Implementación de un modelo predictivo mediante la metodología de machine learning para la localización de pozos inyectores de agua en un yacimiento heterogéneo
Heterogeneous reservoirs are common in the world being a non-uniform and non-linear spatial distribution of rock properties such as porosity, permeability and oil, gas and water saturation. The petroleum industry offers limited options for predicting effective locations for water injection wells in...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad de América
- Repositorio:
- Lumieres
- Idioma:
- spa
- OAI Identifier:
- oai:repository.uamerica.edu.co:20.500.11839/9133
- Acceso en línea:
- https://hdl.handle.net/20.500.11839/9133
- Palabra clave:
- Aprendizaje autónomo
Inyección de agua
Yacimiento heterogeneo
Autonomous Learning
Water injection
Heterogeneous reservoir
- Rights
- License
- Atribución – No comercial – Compartir igual
| Summary: | Heterogeneous reservoirs are common in the world being a non-uniform and non-linear spatial distribution of rock properties such as porosity, permeability and oil, gas and water saturation. The petroleum industry offers limited options for predicting effective locations for water injection wells in a heterogeneous reservoir. The leading country in the use of artificial intelligence is China and it is being implemented in different sectors of daily life such as medicine and surveillance among others. |
|---|