Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{daSilvaPraxedes:2014:GECCO,

• author = "Eric {da Silva Praxedes} and Adriano Soares Koshiyama and Elita Selmara Abreu and Douglas Mota Dias and Marley Maria Bernardes Rebuzzi Vellasco and Marco Aurelio Cavalcanti Pacheco",
• title = "Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach",
• booktitle = "GECCO '14: Proceedings of the 2014 conference on Genetic and evolutionary computation",
• year = "2014",
• editor = "Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. {Montes de Oca} and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges",
• isbn13 = "978-1-4503-2662-9",
• pages = "1151--1158",
• keywords = "genetic algorithms, genetic programming",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Vancouver, BC, Canada",
• URL = "http://doi.acm.org/10.1145/2576768.2598319",
• DOI = "doi:10.1145/2576768.2598319",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "One of the most important issues in oil \& gas industry is the lithological identification. Lithology is the macroscopic description of the physical characteristics of a rock. This work proposes a new methodology for lithological discrimination, using GPF-CLASS model (Genetic Programming for Fuzzy Classification) a Genetic Fuzzy System based on Multi-Gene Genetic Programming. The main advantage of our approach is the possibility to identify, through seismic patterns, the rock types in new regions without requiring opening wells. Thus, we seek for a reliable model that provides two flexibilities for the experts: evaluate the membership degree of a seismic pattern to the several rock types and the chance to analyse at linguistic level the model output. Therefore, the final tool must afford knowledge discovery and support to the decision maker. Also, we evaluate other 7 classification models (from statistics and computational intelligence), using a database from a well located in Brazilian coast. The results demonstrate the potentialities of GPF-CLASS model when comparing to other classifiers.",
• notes = "Also known as \cite{2598319} GECCO-2014 A joint meeting of the twenty third international conference on genetic algorithms (ICGA-2014) and the nineteenth annual genetic programming conference (GP-2014)",

}

Genetic Programming entries for Eric da Silva Praxedes Adriano Soares Koshiyama Elita Selmara Abreu Douglas Mota Dias Marley Maria Bernardes Rebuzzi Vellasco Marco Aurelio Cavalcanti Pacheco

Citations