关注
Zhaoyang Larry Jin
Zhaoyang Larry Jin
在 stanford.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Deep-learning-based surrogate model for reservoir simulation with time-varying well controls
ZL Jin, Y Liu, LJ Durlofsky
Journal of Petroleum Science and Engineering 192, 107273, 2020
1062020
Reduced-order modeling of CO2 storage operations
ZL Jin, LJ Durlofsky
International Journal of Greenhouse Gas Control 68, 49-67, 2018
462018
Fast uncertainty quantification of reservoir simulation with variational U-Net
L Jin, H Lu, G Wen
arXiv preprint arXiv:1907.00718, 2019
202019
Deep-learning-based reduced-order modeling for subsurface flow simulation
ZL Jin, Y Liu, LJ Durlofsky
arXiv preprint arXiv:1906.03729, 2019
202019
Developing and Validating Simplified Predictive Models for CO2 Geologic Sequestration
LJD Srikanta Mishra, Priya Ravi Ganesh, Jared Schuetter, Jincong He ...
SPE Annual Technical Conference and Exhibition, 2015
152015
Reduced-order modeling of coupled flow and quasistatic geomechanics
ZL Jin, T Garipov, O Volkov, LJ Durlofsky
SPE Journal 25 (01), 326-346, 2020
132020
Simplified Predictive Models for CO2 Sequestration Performance Assessment: Research Topical Report on Task# 4-Reduced-Order Method (ROM) Based Models
S Mishra, L Jin, J He, L Durlofsky
Battelle Memorial Institute, Columbus, OH (United States), 2015
52015
Reduced-order modeling of coupled flow-geomechanics problems
ZL Jin, T Garipov, O Volkov, LJ Durlofsky
SPE Reservoir Simulation Conference?, D021S015R003, 2019
32019
Application of Reduced-Order Modeling for Geological Carbon Sequestration
LZ Jin
Stanford University, 2015
32015
New Techniques for Reduced-Order Modeling in Reservoir Simulation
ZL Jin
Stanford University, 2019
2019
Reduced-Order Models Based on POD-Tpwl for Compositional Subsurface Flow Simulation
LZJ LJ Durlofsky, J He
AGU Fall Meeting Abstracts 1, 05, 2014
2014
Extended QANet and Application on SQuAD 2.0
L Jin, Y Liu, S Jiang
系统目前无法执行此操作,请稍后再试。
文章 1–12