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Author

Shungo Abe

Observed names: Abe, Shungo, Shungo Abe3
ORCID: 0009-0006-7307-5216
Observed ORCID: 0009-0006-7307-5216
OpenAlex ID: A5039475687
Experimental study of mud erosion at the interface of an artificial sand-mud alternate layer
2016 · Hiroyuki Oyama, Shungo Abe, et al. · Journal of Natural Gas Science and Engineering · 18
Hybrid Approach Using Physical Insights and Data Science for Stuck-Pipe Prediction
2023 · Tatsuya Kaneko, Tomoya Inoue, et al. · SPE Journal · 13
An Unsupervised Learning Model for Pipe Stuck Predictions Using a Long Short-Term Memory Autoencoder Architecture
2021 · Yujin Nakagawa, Tomoya Inoue, et al. · SPE Asia Pacific Oil and Gas Conference and Exhibition · 13
Multiphysical Responses of a Gas Hydrate Reservoir to Extended-Duration Gas Production on the Alaska North Slope
2026 · Satoshi Ohtsuki, Yutaro Arima, et al. · Energy & Fuels · 10
Hybrid Approach Using Physical Insights and Data Science for Early Stuck Detection
2023 · Tatsuya Kaneko, Tomoya Inoue, et al. · Offshore Technology Conference · 9
Real-Time Mud Motor Stall Detection Using Downhole and Surface Data for Improved Performance Management and Failure Mitigation
2022 · Mohammed Alameer, Akshat Patni, et al. · SPE Annual Technical Conference and Exhibition · 9
Approach for Real-Time Prediction of Pipe Stuck Risk Using a Long Short-Term Memory Autoencoder Architecture
2021 · Yujin Nakagawa, Tomoya Inoue, et al. · Abu Dhabi International Petroleum Exhibition & Conference (ADIPEC) · 9
Early Stuck Detection Using Supervised and Unsupervised Machine Learning Approaches
2022 · Tomoya Inoue, Yujin Nakagawa, et al. · Offshore Technology Conference Asia · 8
Characterization of Formation Deformation during Production Test from Gas Hydrate in Alaska: A Distributed Fiber Optic Sensing Approach
2026 · Shungo Abe, Kenichi Soga, et al. · Energy & Fuels · 7
Attempt of Early Stuck Detection Using Unsupervised Deep Learning With Probability Mixture Model
2021 · Tomoya Inoue, Yujin Nakagawa, et al. · International Conference on Offshore Mechanics and Arctic Engineering (OMAE) · 7
Field Validation of a Universally Applicable Condition-Based Maintenance System for Mud Pumps
2024 · Dongyoung Yoon, Pradeepkumar Ashok, et al. · SPE Journal · 4
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Field Validation of Scalable Condition-Based Maintenance (CBM) of Mud Pumps
2023 · Dongyoung Yoon, Pradeepkumar Ashok, et al. · SPE/IADC Drilling Conference · 4
Early Stuck Pipe Detection Using Graph Attention Machine Learning
2023 · Tomoya Inoue, Yujin Nakagawa, et al. · International Conference on Offshore Mechanics and Arctic Engineering (OMAE) · 3
A Novel Approach of Machine Learning Incorporating Physical Knowledge of Hook Load for Early Stuck Detection
2024 · Tomoya Inoue, Yujin Nakagawa, et al. · Offshore Technology Conference Asia · 2
Experimental Study of Mud Erosion Phenomena at Sand Mud Alternate Layer
2015 · Hiroyuki Oyama, Shungo Abe, et al. · 2
A Novel Approach of Data Science Incorporating Physical Knowledge for Early Stuck Pipe Detection
2024 · Tomoya Inoue, Tatsuya Kaneko, et al. · International Conference on Offshore Mechanics and Arctic Engineering (OMAE) · 1
Experimental studies on sand production and model improvements
2026 · Shungo Abe, Shun Uchida, et al. · SSRN Electronic Journal
Experimental Verification of Blocking a Water-Bearing Zone Using CO2 Reactive Grout for Methane Hydrate Development
2025 · Rongchang Zhang, Takatoshi Ito, et al. · Energies
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Numerical study on strategies to mitigate sand production risk in gas hydrate reservoirs
2025 · Uchida, Shun, Abe, Shungo · HAL
Study on the applicability of waterglass-based chemical for water management during gas hydrate production
2023 · Shungo Abe, Takatoshi Ito, et al. · Journal of the Japanese Association for Petroleum Technology
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JOGMEC research activities on application of digital technology into drilling field and future perspectives
2022 · Ryosuke Sato, Ryuta Kitamura, et al. · Journal of the Japanese Association for Petroleum Technology
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Trends in oil producing countries for well P&A and decommissioning
2021 · Hiroyasu Kudo, Norihito Inada, et al. · Journal of the Japanese Association for Petroleum Technology
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Works count: 22
Citation count: 119
H-index: 8
I10-index: 4
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