| Reduced-order modeling for compositional simulation by use of trajectory piecewise linearization J He, LJ Durlofsky SPE Journal 19 (05), 858-872, 2014 | 141 | 2014 |
| Enhanced linearized reduced-order models for subsurface flow simulation J He, J Sætrom, LJ Durlofsky Journal of Computational Physics 230 (23), 8313-8341, 2011 | 110 | 2011 |
| Reduced-order flow modeling and geological parameterization for ensemble-based data assimilation J He, P Sarma, LJ Durlofsky Computers & geosciences 55, 54-69, 2013 | 74 | 2013 |
| Constraint reduction procedures for reduced‐order subsurface flow models based on POD–TPWL J He, LJ Durlofsky International Journal for Numerical Methods in Engineering 103 (1), 1-30, 2015 | 60 | 2015 |
| Implementation of physics-based data-driven models with a commercial simulator G Ren, J He, Z Wang, RM Younis, XH Wen SPE Reservoir Simulation Conference?, D010S017R010, 2019 | 57 | 2019 |
| Uncertainty quantification and value of information assessment using proxies and Markov chain Monte Carlo method for a pilot project B Chen, J He, XH Wen, W Chen, AC Reynolds Journal of Petroleum Science and Engineering 157, 328-339, 2017 | 49 | 2017 |
| Proxy-based work flow for a priori evaluation of data-acquisition programs J He, J Xie, P Sarma, XH Wen, WH Chen, J Kamath SPE Journal 21 (04), 1400-1412, 2016 | 49 | 2016 |
| Use of reduced-order models for improved data assimilation within an EnKF context J He, P Sarma, LJ Durlofsky SPE Reservoir Simulation Conference?, SPE-141967-MS, 2011 | 46 | 2011 |
| Deep reinforcement learning for generalizable field development optimization J He, M Tang, C Hu, S Tanaka, K Wang, XH Wen, Y Nasir SPE Journal 27 (01), 226-245, 2022 | 43 | 2022 |
| Large scale field development optimization using high performance parallel simulation and cloud computing technology S Tanaka, Z Wang, K Dehghani, J He, B Velusamy, XH Wen SPE Annual Technical Conference and Exhibition?, D031S030R007, 2018 | 41 | 2018 |
| Reduced-Order Modeling for Oil-Water and Compositional Systems, with Application to Data Assimilation and Production Optimization J He Stanford University, 2013 | 38 | 2013 |
| Fast history matching and optimization using a novel physics-based data-driven model: an application to a diatomite reservoir Z Wang, J He, WJ Milliken, XH Wen SPE Journal 26 (06), 4089-4108, 2021 | 37 | 2021 |
| A physics-based data-driven model for history matching, prediction, and characterization of unconventional reservoirs Y Zhang, J He, C Yang, J Xie, R Fitzmorris, XH Wen SPE Journal 23 (04), 1105-1125, 2018 | 35 | 2018 |
| An alternative proxy for history matching using proxy-for-data approach and reduced order modeling J He, J Xie, XH Wen, W Chen Journal of Petroleum Science and Engineering 146, 392-399, 2016 | 34 | 2016 |
| Quantifying expected uncertainty reduction and value of information using ensemble-variance analysis J He, P Sarma, E Bhark, S Tanaka, B Chen, XH Wen, J Kamath SPE Journal 23 (02), 428-448, 2018 | 32 | 2018 |
| Improved proxy for history matching using proxy-for-data approach and reduced order modeling J He, J Xie, XH Wen, W Chen SPE Western Regional Meeting, SPE-174055-MS, 2015 | 32 | 2015 |
| Deep reinforcement learning for constrained field development optimization in subsurface two-phase flow Y Nasir, J He, C Hu, S Tanaka, K Wang, XH Wen Frontiers in Applied Mathematics and Statistics 7, 689934, 2021 | 26 | 2021 |
| An iterative scheme to construct robust proxy models A Castellini, H Gross, Y Zhou, J He, W Chen ECMOR XII-12th European Conference on the Mathematics of Oil Recovery, cp …, 2010 | 25 | 2010 |
| Iterative method and system to construct robust proxy models for reservoir simulation A Castellini, H Gross, Y Zhou, J He, WH Chen US Patent 8,855,986, 2014 | 22 | 2014 |
| Rapid S-curve update using ensemble variance analysis with model validation J He, S Tanaka, XH Wen, J Kamath SPE Western Regional Meeting, D041S012R003, 2017 | 19 | 2017 |
Louis DurlofskyProfessor of Energy Science and Engineering, Stanford UniversityVerified email at stanford.edu