OMAE2020-19169 Attempt of a Real-Time Drilling State Identification With Machine Learning

von Inoue, Tomoya
Veröffentlicht in ASME International Conference on Ocean, Offshore and Arctic Engineering (39. : 2020 : Online) Proceedings of the ASME 39th International Conference on Ocean, Offshore and Arctic Engineering - 2020 ; Volume 11: Petroleum technology (2020)

Analytical, Numerical, and Field Data Investigation for Deriving the Condition of Stick-Slip Drill String Vibration

von Kaneko, Tatsuya
Veröffentlicht in ASME International Conference on Ocean, Offshore & Arctic Engineering (42. : 2023 : Melbourne) Proceedings of ASME 2023 42nd International Conference on Ocean, Offshore & Arctic Engineering (OMAE 2023) ; Volume 9: Offshore geotechnics, petroleum technology (2023)

Early Stuck Pipe Detection Using Graph Attention Machine Learning

von Inoue, Tomoya
Veröffentlicht in ASME International Conference on Ocean, Offshore & Arctic Engineering (42. : 2023 : Melbourne) Proceedings of ASME 2023 42nd International Conference on Ocean, Offshore & Arctic Engineering (OMAE 2023) ; Volume 9: Offshore geotechnics, petroleum technology (2023)

GT2022-79379 Effect of Channel Size on Air-Cooling Performance in Interior Permanent Magnet (IPM) Motor Driving Aviation Fans at High Altitude

von Ito, Yu
Veröffentlicht in ASME Turbo Expo (67. : 2022 : Rotterdam) Proceedings of ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition (GT 2022) ; Volume 1: Aircraft engine, ceramics and ceramic composites (2022)

OMAE2021-62739 Attempt of Early Stuck Detection Using Unsupervised Deep Learning With Probability Mixture Model

von Inoue, Tomoya
Veröffentlicht in ASME International Conference on Ocean, Offshore and Arctic Engineering (40. : 2021 : Online) Proceedings of ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2021) ; Volume 10: Petroleum technology (2021)

Hybrid Approach Using Physical Insights and Data Science for Early Stuck Detection

von Kaneko, Tatsuya
Veröffentlicht in Offshore Technology Conference (2023 : Houston, Tex.) Offshore Technology Conference (OTC 2023) ; Volume 3 of 7 (2023)

AN UNSUPERVISED LEARNING MODEL FOR PIPE STUCK PREDICTIONS USING A LONG SHORT-TERM MEMORY AUTOENCODER ARCHITECTURE

von Nakagawa, Yujin
Veröffentlicht in SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition (2021 : Online) SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition 2021 ; Volume 2 of 5 (2021)

APPROACH FOR REAL-TIME PREDICTION OF PIPE STUCK RISK USING A LONG SHORT-TERM MEMORY AUTOENCODER ARCHITECTURE

von Nakagawa, Yujin
Veröffentlicht in ADIPEC (2021 : Abu Dhabi, Stadt) Abu Dhabi International Petroleum Exhibition & Conference 2021 ; Volume 12 of 13 (2022)