World's Best Scientists 2026 revealed!
Louis J. Durlofsky

Louis J. Durlofsky

D-Index & Metrics

Engineering and Technology

D-Index
83
Citations
22408
World Ranking
445
National Ranking
152

Louis J. Durlofsky publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Louis J. Durlofsky sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 295 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Louis J. Durlofsky D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Louis J. Durlofsky sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 83 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Louis J. Durlofsky is affiliated with Stanford University in the United States and primarily works in the field of Engineering. Their research encompasses a variety of subfields including Ocean Engineering, Mechanical Engineering, Environmental Engineering, Geophysics, and Geochemistry and Petrology.

The main topics of their work are centered on Reservoir Engineering and Simulation Methods, Hydraulic Fracturing and Reservoir Analysis, and Enhanced Oil Recovery Techniques. Additional research areas include CO2 Sequestration and Geologic Interactions, Drilling and Well Engineering, Seismic Imaging and Inversion Techniques, and Geological Modeling and Analysis.

Recent papers authored or co-authored by Durlofsky include:

  • A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems (2020), Journal of Computational Physics
  • Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow (2021), Computer Methods in Applied Mechanics and Engineering
  • Deep-learning-based surrogate model for reservoir simulation with time-varying well controls (2020), Journal of Petroleum Science and Engineering
  • Deep-learning-based coupled flow-geomechanics surrogate model for CO2 sequestration (2022), International Journal of Greenhouse Gas Control
  • 3D CNN-PCA: A deep-learning-based parameterization for complex geomodels (2020), Computers & Geosciences

Durlofsky has collaborated frequently with several researchers, notably Su Jiang, Haoyu Tang, Yusuf Nasir, Yifu Han, and Oleg Volkov.

Their work is published in a range of venues, including multiple publications in arXiv (Cornell University), SSRN Electronic Journal, Computational Geosciences, Journal of Computational Physics, and Journal of Petroleum Science and Engineering.

Best Publications

  • An Efficient Discrete-Fracture Model Applicable for General-Purpose Reservoir Simulators

    Mohammad Karimi-Fard;Louis J. Durlofsky;Khalid Aziz

  • Numerical calculation of equivalent grid block permeability tensors for heterogeneous porous media

    Louis J. Durlofsky

  • Dynamic simulation of hydrodynamically interacting particles

    L. Durlofsky;J. F. Brady;G. Bossis

  • Optimization of Nonconventional Well Type, Location, and Trajectory

    Burak Yeten;Louis J. Durlofsky;Khalid Aziz

  • Application of a particle swarm optimization algorithm for determining optimum well location and type

    Jérôme E. Onwunalu;Louis J. Durlofsky

  • A coupled local-global upscaling approach for simulating flow in highly heterogeneous formations

    Y. Chen;L.J. Durlofsky;L.J. Durlofsky;M. Gerritsen;X.H. Wen

  • Analysis of the Brinkman equation as a model for flow in porous media

    L. Durlofsky;J. F. Brady

  • Drift-Flux Modeling of Two-Phase Flow in Wellbores

    Hua Shi;Jonathan A. Holmes;Louis J. Durlofsky;Khalid Aziz

  • Efficient real-time reservoir management using adjoint-based optimal control and model updating

    Pallav Sarma;Louis J. Durlofsky;Khalid Aziz;Wen H. Chen

  • Experimental study of two and three phase flows in large diameter inclined pipes

    G. Oddie;H. Shi;L.J. Durlofsky;L.J. Durlofsky;K. Aziz

  • A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems

    Meng Tang;Yimin Liu;Louis J. Durlofsky

  • MODELING FLUID FLOW IN OIL RESERVOIRS

    Margot G. Gerritsen;Louis J. Durlofsky

  • Kernel Principal Component Analysis for Efficient, Differentiable Parameterization of Multipoint Geostatistics

    Pallav Sarma;Pallav Sarma;Louis J. Durlofsky;Khalid Aziz

  • Implementation of Adjoint Solution for Optimal Control of Smart Wells

    P. Sarma;K. Aziz;L.J. Durlofsky

  • A triangle based mixed finite element–finite volume technique for modeling two phase flow through porous media

    Louis J. Durlofsky

  • Accuracy of mixed and control volume finite element approximations to Darcy velocity and related quantities

    Louis J. Durlofsky

  • Drift-Flux Parameters for Three-Phase Steady-State Flow in Wellbores

    Hua Shi;Jonathan Holmes;Luis Diaz;Louis J. Durlofsky

  • Production Optimization With Adjoint Models Under Nonlinear Control-State Path Inequality Constraints

    Pallav Sarma;Wen H. Chen;Louis J. Durlofsky;Khalid Aziz

  • A nonuniform coarsening approach for the scale-up of displacement processes in heterogeneous porous media

    Louis J. Durlofsky;Richard C. Jones;William J. Milliken

  • Adaptive Local–Global Upscaling for General Flow Scenarios in Heterogeneous Formations

    Yuguang Chen;Louis J. Durlofsky;Louis J. Durlofsky

  • Joint optimization of oil well placement and controls

    Mathias Rodrigez Bellout;David Echeverria Ciaurri;Louis J. Durlofsky;Bjarne Anton Foss

  • Development and application of reduced-order modeling procedures for subsurface flow simulation

    M. A. Cardoso;L. J. Durlofsky;P. Sarma

Frequent Co-Authors

Khalid Aziz
Khalid Aziz Stanford University
Adam R. Brandt
Adam R. Brandt Stanford University
Hamdi A. Tchelepi
Hamdi A. Tchelepi Stanford University
Atilla Aydin
Atilla Aydin Stanford University
Yalchin Efendiev
Yalchin Efendiev Texas A&M University
Seong H. Lee
Seong H. Lee Chevron (Netherlands)
John F. Brady
John F. Brady California Institute of Technology
Patrick Jenny
Patrick Jenny ETH Zurich
Stanley Osher
Stanley Osher University of California, Los Angeles
Jef Caers
Jef Caers Stanford University

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