Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm
Abstract
This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.
How to cite this document
Serapião, Adriane B. S.; Mendes, José Ricardo P.. Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 5579 LNAI, p. 301-310. Available at: <http://hdl.handle.net/11449/71234>.
Keywords
Language
English
