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245	0	0	_aEVALUATION OF NEURO-SIMULATION TECHNIQUES AS PROXIES TO RESERVOIR SIMULATOR
270			_a15/05/2009 ; 11/04/2007
300			_a8 p.
520			_aProxy models are becoming more widely used as they can simplify highly complex processes with reasonable accuracy. Process such as production history matching, well placement, risk analysis, for example, generally involve large number of reservoir simulations and large computational effort. To minimize this problem some techniques such as Spline, Neural Networks, Kriging and Experimental Design, have been presented in the literature to be used as proxies to reservoir simulator. Due to the importance of the decisions related to the development and management of petroleum fields, the development of proxies with high accuracy can be a decisive aspect in a project. The successful applications of Neural Networks in several research fields suggest the investigation of appropriated architectures to be used as proxies to reservoir simulator. In this article novel proxies to reservoir simulator, based in Neuro-Simulation Techniques, are presented. These proxies present a high accuracy to reservoir simulator. Five different architectures of Neural Networks were studied and applied in two case studies related to history matching. The results obtained showed the large potential of application of the techniques introduced.
942			_cCONGTP
100	1		_aCamargo Silva, Paulo _937638
100	1		_aMaschio, Célio _924259
100	1		_aSchiozer, Denis J. _910197
111	2		_aRio Oil & Gas (2006 sept. 11-14 : Rio de Janeiro, Brazil) _937349
999			_c166222 _d166222
856			_uhttps://biblioteca.iapg.org.ar/ArchivosAdjuntos/Oil&Gas_Rio_2006/IBP_1342.pdf