Data Conditioning

Data Conditioning is a methodological process in geophysical data processing and geological block modeling that transforms raw observational data into a consistent, accurate, and interpretable format by removing noise, correcting artifacts, and standardizing measurements to enhance reliability for subsequent analysis and model construction.

87

Publications

10K

Citations

288

Authors

155

Institutions

Publications per year

2017–2026

31

Authors

288

  1. GM
    Grégoire Mariethoz

    University of Lausanne, Switzerland

    5 publications · 256 citations

    5

    h-index

  2. JC
    Jef Caers

    Stanford University, United States

    4 publications · 280 citations

    4

    h-index

  3. FR
    Forrest R. Girouard

    Ames Research Center, United States

    3 publications · 1.8K citations

    3

    h-index

  4. JM
    Jon M. Jenkins

    Ames Research Center, United States

    3 publications · 1.8K citations

    3

    h-index

  5. JD
    Joseph D. Twicken

    Ames Research Center, United States

    3 publications · 1.8K citations

    3

    h-index

1–5 of 288

Venues

  1. Water Resources Research

    10 publications · 677 citations

    10

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 240 citations

    3

    h-index

  3. 3

    h-index

  4. Mathematical Geosciences

    3 publications · 84 citations

    3

    h-index

  5. Medical Physics

    3 publications · 276 citations

    3

    h-index

1–5