Forecasting Under Uncertainty

Forecasting Under Uncertainty is a methodological framework within reservoir forecasting that quantifies and propagates uncertainty in input data, model parameters, and future conditions to produce probabilistic predictions of reservoir performance, distinguishing itself from deterministic forecasting approaches by explicitly accounting for incomplete knowledge and inherent variability in subsurface systems.

250

Publications

12.3K

Citations

717

Authors

317

Institutions

Publications per year

2017–2026

80

Authors

717

  1. DJ
    Denis José Schiozer

    Universidade Estadual de Campinas (UNICAMP), Brazil

    7 publications · 110 citations

    7

    h-index

  2. AC
    Albert C. Reynolds

    University of Tulsa, United States

    5 publications · 342 citations

    5

    h-index

  3. ET
    E. Todini

    University of Bologna, Italy

    4 publications · 153 citations

    4

    h-index

  4. MZ
    Mohammad Zafari

    Ulsan National Institute of Science and Technology, South Korea

    4 publications · 331 citations

    4

    h-index

  5. CS
    C. S. Kabir

    Chevron (Netherlands), Netherlands

    3 publications · 89 citations

    3

    h-index

1–5 of 717

Venues

  1. Water Resources Research

    17 publications · 1.5K citations

    16

    h-index

  2. SPE Reservoir Evaluation & Engineering

    SPEREE · 13 publications · 426 citations

    12

    h-index

  3. SPE Annual Technical Conference and Exhibition

    Conference · 10 publications · 169 citations

    10

    h-index

  4. SPE Journal

    6 publications · 435 citations

    6

    h-index

  5. Journal of Hydrology

    6 publications · 807 citations

    6

    h-index

1–5