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|Type:||Artigo de periódico|
|Title:||Electrofacies Characterization Using Self-organizing Maps|
|Abstract:||The characterization of electrofacies is essential for reservoir modeling. However, this is a process that dependends on many variables, with errors and associated noise that interfere on visual interpretation. In order to minimize uncertainties, this paper proposes the use of the artifcial neural network called Auto-Maps Organizing, which is a computational algorithm inspired on the brain function that maps and groups similar information. The petrophysical data used, referes to Namorado Field on Campos Basin, of which were studied the neutron porosity, gamma ray, density and sonic profiles, to classify the field's reservoirs lithology. From the results it was possible to define the reservoir geometry and to detail its features with more accuracy. © 2012 Sociedade Brasileira de Geofísica.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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