Louis J. Durlofsky
Affiliations: | Stanford University, Palo Alto, CA |
Area:
Petroleum Engineering, Hydrology, GeophysicsWebsite:
https://earth.stanford.edu/louis-durlofskyGoogle:
"Louis J Durlofsky"Bio:
Durlofsky, Louis J., Topics in fluid mechanics : I. flow between finite rotating disks II. simulation of hydrodynamically interacting particles in stokes flow, Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1986.
Mean distance: (not calculated yet)
Parents
Sign in to add mentor| John F. Brady | grad student | 1986 | MIT (Chemistry Tree) | |
| (Topics in fluid mechanics : I. flow between finite rotating disks II. simulation of hydrodynamically interacting particles in stokes flow) | ||||
Children
Sign in to add trainee| Christian Wolfsteiner | grad student | 2002 | Stanford |
| Burak Yeten | grad student | 2003 | Stanford |
| Mathieu Prevost | grad student | 2004 | Stanford |
| Yuguang Chen | grad student | 2005 | Stanford |
| Chuanping He | grad student | 2005 | Stanford |
| Mun-Hong (Robin) Hui | grad student | 2005 | Stanford |
| Pallav Sarma | grad student | 2006 | Stanford |
| Bin Gong | grad student | 2007 | Stanford |
| Marco A. Cardoso | grad student | 2009 | Stanford |
BETA: Related publications
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Publications
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| Liu Y, Durlofsky LJ. (2020) Multilevel Strategies and Geological Parameterizations for History Matching Complex Reservoir Models Spe Journal. 25: 81-104 |
| Jin ZL, Garipov T, Volkov O, et al. (2020) Reduced-Order Modeling of Coupled Flow and Quasistatic Geomechanics Spe Journal. 25: 326-346 |
| Jin ZL, Liu Y, Durlofsky LJ. (2020) Deep-learning-based surrogate model for reservoir simulation with time-varying well controls Journal of Petroleum Science and Engineering. 192: 107273 |
| Brito DUd, Durlofsky LJ. (2020) Well control optimization using a two-step surrogate treatment Journal of Petroleum Science and Engineering. 187: 106565 |
| Tang M, Liu Y, Durlofsky LJ. (2020) A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems Journal of Computational Physics. 413: 109456 |
| Brito DUd, Durlofsky LJ. (2020) Field development optimization using a sequence of surrogate treatments Computational Geosciences. 1-31 |
| Kostakis F, Mallison BT, Durlofsky LJ. (2020) Multifidelity framework for uncertainty quantification with multiple quantities of interest Computational Geosciences. 24: 761-773 |
| Jiang S, Sun W, Durlofsky LJ. (2020) A data-space inversion procedure for well control optimization and closed-loop reservoir management Computational Geosciences. 24: 361-379 |
| Jiang R, Durlofsky LJ. (2019) Implementation and detailed assessment of a GNAT reduced-order model for subsurface flow simulation Journal of Computational Physics. 379: 192-213 |
| Sun W, Durlofsky LJ. (2019) Data-space approaches for uncertainty quantification of CO2 plume location in geological carbon storage Advances in Water Resources. 123: 234-255 |