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

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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Bibliographic Details
Main Authors: Kyungbook Lee, Sungil Kim, Jonggeun Choe, Baehyun Min, Hyun Suk Lee
Format: Article
Language:English
Published: SpringerOpen 2018-08-01
Series:Petroleum Science
Subjects:
History-matched facies probability map
Training image rejection
Iterative static modeling
Channelized reservoirs
Multiple-point statistics
History matching
Online Access:http://link.springer.com/article/10.1007/s12182-018-0254-x

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http://link.springer.com/article/10.1007/s12182-018-0254-x

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