Applying a genetic neuro-model reference adaptive controller in drilling optimization

Nenhuma Miniatura disponível

Data

2007-10-01

Título da Revista

ISSN da Revista

Título de Volume

Editor

Resumo

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between 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 an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Descrição

Palavras-chave

Como citar

World Oil, v. 228, n. 10, p. 29-36, 2007.