Mailing Address
Tsubasa Onishi
Geothermal Energy & Geofluids
Institute of Geophysics
NO F 61.1
Sonneggstrasse 5
CH-8092 Zurich Switzerland
Publications
[Go to Proceedings Refereed] [Go to Proceedings Non-Refereed] [Go to Theses]
Underlined names are links to current or past GEG members
REFEREED PUBLICATIONS IN JOURNALS
10.
Yang, C, J He, T Onishi, S Du, X Guan, J Chen, and X Wen, A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models, SPE Journal, 2022. https://doi.org/10.2118/204004-PA [Download] [View Abstract]Please enter abstract here
9.
Onishi, T, S Tanaka, H Chen, D Kam, J Xie, Z Wang, and X Wen, Streamline Tracing and Applications in Dual-Porosity Dual-Permeability Models, SPE Journal, 2022. https://doi.org/10.2118/203993-PA [Download] [View Abstract]Please enter abstract here
8.
Chen, H, T Onishi, J Park, and A Datta-Gupta, Computing pressure front propagation using the diffusive-time-of-flight in structured and unstructured grid systems via the fast-marching Method, SPE Journal, 2021. https://doi.org/10.2118/201771-PA [Download] [View Abstract]Please enter abstract here
7.
Kim, H, T Onishi, H Chen, and A Datta-Gupta, Parameterization of embedded discrete fracture models (EDFM) for efficient history matching of fractured reservoirs, Journal of Petroleum Science and Engineering, 2021. https://doi.org/10.1016/j.petrol.2021.108681 [Download] [View Abstract]Please enter abstract here
6.
Chen, H, T Onishi, F Olalotiti-Lawal, and A Datta-Gupta, Streamline tracing and applications in embedded discrete fracture models, Journal of Petroleum Science and Engineering, 2020. https://doi.org/10.1016/j.petrol.2019.106865 [Download] [View Abstract]Please enter abstract here
5.
Pawar, R, S Chu, N Makedonska, T Onishi, and D Harp, Assessment of relationship between post-injection plume migration and leakage risks at geologic CO2 storage sites, International Journal of Greenhouse Gas Control, 2020. https://doi.org/10.1016/j.ijggc.2020.103138 [Download] [View Abstract]Please enter abstract here
4.
Onishi, T, M Nguyen, J Carey, B Will, W Zaluski, D Bowen, B Devault, A Duguid, Q Zhou, S Fairweather, and L Spangler, Potential CO2 and brine leakage through wellbore pathways for geologic CO2 sequestration using the National Risk Assessment Partnership tools: Application to the Big Sky Regional Partnership, International Journal of Greenhouse Gas Control, 2019. https://doi.org/10.1016/j.ijggc.2018.12.002 [Download] [View Abstract]Please enter abstract here
3.
Olalotiti-Lawal, F, T Onishi, H Kim, A Datta-Gupta, Y Fujita, and K Hagiwara, Post-combustion carbon dioxide enhanced-oil-recovery development in a mature oil field: model calibration using a hierarchical approach, SPE Reservoir Evaluation & Engineering, 2019. https://doi.org/10.2118/187116-PA [Download] [View Abstract]Please enter abstract here
2.
Harp, D, T Onishi, S Chu, B Chen, and R Pawar, Development of quantitative metrics of plume migration at geologic CO2 storage sites, Greenhouse Gases: Science and Technology, 2019. https://doi.org/10.1002/ghg.1903 [Download] [View Abstract]Please enter abstract here
1.
Xue, X, C Yang, T Onishi, M King, and A Datta–Gupta, Modeling hydraulically fractured shale wells using the fast-marching method with local grid refinements and an embedded discrete fracture model, SPE Journal, 2019. https://doi.org/10.2118/193822-PA [Download] [View Abstract]Please enter abstract here
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PROCEEDINGS REFEREED
12.
Ren, G, Z Wang, Y Lin, T Onishi, X Guan, and X Wen, A Fast History Matching and Optimization Tool and its Application to a Full Field with More than 1,000 Wells, SPE Reservoir Simulation Conference, 2023. https://doi.org/10.2118/212188-MS [Download] [View Abstract]Please enter abstract here
11.
