TY - JOUR
T1 - A neo-fuzzy approach for bottom parameters estimation in oil wells
AU - Camargo, Edgar
AU - Aguilar, Jose
AU - Ríos, Addison
AU - Rivas, Francklin
AU - Aguilar-Martin, Joseph
PY - 2009/9
Y1 - 2009/9
N2 - In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.
AB - In this work, an approach for the bottom parameters estimation in oil wells is presented. It is based on neural networks and fuzzy logic, specifically on the neo-fuzzy-neuron model. We propose a neo-fuzzy system compose by two neo-fuzzy neurons. For validating the results, the estimation is applied in oil wells based on the artificial gas lift method, using variables of the head of the wells, particularly the gas and production pressures.
KW - Artificial gas lift wells
KW - Neofuzzy neurons
KW - Neuro-fuzzy models
KW - Oil system production
KW - Oil wells
KW - Parameters estimation
UR - https://www.scopus.com/pages/publications/70349572491
M3 - Article
AN - SCOPUS:70349572491
SN - 1991-8763
VL - 4
SP - 445
EP - 454
JO - WSEAS Transactions on Systems and Control
JF - WSEAS Transactions on Systems and Control
IS - 9
ER -