Kyungbook Lee(이경북)

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Jonggeun ChoeProfessor of Energy Resources Eng., Seoul National UniversityVerified email at snu.ac.kr
Sungil KimKorea Institute of Geoscience and Mineral ResourcesVerified email at kigam.re.kr
Hyungsik JungImage Vision, Naver CloudVerified email at navercorp.com
Jungtek LimSmartMind. Inc., Energy Holdings Group, Inc., Postdoc. Texas A&M, Seoul National Univ.Verified email at snu.ac.kr
Hyun Suk LeeKorea Institute of Geoscience and Mineral ResourcesVerified email at kigam.re.kr
Hoonyoung JeongSeoul National UniversityVerified email at snu.ac.kr
Honggeun JoAssistant professor at Inha UniversityVerified email at utexas.edu
Baehyun Min (B Min)Department of Climate & Energy Systems Engineering, Ewha Womans UniversityVerified email at ewha.ac.kr
Hyundon ShinProfessor of Energy Resources Engineering, Inha UniversityVerified email at inha.ac.kr
jaejun kimAI Advanced Research Lab., Technology Research, Samsung SDSVerified email at samsung.com
Changhyup ParkDepartment of Energy and Resources Engineering, Kangwon National UniversityVerified email at kangwon.ac.kr
Joonyi KimAI Advanced Research Lab., Samsung SDS, Seoul National UniversityVerified email at snu.ac.kr
Daeung YoonChonnam National UniversityVerified email at jnu.ac.kr
Seongin AhnKorea Institute Geoscience and Mineral ResourcesVerified email at kigam.re.kr
Jaewoo AnStanford UniversityVerified email at stanford.edu
Hyung Jun YangStanford UniversityVerified email at stanford.edu
Sun Young ParkKorea Institute of Geoscience and Mineral ResourcesVerified email at kigam.re.kr
ILSIK JANGProfessor, Dept. of Energy & Resources Eng., Chosun UniversityVerified email at chosun.ac.kr
Seok Goo SongKIGAM, KoreaVerified email at kigam.re.kr
Dae Sung LeeProfessor, Department of Energy and Mineral Resources Engineering, Dong-A UniversityVerified email at dau.ac.kr

Kyungbook Lee(이경북)

Kongju National University

Verified email at kongju.ac.kr - Homepage

Deep Learning Data Assimilation Subsurface Modeling(Geostatistics)CO2 Sequestration Subsurface Monitoring


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Prediction of shale-gas production at duvernay formation using deep-learning algorithm K Lee, J Lim, D Yoon, H Jung SPE Journal 24 (06), 2,423-2,437, 2019	140	2019
Improvement of ensemble smoother with clustered covariance for channelized reservoirs K Lee, H Jeong, SP Jung, J Choe Energy Exploration & Exploitation 31 (5), 713-726, 2013	45	2013
Characterization of channelized reservoir using ensemble Kalman filter with clustered covariance K Lee, H Jeong, SP Jung, J Choe Energy exploration & exploitation 31 (1), 17-29, 2013	39	2013
Geological model sampling using PCA-assisted support vector machine for reliable channel reservoir characterization H Jung, H Jo, S Kim, K Lee, J Choe Journal of Petroleum Science and Engineering 167, 396-405, 2018	37	2018
Recursive update of channel information for reliable history matching of channel reservoirs using EnKF with DCT H Jung, H Jo, S Kim, K Lee, J Choe Journal of Petroleum Science and Engineering 154, 19-37, 2017	37	2017
Ensemble smoother with clustered covariance for 3D channelized reservoirs with geological uncertainty K Lee, S Jung, J Choe Journal of Petroleum Science and Engineering 145, 423-435, 2016	33	2016
Generation of synthetic density log data using deep learning algorithm at the Golden field in Alberta, Canada S Kim, KH Kim, B Min, J Lim, K Lee Geofluids 2020, 1-26, 2020	32	2020
Feature extraction using a deep learning algorithm for uncertainty quantification of channelized reservoirs K Lee, J Lim, S Ahn, J Kim Journal of Petroleum Science and Engineering 171, 1007-1022, 2018	32	2018
Uncertainty quantification of channelized reservoir using ensemble smoother with selective measurement data K Lee, SP Jung, H Shin, J Choe Energy Exploration & Exploitation 32 (5), 805-816, 2014	32	2014
Ensemble-based data assimilation in reservoir characterization: A review S Jung, K Lee, C Park, J Choe Energies 11 (2), 445, 2018	31	2018
Use of clustered covariance and selective measurement data in ensemble smoother for three-dimensional reservoir characterization K Lee, S Jung, T Lee, J Choe Journal of Energy Resources Technology 139 (2), 2017	31	2017
Ensemble Kalman filter with principal component analysis assisted sampling for channelized reservoir characterization B Kang, H Yang, K Lee, J Choe Journal of Energy Resources Technology 139 (3), 2017	30	2017
Improvement of ensemble smoother with SVD-assisted sampling scheme B Kang, K Lee, J Choe Journal of Petroleum Science and Engineering 141, 114-124, 2016	29	2016
Efficient and robust optimization for well patterns using a PSO algorithm with a CNN-based proxy model J Kim, K Lee, J Choe Journal of Petroleum Science and Engineering 207, 109088, 2021	28	2021
History matching of channel reservoirs using ensemble Kalman filter with continuous update of channel information H Jo, H Jung, J Ahn, K Lee, J Choe Energy Exploration & Exploitation 35 (1), 3-23, 2017	27	2017
Characterization of channelized gas reservoirs using ensemble Kalman filter with application of discrete cosine transformation S Kim, C Lee, K Lee, J Choe Energy Exploration & Exploitation 34 (2), 319-336, 2016	27	2016
The kinetic effects of hydrate anti-agglomerants/surfactants F Ning, D Guo, SU Din, H Zhang, W Ou, B Fang, Y Liang, L Zhang, K Lee, ... Fuel 318, 123566, 2022	23	2022
Regeneration of channelized reservoirs using history-matched facies-probability map without inverse scheme K Lee, J Lim, J Choe, HS Lee Journal of Petroleum Science and Engineering 149, 340-350, 2017	23	2017
Initial ensemble design scheme for effective characterization of three-dimensional channel gas reservoirs with an aquifer S Kim, H Jung, K Lee, J Choe Journal of Energy Resources Technology 139 (2), 2017	22	2017
Development of fluid flow and heat transfer model in naturally fractured geothermal reservoir with discrete fracture network method T Lee, K Kim, K Lee, H Lee, W Lee Geosciences Journal 22, 477-485, 2018	21	2018

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