World's Best Scientists 2026 revealed!
Albert C. Reynolds

Albert C. Reynolds

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
16007
World Ranking
1634
National Ranking
534

Albert C. Reynolds 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 Albert C. Reynolds 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: 238 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Albert C. Reynolds 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 Albert C. Reynolds 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: 64 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Overview

Albert C. Reynolds is affiliated with the University of Tulsa in the United States. Their primary area of research lies within the field of engineering, with a focus on specialized subfields including ocean engineering and mechanical engineering. Within these domains, their work predominantly addresses topics related to reservoir engineering and simulation methods, hydraulic fracturing and reservoir analysis, enhanced oil recovery techniques, drilling and well engineering, obstructive sleep apnea research, neuroscience of respiration and sleep, and respiratory support and mechanisms.

Their recent scholarly output demonstrates a strong concentration in optimization and robust production methods within complex engineering systems. Notable papers include:

  • A Sequential-Quadratic-Programming-Filter Algorithm with a Modified Stochastic Gradient for Robust Life-Cycle Optimization Problems with Nonlinear State Constraints, 2020, SPE Journal
  • Gradient-Enhanced Support Vector Regression for Robust Life-Cycle Production Optimization with Nonlinear-State Constraints, 2020, SPE Journal
  • Robust Multiobjective Nonlinear Constrained Optimization with Ensemble Stochastic Gradient Sequential Quadratic Programming-Filter Algorithm, 2021, SPE Journal
  • Joint Optimization of Well Locations, Types, Drilling Order, and Controls Given a Set of Potential Drilling Paths, 2020, SPE Journal
  • Optimizing vertical and deviated wells based on advanced initialization using new productivity potential map, 2020, Journal of Petroleum Science and Engineering

Albert C. Reynolds frequently publishes in venues including:

  • SLEEP Advances
  • SPE Journal
  • Journal of Petroleum Science and Engineering
  • SPE Improved Oil Recovery Conference
  • American Journal of Ophthalmology

Collaboration is an important aspect of their research activity. Frequent co-authors include Bastien Lechat, Robert J. Adams, Nicole Lovato, John M. Manners, and Danny J. Eckert, indicating a pattern of sustained collaborative projects across their work.

The breadth of topics addressed in their publications spans both traditional reservoir and well engineering challenges and interdisciplinary investigations involving physiology and respiratory medicine. This highlights the integration of engineering approaches with biological and medical applications such as obstructive sleep apnea research and neuroscience of respiration.

Best Publications

  • Inverse Theory for Petroleum Reservoir Characterization and History Matching

    Dean S. Oliver;Albert C. Reynolds;Ning Liu

  • Ensemble smoother with multiple data assimilation

    Alexandre A. Emerick;Albert C. Reynolds

  • THE ENSEMBLE KALMAN FILTER IN RESERVOIR ENGINEERING-A REVIEW

    Sigurd I. Aanonsen;Geir Nævdal;Dean S. Oliver;Albert C. Reynolds

  • History Matching of Three-Phase Flow Production Data

    Ruijian Li;A.C. Reynolds;D.S. Oliver

  • Boundary conditions for the numerical solution of wave propagation problems

    Albert C. Reynolds

  • Results of the Brugge Benchmark Study for Flooding Optimization and History Matching

    E.. Peters;R.J.. J. Arts;G.K.. K. Brouwer;C.R.. R. Geel

  • An Improved Implementation of the LBFGS Algorithm for Automatic History Matching

    Guohua Gao;Albert C. Reynolds

  • Quantifying Uncertainty for the PUNQ-S3 Problem in a Bayesian Setting With RML and EnKF

    Guohua Gao;Mohammad Zafari;Albert C. Reynolds

  • Assessing the Uncertainty in Reservoir Description and Performance Predictions With the Ensemble Kalman Filter

    Mohammad Zafari;Albert Coburn Reynolds

  • Markov Chain Monte Carlo Methods for Conditioning a Permeability Field to Pressure Data

    Dean S. Oliver;Luciane B. Cunha;Luciane B. Cunha;Albert C. Reynolds

  • Production Optimization in Closed-Loop Reservoir Management

    Chunhong Wang;Gaoming Li;Albert C. Reynolds

  • Conditioning Permeability Fields to Pressure Data

    D. S. Oliver;N. He;A. C. Reynolds

  • History matching time-lapse seismic data using the ensemble Kalman filter with multiple data assimilations

    Alexandre A. Emerick;Albert C. Reynolds

  • A stochastic simplex approximate gradient (StoSAG) for optimization under uncertainty

    Rahul Rahul-Mark Fonseca;Bailian Chen;Jan Dirk Jansen;Albert Reynolds

  • Investigation of the sampling performance of ensemble-based methods with a simple reservoir model

    Alexandre A. Emerick;Albert C. Reynolds

  • Conditioning Geostatistical Models to Two-Phase Production Data

    Zhan Wu;A.C. Reynolds;D.S. Oliver

  • New pressure transient analysis methods for naturally fractured reservoirs

    K. Serra;A.C. Reynolds;R. Raghavan

  • Reparameterization Techniques for Generating Reservoir Descriptions Conditioned to Variograms and Well-Test Pressure Data

    A.C. Reynolds;Nanqun He;Lifu Chu;D.S. Oliver

  • Iterative Ensemble Kalman Filters for Data Assimilation

    Gaoming Li;Albert C. Reynolds

  • Robust Constrained Optimization of Short- and Long-Term Net Present Value for Closed-Loop Reservoir Management

    Chaohui Chen;Gaoming Li;Albert Reynolds

Frequent Co-Authors

Dean S. Oliver
Dean S. Oliver NORCE Research
Rajagopal Raghavan
Rajagopal Raghavan Phillips 66 (United States)
Jan Dirk Jansen
Jan Dirk Jansen Delft University of Technology
Jun Yao
Jun Yao China University of Petroleum, Beijing

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