Spatial Correlation Models

Spatial Correlation Models is a statistical framework that characterizes the degree and structure of spatial dependence among random variables in geostatistical reservoir modeling by specifying the functional form of the covariance or semivariogram as a function of distance and direction.

880

Publications

47.1K

Citations

2.6K

Authors

986

Institutions

Publications per year

2017–2026

343

Variants

Spatial Covariance ModelsSpatial Dependence Models

Authors

2.6K

  1. KG
    Katsuichiro Goda

    University of Bristol, United Kingdom

    8 publications · 628 citations

    8

    h-index

  2. JW
    Jack W. Baker

    Stanford University, United States

    5 publications · 676 citations

    5

    h-index

  3. PJ
    Peter J. Smith

    University of Canterbury, New Zealand

    4 publications · 101 citations

    4

    h-index

  4. DB
    David Blaauw

    University of Michigan, United States

    4 publications · 371 citations

    4

    h-index

  5. PG
    Peter Guttorp

    University of Washington, United States

    4 publications · 446 citations

    4

    h-index

1–5 of 2.6K

Venues

  1. Sustainability

    30 publications · 824 citations

    20

    h-index

  2. 19

    h-index

  3. Land

    16 publications · 433 citations

    15

    h-index

  4. Water Resources Research

    14 publications · 736 citations

    14

    h-index

  5. IEEE Transactions on Wireless Communications

    16 publications · 1.5K citations

    14

    h-index

1–5