Artificial immune systems for classification of petroleum well drilling operations

Authors:
Adriane B. S. Serapião;José R. P. Mendes;Kazuo Miura
Affiliations:
UNESP, IGCE, DEMAC, Rio Claro, SP, Brazil;UNICAMP, FEM, DEP, Campinas, SP, Brazil;PETROBRAS, E&P-SSE, UN-BC, ST, EP, Macaéé, RJ, Brazil
Venue:
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Year:
2007

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Abstract

This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning.