Towards a Robust Parameterization for Conditioning Facies Models Using Deep Variational Autoencoders and Ensemble Smoother

The literature about history matching is vast and despite the impressive number of methods proposed and the significant progresses reported in the last decade, conditioning reservoir models to dynamic data is still a challenging task. Ensemble-based methods are among the most successful and efficien...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Canchumuni, Smith W A, Emerick, Alexandre A, Pacheco, Marco Aurélio C
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 17.12.2018
Schlagworte:	Conditioning Data assimilation Iterative methods Machine learning Matching Neural networks Parameterization
ISSN:	2331-8422
Online-Zugang:	Volltext
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