Decision-making framework to optimize the waterflooding process in an oilfield using reduced-order models and machine learning
In the face of increasing global energy demand and the need for energy transitions, improved decision-making processes in the oil and gas industry are essential. Waterflooding is a successful method for enhancing oil recovery. Numerical reservoir simulation software are essential tools for evaluatin...
- Autores:
-
Rodríguez Castelblanco, Astrid Xiomara
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2023
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/68869
- Acceso en línea:
- http://hdl.handle.net/1992/68869
- Palabra clave:
- Waterflooding
Optimization
Machine Learning
Deep Learning
Reduced-order models
Diffusivity Equation
Reservoir Engineering
Ingeniería
- Rights
- openAccess
- License
- Atribución 4.0 Internacional