World's Best Scientists 2026 revealed!
Clayton V. Deutsch

Clayton V. Deutsch

D-Index & Metrics

Engineering and Technology

D-Index
50
Citations
19608
World Ranking
3988
National Ranking
161

Clayton V. Deutsch 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 Clayton V. Deutsch sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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: 267 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Clayton V. Deutsch 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 Clayton V. Deutsch sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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: 50 D-Index — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering

Overview

Clayton V. Deutsch is affiliated with the University of Alberta in Canada and has contributed extensively to the fields of environmental science, engineering, and computer science. Their research spans several subfields including environmental engineering, artificial intelligence, mechanical engineering, ocean engineering, and control and systems engineering.

The scientist's work primarily addresses topics such as soil geostatistics and mapping, geochemistry and geologic mapping, mineral processing and grinding, mining techniques and economics, reservoir engineering and simulation methods, geological modeling and analysis, and atmospheric and environmental gas dynamics.

Recent publications by Clayton V. Deutsch include:

  • Combination of Machine Learning and Kriging for Spatial Estimation of Geological Attributes (2022) published in Natural Resources Research
  • A Hybrid Estimation Technique Using Elliptical Radial Basis Neural Networks and Cokriging (2021) published in Mathematical Geosciences
  • Assessment of variogram reproduction in the simulation of decorrelated factors (2021) published in Stochastic Environmental Research and Risk Assessment
  • Mineral Resources Evaluation with Mining Selectivity and Information Effect (2020) published in Mining Metallurgy & Exploration
  • Merging machine learning and geostatistical approaches for spatial modeling of geoenergy resources (2023) published in International Journal of Coal Geology

Clayton collaborates frequently with several researchers. Notable co-authors include:

  • Oktay Erten
  • Gamze Erdogan Erten
  • Jeff Boisvert
  • João Felipe Coimbra Leite Costa
  • Mahmut Yavuz

The scientist's research has been published repeatedly in key venues such as:

  • Mining Metallurgy & Exploration
  • Natural Resources Research
  • Computers & Geosciences
  • CIM Journal
  • Mathematical Geosciences

Clayton has been recognized by the Canadian Academy of Engineering, reflecting their involvement in engineering disciplines.

Best Publications

  • GSLIB: Geostatistical Software Library and User's Guide

    Eric R. Ziegel;C. Deutsch;A. Journel

  • GSLIB: Geostatistical Software Library and User's Guide

    Clayton Vernon Deutsch;André Georges Journel

  • Geostatistical Reservoir Modeling

    Clayton V. Deutsch

  • Geostatistical Software Library and User's Guide

    Eric R. Ziegel;Clayton V. Deutsch;Andre G. Journel

  • Mineral Resource Estimation

    Clayton V. Deutsch;Mario E. Rossi

  • Teacher's Aide Variogram Interpretation and Modeling 1

    Emmanuel Gringarten;Clayton V. Deutsch

  • Hierarchical object-based stochastic modeling of fluvial reservoirs

    Clayton V. Deutsch;Libing Wang

  • FLUVSIM: a program for object-based stochastic modeling of fluvial depositional systems

    C. V. Deutsch;T. T. Tran

  • ANNEALING TECHNIQUES APPLIED TO RESERVOIR MODELING AND THE INTEGRATION OF GEOLOGICAL AND ENGINEERING (WELL TEST) DATA

    Clayton Vernon Deutsch

  • Calculating effective absolute permeability in sandstone/shale sequences

    Clayton Deutsch

  • Statistical approach to inverse distance interpolation

    Olena Babak;Clayton V. Deutsch

  • A sequential indicator simulation program for categorical variables with point and block data: BlockSIS

    Clayton V. Deutsch

  • Practical considerations in the application of simulated annealing to stochastic simulation

    Clayton V. Deutsch;Perry W. Cockerham

  • Power Averaging for Block Effective Permeability

    A.G. Journel;C. Deutsch;A.J. Desbarats

  • Latin hypercube sampling with multidimensional uniformity

    Jared L. Deutsch;Clayton V. Deutsch

  • Minimum acceptance criteria for geostatistical realizations

    Oy Leuangthong;Jason A. McLennan;Clayton V. Deutsch

  • Stochastic surface-based modeling of turbidite lobes

    Michael J. Pyrcz;Octavian Catuneanu;Clayton V. Deutsch

  • High-Resolution Reservoir Models Integrating Multiple-Well Production Data

    Xian-Huan Wen;C.V. Deutsch;A.S. Cullick

  • Stepwise Conditional Transformation for Simulation of Multiple Variables

    Oy Leuangthong;Clayton V. Deutsch

  • Correcting for negative weights in ordinary kriging

    Clayton V. Deutsch

  • The Quality Map: A Tool for Reservoir Uncertainty Quantification and Decision Making

    Paulo S. da Cruz;Roland N. Horne;Clayton V. Deutsch

  • DECLUS: a FORTRAN 77 program for determining optimum spatial declustering weights

    C. Deutsch

Frequent Co-Authors

Carl A. Mendoza
Carl A. Mendoza University of Alberta
Roland N. Horne
Roland N. Horne Stanford University
Tapan Mukerji
Tapan Mukerji Stanford University
Gary Mavko
Gary Mavko Stanford University
Khalid Aziz
Khalid Aziz Stanford University
René Therrien
René Therrien Université Laval
Kathy Ehrig
Kathy Ehrig BHP (Australia)
Octavian Catuneanu
Octavian Catuneanu University of Alberta
Biondo Biondi
Biondo Biondi Stanford University
Dean S. Oliver
Dean S. Oliver NORCE Research

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