Characterization of three-dimensional channel reservoirs using ensemble Kalman filter assisted by principal component analysis

Characterization of three-dimensional channel reservoirs using ensemble Kalman filter assisted by principal component analysis

Abstracts Ensemble-based analyses are useful to compare equiprobable scenarios of the reservoir models. However, they require a large suite of reservoir models to cover high uncertainty in heterogeneous and complex reservoir models. For stable convergence in ensemble Kalman filter (EnKF), increasing...

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Détails bibliographiques
Auteurs principaux: Byeongcheol Kang, Hyungsik Jung, Hoonyoung Jeong, Jonggeun Choe
Format: Article
Langue:English
Publié: KeAi Communications Co., Ltd. 2019-09-01
Collection:Petroleum Science
Sujets:
Channel reservoir characterization
Model selection scheme
Egg model
Principal component analysis (PCA)
Ensemble Kalman filter (EnKF)
History matching
Accès en ligne:http://link.springer.com/article/10.1007/s12182-019-00362-8

Internet

http://link.springer.com/article/10.1007/s12182-019-00362-8

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