudy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7143904/
https://www.ncbi.nlm.nih.gov/pubmed/32204456
http://dx.doi.org/10.3390/ma13061397

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7143904/
https://www.ncbi.nlm.nih.gov/pubmed/32204456
http://dx.doi.org/10.3390/ma13061397

Ejemplares similares