000			01848nmc a2200229 4500
005			20260520005600.0
008			260224s2001 xxu ing
041			_aInglés
245	0	0	_aArtificial-Lift Systems Pattern Recognition Using Neural Networks _bSPE 69405
260			_aDallas, Texas _bSociety of Petroleum Engineers _c2001
270			_a12/09/06 ; 17/07/01
520			_aArtificial Neural Networks (ANN) are computational algorithms well suited to identify non-evident regularities and correlations in data. ANN are especially useful when there is missing or noisy process data, and when a mathematical model of the process is not readily available, as is the case with some Artificial Lift methods. Some ANN models exhibit excellent dimensionality reduction and visualization capabilities, mapping non-linear statistical relationships between high-dimensional data into simple geometric relationships, preserving the most important topological relationships of the data set. Thus, useful insight on the behavior of the process under study can be gained and used in its analysis and diagnosis. All this makes ANN a very useful tool in the exploratory phase of data mining. Results of several case studies applying ANN in pattern recognition of some Artificial Lift systemas are presented.
942			_cCONGTP
100	1		_aOcanto, L. _95800
100	1		_aRojas, A. _95801
111	2		_aLatin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina) _95738
700	1		_aRojas, A. _95801
711	2		_aLatin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina) _95738
800	1		_aOcanto, L. _95800
999			_c130851 _d130851
856			_uhttps://biblioteca.iapg.org.ar/ArchivosAdjuntos/LACPEC2001/Spe69405.pdf