Nagao, M, A Datta-Gupta, T Onishi, and S Sankaran, Reservoir Connectivity Identification and Robust Production Forecasting Using Physics Informed Machine Learning, SPE Reservoir Simulation Conference, 2023. https://doi.org/10.2118/212201-MS [Download] [View Abstract]Please enter abstract here
10.
Nagao, M, C Yao, T Onishi, H Chen, and A Datta-Gupta, An Efficient Deep Learning-Based Workflow for CO2 Plume Imaging Using Distributed Pressure and Temperature Measurements, SPE Annual Technical Conference and Exhibition, 2022. https://doi.org/10.2118/210309-MS [Download] [View Abstract]Please enter abstract here
9.
Nagao, M, C Yao, T Onishi, H Chen, A Datta-Gupta, and S Mishra, An Efficient Deep Learning-Based Workflow for CO2 Plume Imaging Considering Model Uncertainties Using Distributed Pressure and Temperature Measurements, The 16th Greenhouse Gas Control Technologies Conference (GHGT-16), 2022. https://doi.org/10.2139/ssrn.4280048 [Download] [View Abstract]Please enter abstract here
8.
Pawar, R, S Chu, N Makedonska, T Onishi, and D Harp, Evaluation of relationship between post-injection plume stability and leakage risks, The 15th Greenhouse Gas Control Technologies Conference, 2021. https://doi.org/10.2139/ssrn.3820715 [Download] [View Abstract]Please enter abstract here
7.
Onishi, T, H Chen, A Datta-Gupta, and S Mishra, An Efficient Deep Learning-Based Workflow Incorporating a Reduced Physics Model for Subsurface Imaging in Unconventional Reservoirs, SPE Annual Technical Conference and Exhibition, 2021. https://doi.org/10.2118/206065-MS [Download] [View Abstract]Please enter abstract here
6.
Yao, C, H Chen, T Onishi, A Datta-Gupta, S Mawalkar, S Mishra, and A Pasumarti, Robust CO2 Plume Imaging Using Joint Tomographic Inversion of Distributed Pressure and Temperature Measurements, SPE Annual Technical Conference and Exhibition, 2021. https://doi.org/10.2118/206249-MS [Download] [View Abstract]Please enter abstract here
5.
Tanaka, S, T Onishi, D Kam, K Dehghani, and X Wen, Application of Combined Streamline-Based Reduced-physics Surrogate and Response Surface Method for Field Development Optimization, IPTC 2020, 2020. https://doi.org/10.2523/IPTC-19958-MS [Download] [View Abstract]Please enter abstract here
4.
Iino, A, H Jung, T Onishi, and A Datta-Gupta, Rapid simulation accounting for well interference in unconventional reservoirs using fast marching method, SPE/AAPG/SEG Unconventional Resources Technology Conference, 2020. https://doi.org/10.15530/urtec-2020-2468 [Download] [View Abstract]Please enter abstract here
3.
Jung, H, T Onishi, and A Datta-Gupta, Numerical simulation of EOR from wettability alteration in tight oil reservoir with multiple hydraulic fractures, SPE Annual Technical Conference and Exhibition, 2018. https://doi.org/10.2118/191409-MS [Download] [View Abstract]Please enter abstract here
2.
Iino, A, T Onishi, F Olalotiti-Lawal, and A Datta-Gupta, Rapid field-scale well spacing optimization in tight and shale oil reservoirs using fast marching method, Unconventional Resources Technology Conference, 2018. https://doi.org/10.15530/urtec-2018-2901376 [Download] [View Abstract]Please enter abstract here
1.
Aoi, E, T Onishi, and M Kurihara, Development of Two Geostatistical Programs: Program-1 for Estimating Categorical Variable Distribution by Multiple-Point Statistics; Program-2 for Optimizing Estimates by Program-1 Applying Genetic Algorithm , SPWLA 21st Formation Evaluation Symposium of Japan, 2015. [Download PDF] [View Abstract]Please enter abstract here
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THESES
2.
Onishi, T, Effective Reservoir Management for Unconventional Reservoirs Using the Fast Marching Method and Machine Learning, Dissertation, pp., 2021. [Download PDF] [View Abstract]Please enter abstract here
1.
Onishi, T, Effective Modeling Approaches for CO2 EOR Developments, MSc Thesis, pp., 2017. [Download PDF] [View Abstract]Please enter abstract here