Kyungbook Lee

1.4k total citations
73 papers, 1.1k citations indexed

About

Kyungbook Lee is a scholar working on Mechanical Engineering, Ocean Engineering and Mechanics of Materials. According to data from OpenAlex, Kyungbook Lee has authored 73 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Mechanical Engineering, 47 papers in Ocean Engineering and 26 papers in Mechanics of Materials. Recurrent topics in Kyungbook Lee's work include Hydraulic Fracturing and Reservoir Analysis (48 papers), Reservoir Engineering and Simulation Methods (43 papers) and Drilling and Well Engineering (25 papers). Kyungbook Lee is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (48 papers), Reservoir Engineering and Simulation Methods (43 papers) and Drilling and Well Engineering (25 papers). Kyungbook Lee collaborates with scholars based in South Korea, United States and China. Kyungbook Lee's co-authors include Jonggeun Choe, Sungil Kim, Hyungsik Jung, Daeung Yoon, Lei Zhang, Richard A. Larson, J. W. Stucki, Hoonyoung Jeong, Byeong‐Cheol Kang and Honggeun Jo and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Annals of Oncology and Fuel.

In The Last Decade

Kyungbook Lee

63 papers receiving 1.1k citations

Peers

Kyungbook Lee

GEOPH

Christopher J. Landry United States

Amjed Hassan Saudi Arabia

Weiyao Zhu China

Megan M. Smith United States

Alireza Nouri Canada

Yugang Cheng China

Bo Huang China

Xizhe Li China

Xiaoqiang Liu China

Karen Bybee United States

Christopher J. Landry United States

Kyungbook Lee

394 ×0.6

292 ×0.4

290 ×1.0

137 ×0.8

64 ×0.5

GEOPH

Citations per year, relative to Kyungbook Lee Kyungbook Lee (= 1×) peers Christopher J. Landry

Countries citing papers authored by Kyungbook Lee

Since Specialization

Citations

This map shows the geographic impact of Kyungbook Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kyungbook Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyungbook Lee more than expected).

Fields of papers citing papers by Kyungbook Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyungbook Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kyungbook Lee. The network helps show where Kyungbook Lee may publish in the future.

Co-authorship network of co-authors of Kyungbook Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Kyungbook Lee. A scholar is included among the top collaborators of Kyungbook Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kyungbook Lee. Kyungbook Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Shin, Hyundon, et al.. (2026). Impact of Non‐Condensable Gas Selection on CO ₂ Mitigation and Economic Viability in Steam and Gas Push. International Journal of Energy Research. 2026(1).

Lee, Kyungbook, et al.. (2026). Development of machine learning-based TOC estimation model using well logging and sidewall core data for source rock evaluation in the Jeju Basin, South Sea of Korea. Journal of the geological society of Korea. 62(1). 123–133. 1 indexed citations

Lee, Kyungbook, et al.. (2026). Exploration history and petroleum systems of the South Sea of Korea: Recent advances and perspectives. Journal of the geological society of Korea. 62(1). 5–22. 2 indexed citations

Zhang, Zhun, Liangxiao Jiang, Zhichao Liu, et al.. (2025). WirMAE: Learning Well-Logging Interval Representations via Masked Autoencoders for Gas Hydrate Reservoir Characterization. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–16.

Park, Juyoung, et al.. (2024). Effect of preprocessing on performances of machine learning-based mineral composition analysis on gas hydrate sediments, Ulleung Basin, East Sea. Petroleum Science. 22(1). 151–162.

Shin, Hyundon, et al.. (2024). Analysis of Non-condensable Gas Injection Timing in eMSAGP Method for Oil Sands Reservoir with Thief Zone. Journal of the Korean Society of Mineral and Energy Resources Engineers. 61(3). 182–190.

Chang, Chandong, et al.. (2024). Development of Deep Learning-Based Detection Model for Borehole Breakout Depths in Image Logs. Journal of the Korean Society of Mineral and Energy Resources Engineers. 61(6). 468–479. 1 indexed citations

Lee, Kyungbook, et al.. (2024). Effects of aquifer size and formation fracture pressure on CO2 geological storage capacity. Frontiers in Energy Research. 12. 4 indexed citations

Liu, Zhichao, et al.. (2023). Missing Sonic Logs Generation for Gas Hydrate-Bearing Sediments via Hybrid Networks Combining Deep Learning With Rock Physics Modeling. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–15. 10 indexed citations

10.

Lee, Kyungbook, et al.. (2023). Numerical approach on production optimization of high water-cut well via advanced completion management using flow control valves. Journal of Petroleum Exploration and Production Technology. 13(7). 1611–1625. 7 indexed citations

11.

Lee, Kyungbook, et al.. (2022). Spatiotemporal interpretation of three-phase saturation behaviors in gas hydrate formation and dissociation through deep learning modeling. Geoenergy Science and Engineering. 221. 111219–111219. 3 indexed citations

12.

Lee, Kyungbook, et al.. (2021). Directional Hydraulic Characteristics of Reservoir Rocks for CO2 Geological Storage in the Pohang Basin, Southeast Korea. Energies. 14(8). 2211–2211. 4 indexed citations

13.

Lee, Kyungbook, et al.. (2021). Evaluation of saturation changes during gas hydrate dissociation core experiment using deep learning with data augmentation. Journal of Petroleum Science and Engineering. 209. 109820–109820. 16 indexed citations

14.

Lee, Kyungbook, et al.. (2020). Data-Driven Three-Phase Saturation Identification from X-ray CT Images with Critical Gas Hydrate Saturation. Energies. 13(21). 5844–5844. 15 indexed citations

15.

Lee, Kyungbook, et al.. (2020). Saturation Modeling of Gas Hydrate Using Machine Learning with X-Ray CT Images. Energies. 13(19). 5032–5032. 20 indexed citations

16.

Kang, Byeong‐Cheol & Kyungbook Lee. (2020). Managing Uncertainty in Geological Scenarios Using Machine Learning-Based Classification Model on Production Data. Geofluids. 2020. 1–16. 7 indexed citations

17.

Kang, Byeong‐Cheol, Sungil Kim, Hyungsik Jung, Jonggeun Choe, & Kyungbook Lee. (2019). Efficient Assessment of Reservoir Uncertainty Using Distance-Based Clustering: A Review. Energies. 12(10). 1859–1859. 21 indexed citations

18.

Lee, Kyungbook, Sungil Kim, Jonggeun Choe, Baehyun Min, & Hyun Suk Lee. (2018). Iterative static modeling of channelized reservoirs using history-matched facies probability data and rejection of training image. Petroleum Science. 16(1). 127–147. 12 indexed citations

19.

Lee, Kyungbook, et al.. (2017). Classification and Example of Assessment Methodologies for Shale Resources. Journal of the Korean Society of Mineral and Energy Resources Engineers. 54(2). 185–200.

20.

Yun, Young Ho, et al.. (2005). Predictors of prescription of morphine for severe cancer pain by physicians in Korea. Annals of Oncology. 16(6). 966–971. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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