Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach
Authors: 
Eric da Silva Praxedes, Adriano Soares Koshiyama, Elita Selmara Abreu, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti PachecoAuthors Info & Claims
Eric da Silva Praxedes, Adriano Soares Koshiyama, Elita Selmara Abreu, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti PachecoAuthors Info & ClaimsPages 1151 - 1158
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.
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- Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach
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Published: 12 July 2014
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