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...

Full description

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