Fuzzy clustering based models applied to petroleum processes


Abstract:

The application of fuzzy clustering techniques has recently become in a very useful alternative in the area of modeling and identification of complex industrial processes. In particular, fuzzy clustering techniques such as Fuzzy C-Means and the Gustafson-Kessel (GK) algorithms will be analyzed and applied in details in this paper. These algorithms will be implemented in the construction of Takagi-Sugeno fuzzy models for the gas-liquid separation process, the water-oil separation process and the oil-heating process, which are important processes in the oil industry. Validations of the obtained fuzzy models will be performed and some conclusions will be established.

Año de publicación:

2008

Keywords:

  • Fuzzy C-means
  • Production separator
  • Gustafson-Kessel (GK) algorithm
  • Washing-tanks and fired heaters
  • Least-squares method
  • Fuzzy Clustering
  • Artificial lift production methods

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Petróleo

Áreas temáticas:

  • Física aplicada
  • Aceites, grasas, ceras y gases industriales
  • Tecnología alimentaria