TY - JOUR
T1 - Integration of an Iterative Update of Sparse Geologic Dictionaries with ES-MDA for History Matching of Channelized Reservoirs
AU - Kim, Sungil
AU - Min, Baehyun
AU - Lee, Kyungbook
AU - Jeong, Hoonyoung
N1 - Funding Information:
Dr. Baehyun Min was funded by the National Research Foundation of Korea (NRF) grants (no. NRF-2017R1C1B5017767 and no. NRF-2017K2A9A1A01092734). Dr. Kyungbook Lee was supported by the Korea Institute of Geoscience and Mineral Resources (GP2017-024) and MOTIE projects (NP2017-021, 20172510102090). Dr. Hoonyoung Jeong is thankful to the Research Institute of Energy and Resources, Seoul National University. The authors are grateful for the support of Korea Gas Corporation (KOGAS).
Publisher Copyright:
© 2018 Sungil Kim et al.
PY - 2018
Y1 - 2018
N2 - This study couples an iterative sparse coding in a transformed space with an ensemble smoother with multiple data assimilation (ES-MDA) for providing a set of geologically plausible models that preserve the non-Gaussian distribution of lithofacies in a channelized reservoir. Discrete cosine transform (DCT) of sand-shale facies is followed by the repetition of K-singular value decomposition (K-SVD) in order to construct sparse geologic dictionaries that archive geologic features of the channelized reservoir such as pattern and continuity. Integration of ES-MDA, DCT, and K-SVD is conducted in a complementary way as the initially static dictionaries are updated with dynamic data in each assimilation of ES-MDA. This update of dictionaries allows the coupled algorithm to yield an ensemble well conditioned to static and dynamic data at affordable computational costs. Applications of the proposed algorithm to history matching of two channelized gas reservoirs show that the hybridization of DCT and iterative K-SVD enhances the matching performance of gas rate, water rate, bottomhole pressure, and channel properties with geological plausibility.
AB - This study couples an iterative sparse coding in a transformed space with an ensemble smoother with multiple data assimilation (ES-MDA) for providing a set of geologically plausible models that preserve the non-Gaussian distribution of lithofacies in a channelized reservoir. Discrete cosine transform (DCT) of sand-shale facies is followed by the repetition of K-singular value decomposition (K-SVD) in order to construct sparse geologic dictionaries that archive geologic features of the channelized reservoir such as pattern and continuity. Integration of ES-MDA, DCT, and K-SVD is conducted in a complementary way as the initially static dictionaries are updated with dynamic data in each assimilation of ES-MDA. This update of dictionaries allows the coupled algorithm to yield an ensemble well conditioned to static and dynamic data at affordable computational costs. Applications of the proposed algorithm to history matching of two channelized gas reservoirs show that the hybridization of DCT and iterative K-SVD enhances the matching performance of gas rate, water rate, bottomhole pressure, and channel properties with geological plausibility.
UR - http://www.scopus.com/inward/record.url?scp=85065416978&partnerID=8YFLogxK
U2 - 10.1155/2018/1532868
DO - 10.1155/2018/1532868
M3 - Article
AN - SCOPUS:85065416978
SN - 1468-8115
VL - 2018
JO - Geofluids
JF - Geofluids
M1 - 1532868
ER -