Machine learning augmented dead oil viscosity model for all oil types U Sinha, B Dindoruk, M Soliman Journal of Petroleum Science and Engineering 195, 107603, 2020 | 34 | 2020 |
Prediction of CO2 minimum miscibility pressure using an augmented machine-learning-based model U Sinha, B Dindoruk, M Soliman SPE Journal 26 (04), 1666-1678, 2021 | 33 | 2021 |
Prediction of CO2 minimum miscibility pressure MMP using machine learning techniques U Sinha, B Dindoruk, M Soliman SPE Improved Oil Recovery Conference, 2020 | 26 | 2020 |
Development of a new correlation to determine relative viscosity of heavy oils with varying asphaltene content and temperature U Sinha, B Dindoruk, MY Soliman Journal of Petroleum Science and Engineering 173, 1020-1030, 2019 | 18 | 2019 |
Physics augmented correlations and machine learning methods to accurately calculate dead oil viscosity based on the available inputs U Sinha, B Dindoruk, MY Soliman SPE Journal 27 (05), 3240-3253, 2022 | 9 | 2022 |
Physics guided data-driven model to estimate minimum miscibility pressure (MMP) for hydrocarbon gases U Sinha, B Dindoruk, M Soliman Geoenergy Science and Engineering 224, 211389, 2023 | 8 | 2023 |
Physics guided data driven model to forecast production rates in liquid wells U Sinha, H Zalavadia, S Sankaran SPE Oklahoma City Oil and Gas Symposium/Production and Operations Symposium …, 2023 | 8 | 2023 |
An Improved Method for GOR Forecasting in Unconventionals H Zalavadia, U Sinha, S Sankaran Unconventional Resources Technology Conference, Houston, Texas, USA, June 2022., 2022 | 8 | 2022 |
A Comparative Analysis of the Prediction of Gas Condensate Dew Point Pressure Using Advanced Machine Learning Algorithms T Lertliangchai, B Dindoruk, L Lu, X Yang, U Sinha Fuels 5 (3), 548-563, 2024 | 4 | 2024 |
Improving artificial lift timing, selection, and operations strategy using a physics informed data-driven method H Zalavadia, P Singh, U Sinha, S Sankaran Unconventional Resources Technology Conference, 13–15 June 2023, 772-794, 2023 | 4 | 2023 |
Using hybrid models for unconventional production opportunities and value generation—Case studies H Zalavadia, T Stoddard, U Sinha, A Corman, S Sankaran Unconventional Resources Technology Conference, 20–22 June 2022, 1960-1979, 2022 | 3 | 2022 |
A New Physics-Based CO2 EOR Screening Tool for Offshore Applications A Abdulwarith, U Sinha, S Gautam, B Dindoruk SPE Improved Oil Recovery Conference?, D031S022R001, 2024 | 2 | 2024 |
Unconventional well interference detection using physics informed data-driven model U Sinha, PS Chauhan, H Zalavadia, S Sankaran, C Chen SPE/AAPG/SEG Unconventional Resources Technology Conference, D011S015R001, 2023 | 2 | 2023 |
Real Time Artificial Lift Timing and Selection Using Hybrid Data-Driven and Physics Models H Zalavadia, M Gokdemir, U Sinha, P Singh, S Sankaran SPE Western Regional Meeting, D041S014R001, 2023 | 2 | 2023 |
Estimation of Dead Oil Viscosity Utilizing Physics Based Correlative Principles and Predictive Machine Learning Techniques. U Sinha, B Dindoruk, M Soliman SPE Annual Technical Conference and Exhibition?, D031S054R003, 2019 | 2 | 2019 |
Machine Learning-Enhanced Forecasting for Efficient Water-Flooded Reservoir Management U Sinha, S Gautam, B Dindoruk, A Abdulwarith SPE Improved Oil Recovery Conference?, D041S029R001, 2024 | 1 | 2024 |
Gas-oil ratio forecasting in unconventional reservoirs S Sankaran, H Zalavadia, U Sinha US Patent 11,767,750, 2023 | 1 | 2023 |
Physics informed data-driven models for discovery of flow physics and forecasts in unconventional reservoirs H Zalavadia, U Sinha, P Singh, Z Guo, S Sankaran Unconventional Resources Technology Conference, 13–15 June 2023, 1847-1877, 2023 | 1 | 2023 |
Hybrid Multiphase Rate Forecasting Model in Liquid Wells for Unconventional Reservoirs U Sinha, H Zalavadia, PS Chauhan, S Sankaran SPE Western Regional Meeting, D031S008R004, 2023 | 1 | 2023 |
Discovery of Unconventional Reservoir Flow Physics for Production Forecasting Through Hybrid Data-Driven and Physics Models H Zalavadia, U Sinha, P Singh, S Sankaran SPE Western Regional Meeting, D031S011R007, 2023 | 1 | 2023 |