Title :
Fault detection system in gas lift well based on artificial immune system
Author :
Araujo, Mariana ; Aguilar, Jose ; Aponte, Hugo
Author_Institution :
Dpto. de Computacion, Univ. de Los Andes, Merida, Venezuela
Abstract :
In this paper we propose an Artificial Immune System for fault detection in gas lift oil well. Our novel approach inspired by the Immune System allows the application of a pattern recognition model to perform fault detection. A significant feature of our approach is its ability to dynamically learning the fluid patterns of the ´self´ and predicting new patterns of the ´non-self´.
Keywords :
fault diagnosis; natural gas technology; oil technology; pattern recognition; unsupervised learning; artificial immune system; dynamic learning; fault detection system; fluid patterns; gas lift oil well; pattern recognition; Artificial immune systems; Centralized control; Fault detection; Immune system; Microorganisms; Pathogens; Pattern recognition; Petroleum; Protection; Viruses (medical);
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223658
