| dc.date | 2015 | |
| dc.date | 2016-06-03T20:15:07Z | |
| dc.date | 2016-06-03T20:15:07Z | |
| dc.date.accessioned | 2018-03-29T01:33:46Z | |
| dc.date.available | 2018-03-29T01:33:46Z | |
| dc.identifier | | |
| dc.identifier | Revista Brasileira De Geofisica. Sociedade Brasileira De Geofisica, v. 33, n. 1, p. 119 - 126, 2015. | |
| dc.identifier | 0102261X | |
| dc.identifier | 10.1590/rbgf.v33i1.606 | |
| dc.identifier | http://www.scopus.com/inward/record.url?eid=2-s2.0-84947918444&partnerID=40&md5=18fc29a3dd5ad198a16516e48e401b2f | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/238342 | |
| dc.identifier | 2-s2.0-84947918444 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1305003 | |
| dc.description | The problem of automatic classification of facies was addressed using the Fast Independent Component Analysis (FastICA) of a data set of geophysical well logs of the Namorado Field, Campos Basin, Brazil, followed by a k-nearest neighbor (k-NN) classification. The goal of an automatic classification of facies is to produce spatial models of facies that assist the geological characterization of petroleum reservoirs. The FastICA technique provides a new data set that has the most stable and less Gaussian distribution possible. The k-NN classifies this new data set according to its characteristics. The previous application of FastICA improves the accuracy of the k-NN automatic classification and it also provides better results in comparison with the automatic classification by means of the Principal Component Analysis (PCA). © 2015 Sociedade Brasileira de Geofísica. | |
| dc.description | 33 | |
| dc.description | 1 | |
| dc.description | 119 | |
| dc.description | 126 | |
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| dc.description | | |
| dc.language | en | |
| dc.publisher | Sociedade Brasileira de Geofisica | |
| dc.relation | Revista Brasileira de Geofisica | |
| dc.rights | fechado | |
| dc.source | Scopus | |
| dc.title | Automatic Classification Of Lithofacies Using Fast Independent Component Analysis | |
| dc.type | Artículos de revistas | |
