Please use this identifier to cite or link to this item:
Type: Artigo de evento
Title: A Genetic Neuro-model Reference Adaptive Controller For Petroleum Wells Drilling Operations
Author: Fonseca T.C.
Mendes J.R.P.
Serapiao A.B.S.
Guilherme I.R.
Abstract: Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.
Rights: fechado
Identifier DOI: 10.1109/CIMCA.2006.8
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-38849162361.pdf296.23 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.