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    Regeneration of Initial Ensembles With Facies Analysis for Efficient History Matching 

    Source: Journal of Energy Resources Technology:;2017:;volume( 139 ):;issue: 004:;page 42903
    Author(s): Kang, Byeongcheol; Choe, Jonggeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Reservoir characterization is needed for estimating reservoir properties and forecasting production rates in a reliable manner. However, it is challenging to figure out reservoir properties of interest due to limited ...
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    Ensemble Kalman Filter With Principal Component Analysis Assisted Sampling for Channelized Reservoir Characterization 

    Source: Journal of Energy Resources Technology:;2017:;volume( 139 ):;issue: 003:;page 32907
    Author(s): Kang, Byeongcheol; Yang, Hyungjun; Lee, Kyungbook; Choe, Jonggeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Ensemble Kalman filter (EnKF) is one of the widely used optimization methods in petroleum engineering. It uses multiple reservoir models, known as ensemble, for quantifying uncertainty ranges, and model parameters are ...
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    Model Regeneration Scheme Using a Deep Learning Algorithm for Reliable Uncertainty Quantification of Channel Reservoirs 

    Source: Journal of Energy Resources Technology:;2022:;volume( 144 ):;issue: 009:;page 93004-1
    Author(s): Lee, Youjun; Kang, Byeongcheol; Kim, Joonyi; Choe, Jonggeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Reservoir characterization is one of the essential procedures for decision makings. However, conventional inversion methods of history matching have several inevitable issues of losing geological information and poor ...
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