Applying data mining and artificial intelligence techniques for high precision measuring of the two-phase flow’s characteristics independent of the pipe’s scale layer

Scale formation inside oil and gas pipelines is always one of the main threats to the efficiency of equipment and their depreciation. In this study, an artificial intelligence method method is presented to provide the flow regime and volume percentage of a two-phase flow while considering the presen...

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Autores:

Mayet, Abdulilah
Salama, Ahmed S.
Alizadeh, Mehdi
Nesic, Slavko
Grimaldo Guerrero, John William
Eftekhari-Zadeh, Ehsan
nazemi, ehsan
Iliyasu, Abdullah

Tipo de recurso:

Article of journal

Fecha de publicación:

2022

Institución:

Corporación Universidad de la Costa

Repositorio:

REDICUC - Repositorio CUC

Idioma:

eng

OAI Identifier:

oai:repositorio.cuc.edu.co:11323/9119

Acceso en línea:

https://hdl.handle.net/11323/9119
https://doi.org/10.3390/electronics11030459
https://repositorio.cuc.edu.co/

Palabra clave:

Pipeline’s scale
RBF neural network
Two-phase flow
Oil and gas
Artificial intelligence

Rights

openAccess

License

© 2022 by the authors. Licensee MDPI, Basel, Switzerland.