Comparison of data mining algorithms for pressure prediction of crude oil pipeline to identify congeal
Data mining is applied in many areas. In oil and gas industries, data mining may be implemented to support the decision making in their operation to prevent a massive loss. One of serious problems in the petroleum industry is congeal phenomenon, since it leads to block crude oil flow during transpor...
Guardado en:
Autores principales: | Santoso Agus, Wijaya F. Danang, Setiawan Noor Akhmad, Waluyo Joko |
---|---|
Formato: | article |
Lenguaje: | EN FR |
Publicado: |
EDP Sciences
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/b4fdc25638fb4d57a3a7fcaad53664ce |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Emulsification of Indian heavy crude oil using a novel surfactant for pipeline transportation
por: Shailesh Kumar, et al.
Publicado: (2017) -
The Origin, Physicochemical Properties, and Removal Technology of Metallic Porphyrins from Crude Oils
por: Jumina Jumina, et al.
Publicado: (2021) -
In-silico research of the influence of gas injection into the subsea crude oil pipeline on the paraffin solid phase deposition
por: Wójcikowski Artur, et al.
Publicado: (2021) -
Crowd oil not crude oil
por: Roland Dittmeyer, et al.
Publicado: (2019) -
Determination of free fatty acids in crude vegetable oil samples obtained by high-pressure processes
por: Carolina Medeiros Vicentini-Polette, et al.
Publicado: (2021)