| Systems analysis for deployment of internet of things (IoT) in the maritime industry K Hiekata, S Wanaka, T Mitsuyuki, R Ueno, R Wada, B Moser Journal of Marine Science and Technology 26, 459-469, 2021 | 43 | 2021 |
| Longitudinal natural vibration of ultra-long drill string during offshore drilling R Wada, T Kaneko, M Ozaki, T Inoue, H Senga Ocean Engineering 156, 1-13, 2018 | 38 | 2018 |
| Early stuck pipe sign detection with depth-domain 3D convolutional neural network using actual drilling data N Tsuchihashi, R Wada, M Ozaki, T Inoue, KR Mopuri, H Bilen, ... SPE Journal 26 (02), 551-562, 2021 | 36 | 2021 |
| Early sign detection for the stuck pipe scenarios using unsupervised deep learning KR Mopuri, H Bilen, N Tsuchihashi, R Wada, T Inoue, K Kusanagi, ... Journal of Petroleum Science and Engineering 208, 109489, 2022 | 33 | 2022 |
| Extreme value estimation using the likelihood-weighted method R Wada, T Waseda, P Jonathan Ocean Engineering 124, 241-251, 2016 | 22 | 2016 |
| A simple spatial model for extreme tropical cyclone seas R Wada, T Waseda, P Jonathan Ocean Engineering 169, 315-325, 2018 | 14 | 2018 |
| Numerical modelling of a relatively small floating body’s wave and low frequency motion response, compared with observational data C Wright, H Yoshimoto, R Wada, K Takagi International Conference on Offshore Mechanics and Arctic Engineering 58882 …, 2019 | 13 | 2019 |
| An unsupervised learning model for pipe stuck predictions using a long short-term memory autoencoder architecture Y Nakagawa, T Inoue, H Bilen, KR Mopuri, K Miyoshi, S Abe3, R Wada, ... SPE Asia Pacific Oil and Gas Conference and Exhibition, D011S009R006, 2021 | 12 | 2021 |
| Assessment of data-inherited uncertainty in extreme wave analysis R Wada, T Waseda Journal of Offshore Mechanics and Arctic Engineering 142 (2), 021204, 2020 | 11 | 2020 |
| Prediction of wave time-history using multipoint measurements K Takagi, S Hamamichi, R Wada, Y Sakurai Ocean Engineering 140, 412-418, 2017 | 11 | 2017 |
| Attempt of early stuck detection using unsupervised deep learning with probability mixture model T Inoue, Y Nakagawa, R Wada, K Miyoshi, S Abe, K Kuroda, H Tamamura, ... International Conference on Offshore Mechanics and Arctic Engineering 85208 …, 2021 | 10 | 2021 |
| Combining physics-based and data-driven models for estimation of WOB during ultra-deep ocean drilling T Kaneko, R Wada, M Ozaki, T Inoue International Conference on Offshore Mechanics and Arctic Engineering 51296 …, 2018 | 10 | 2018 |
| Benchmark for the sources of uncertainty in extreme wave analysis R Wada, T Waseda International Conference on Offshore Mechanics and Arctic Engineering 51227 …, 2018 | 9 | 2018 |
| Approach for Real-Time Prediction of Pipe Stuck Risk Using a Long Short-Term Memory Autoencoder Architecture Y Nakagawa, T Inoue, H Bilen, KR Mopuri, K Miyoshi, S Abe, R Wada, ... Abu Dhabi International Petroleum Exhibition and Conference, D041S112R001, 2021 | 8 | 2021 |
| Well Design for Methane Hydrate Production: developing a low-cost production well for offshore Japan M Yamamoto, K Miura, R Wada, K Takagi Offshore Technology Conference Asia, D021S011R001, 2018 | 8 | 2018 |
| Hybrid approach using physical insights and data science for early stuck detection T Kaneko, T Inoue, Y Nakagawa, R Wada, K Miyoshi, S Abe, K Kuroda, ... Offshore Technology Conference, D021S020R003, 2023 | 7 | 2023 |
| Early Stuck Detection Using Supervised and Unsupervised Machine Learning Approaches T Inoue, Y Nakagawa, R Wada, K Miyoshi, S Abe, K Kuroda, M Nishi, ... Offshore Technology Conference Asia, D041S043R002, 2022 | 7 | 2022 |
| Diffraction problem of a floating breakwater with an array of small ports R Mondal, K Takagi, R Wada Journal of Marine Science and Technology 22, 459-469, 2017 | 7 | 2017 |
| Combining statistical and dynamical approaches in resource assessments of ocean wave, ocean current and tidal current power T Waseda, K Kiyomatsu, A Ribal, Y Kidoura, R Wada Renewable Energies Offshore, CG Soares, ed, 123-128, 2015 | 7 | 2015 |
| Statistical estimation of spatial wave extremes for tropical cyclones from small data samples: validation of the STM-E approach using long-term synthetic cyclone data for the … R Wada, J Rohmer, Y Krien, P Jonathan Natural Hazards and Earth System Sciences 22 (2), 431-444, 2022 | 6 | 2022 |
