Iterative static modeling of channelized reservoirs using history-matched facies probability data and rejection of training image

Abstract Most inverse reservoir modeling techniques require many forward simulations, and the posterior models cannot preserve geological features of prior models. This study proposes an iterative static modeling approach that utilizes dynamic data for rejecting an unsuitable training image (TI) amo...

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Autores principales: Kyungbook Lee, Sungil Kim, Jonggeun Choe, Baehyun Min, Hyun Suk Lee
Formato: article
Lenguaje:EN
Publicado: KeAi Communications Co., Ltd. 2018
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Acceso en línea:https://doaj.org/article/e5822848121e49acad9a3a9f2630e358
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