| Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data S Sinha, RP de Lima, Y Lin, AY Sun, N Symons, R Pawar, G Guthrie International Journal of Greenhouse Gas Control 103, 103189, 2020 | 28 | 2020 |
| Multivariate statistical analysis for resource estimation in unconventional plays application to Eagle Ford shales S Sinha, D Devegowda, B Deka SPE Eastern Regional Meeting, SPE-184050-MS, 2016 | 17 | 2016 |
| Effect of Frequent Well Shut-In's on Well Productivity: Marcellus Shale Case Study S Sinha, KJ Marfurt, B Deka SPE Eastern Regional Meeting, D023S004R001, 2017 | 15 | 2017 |
| Statistical controls on induced seismicity S Sinha, Y Wen, R Pires De Lima, K Marfurt Unconventional Resources Technology Conference, Houston, Texas, 23-25 July …, 2018 | 10 | 2018 |
| Quantification of recovery factors in downspaced wells: Application to the eagle ford shale S Sinha, D Devegowda, B Deka SPE Western Regional Meeting, D041S008R008, 2017 | 8 | 2017 |
| Improving fault delineation using maximum entropy multispectral coherence B Lyu, J Qi, S Sinha, J Li, KJ Marfurt Interpretation 8 (4), T835-T850, 2020 | 7 | 2020 |
| Seismic to Simulation: Woodford Shale Case Study in Oklahoma, USA EJ Torres-Parada, S Sinha, LE Infante-Paez, RM Slatt, KJ Marfurt Unconventional Resources Technology Conference, Houston, Texas, 23-25 July …, 2018 | 6 | 2018 |
| Seismic inversion based SRV and reserves estimation for shale plays S Sinha, KJ Marfurt, D Devegowda, R Pires de Lima, S Verma SPE Annual Technical Conference and Exhibition?, D031S031R004, 2017 | 6 | 2017 |
| PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt S Sinha, Y Chen, Y Lin, R Pires de Lima Space Weather 19 (9), e2021SW002773, 2021 | 4 | 2021 |
| Quantification of Recovery Factors in Downspaced Shale Wells: Application of a Fully Coupled Geomechanical EOS compositional Simulator S Sinha, D Devegowda Unconventional Resources Technology Conference, Austin, Texas, 24-26 July …, 2017 | 4 | 2017 |
| Leak detection in carbon sequestration projects using machine learning methods: Cranfield site, Mississippi, USA S Sinha, R Pires De Lima, Y Lin, A Y. Sun, N Symon, R Pawar, G Guthrie SPE Annual Technical Conference and Exhibition?, D031S022R007, 2020 | 3 | 2020 |
| Well-log attributes to map upward-fining and upward-coarsening parasequences S Sinha, RP de Lima, J Qi, L Infante-Paez, K Marfurt SEG International Exposition and Annual Meeting, SEG-2018-2998559, 2018 | 3 | 2018 |
| Identification and Quantification of Parasequences Using Expectation Maximization Filter: Defining Well Log Attributes for Reservoir Characterization S Sinha*, R Kiran, J Tellez, K Marfurt Unconventional Resources Technology Conference, Denver, Colorado, 22-24 July …, 2019 | 2 | 2019 |
| Statistical and Deep Learning Methods for Geoscience Problems S Sinha University of Oklahoma, 2021 | 1 | 2021 |
| Machine learning generated predictive model to forecast the dynamic flux distributions of ultra-relativistic electrons Y Chen, Y Lin, RP de Lima, S Sinha US Patent App. 17/499,591, 2023 | | 2023 |
| PreMevE: A Machine-Learning Based Predictive Model for MeV Electrons inside Earth's Outer Radiation Belt Y Chen, R Pires de Lima, S Sinha, Y Lin EGU General Assembly Conference Abstracts, EGU21-8545, 2021 | | 2021 |
| Automatic Leak Detection in Carbon Sequestration Projects S Sinha | | 2020 |
| Attribute-driven residual lateral moveout correction for azimuthally limited seismic volumes J Qi, J Zhang, S Sinha, K Marfurt SEG International Exposition and Annual Meeting, D043S115R006, 2019 | | 2019 |
| Quantification of recovery factors in downspaced shale wells S Sinha | | 2016 |
| From Unconventional Reservoir Characterization, 3D Seismic multi-attribute analysis and machine learning guided geocellular modeling to Well Performance (EUR) Simulation … ET Parada, S Sinha, L Infante-Paez, R Slatt, K Marfurt 2019 AAPG Annual Convention and Exhibition:, 0 | | |
Rafael Pires de LimaData Scientist, VerAI DiscoveriesAdresse e-mail validée de ver-ai.com
