Concepedia

Machine Learning For Image Logs

Machine Learning for Image Logs is a computational methodology that applies machine learning techniques to the analysis and interpretation of image logs in geoscience, distinguished by its focus on automating feature extraction, pattern recognition, and stratigraphic classification within subsurface imaging data.

11

Publications

308

Citations

39

Authors

18

Institutions

Publications per year

2017–2026

8

Parents

Publications

11

Rock type classification based on petrophysical, geochemical, and core imaging data using machine and deep learning techniques

Negin Houshmand, Sebastian D. Goodfellow, Kamran Esmaeili et al. · Applied Computing and Geosciences · 2022 · 61 citations · Full text

, , +15

An integrated sedimentological, rock typing, image logs, and artificial neural networks analysis for reservoir quality assessment of the heterogeneous fluvial-deltaic Messinian Abu Madi reservoirs, Salma field, onshore East Nile Delta, Egypt

Nader H. El-Gendy, Ahmed E. Radwan, Mohamed A. Waziry et al. · Marine and Petroleum Geology · 2022 · 42 citations · Full text

, , +17

Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation

Reinaldo Mozart Silva, Laís Baroni, Rodrigo Soares Ferreira et al. · arXiv (Cornell University) · 2019 · 39 citations · Full text

, , +16

Automated Labeling of Log Features in CT Imagery of Multiple Hardwood Species

Daniel L. Schmoldt, Jing He, A. Lynn Abbott · Wood and Fiber Science (Society of Wood Science and Technology) · 2000 · 38 citations · Full text

, , +17

Automatic fracture detection from the images of electrical image logs using Mask R-CNN

Lin Du, Xuemin Lu, Huazhou Li · Fuel · 2023 · 38 citations

, , +16

1–5 of 11

Authors

39

  1. DL
    Daniel L. Schmoldt

    Virginia Tech, United States

    2 publications · 49 citations

    2

    h-index

  2. LB
    Laís Baroni

    Federal Center for Technological Education of Minas Gerais, Brazil

    2 publications · 54 citations

    2

    h-index

  3. DC
    Daniel Civitarese

    IBM Research - Brazil, Brazil

    2 publications · 54 citations

    2

    h-index

  4. JH
    Jing He

    US Forest Service, United States

    2 publications · 49 citations

    2

    h-index

  5. DS
    Daniela Szwarcman

    IBM Research - Brazil, Brazil

    2 publications · 54 citations

    2

    h-index

1–5 of 39

Institutions

18

  1. Norwegian Institute of Bioeconomy Research

    Oslo, Norway

    2 h-index

    5 publications

    87 citations

  2. Jagiellonian University

    Krakow, Poland

    1 h-index

    1 publications

    42 citations

  3. FPInnovations

    Pointe-Claire, Canada

    1 h-index

    1 publications

    15 citations

  4. Virginia Tech

    Blacksburg, United States

    1 h-index

    1 publications

    11 citations

  5. University of New Brunswick

    Fredericton, Canada

    1 h-index

    3 publications

    45 citations

  6. K Lab (United States)

    Hillsborough, United States

    1 h-index

    1 publications

    11 citations

  7. US Forest Service

    Washington, United States

    1 h-index

    1 publications

    11 citations

  8. University of Helsinki

    Helsinki, Finland

    1 h-index

    2 publications

    30 citations

1–8 of 18

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 54 citations

    2

    h-index

  2. Holzforschung

    1 publications · 15 citations

    1

    h-index

  3. Applied Computing and Geosciences

    1 publications · 61 citations

    1

    h-index

  4. Wood and Fiber Science (Society of Wood Science and Technology)

    Repository · 1 publications · 38 citations

    1

    h-index

  5. Marine and Petroleum Geology

    1 publications · 42 citations

    1

    h-index

1–5