Paper Info
Title
Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach
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 analyze 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.
Year
DOI
Venue
2014
10.1145/2576768.2598319
GECCO
Keywords
Field
DocType
applications and expert systems,fuzzy classification systems,genetic programming,oil & gas industry
Data mining,Computational intelligence,Fuzzy classification,Computer science,Genetic programming,Knowledge extraction,Artificial intelligence,Fuzzy control system,Fuzzy classifier,Machine learning,Decision maker,Lithology
Conference
Citations 
PageRank 
References 
0
0.34
10
Authors
6
Name
Order
Citations
PageRank
Eric da Silva Praxedes100.34
Adriano Soares Koshiyama23410.19
Elita Selmara Abreu300.34
Douglas Mota Dias4247.18
Marley Maria Bernardes Rebuzzi Vellasco56611.93
Marco Aurélio Cavalcanti Pacheco614322.29