Machine Learning Lithology Classification
Machine Learning Lithology Classification is a computational method that employs machine learning algorithms to automatically categorize subsurface rock types from geophysical or geological data, distinguishing itself from traditional lithology identification techniques through its reliance on data-driven pattern recognition and predictive modeling.
175
Publications
9.3K
Citations
628
Authors
224
Institutions
Publications per year
2017–2026
145
Parents
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1–5 of 175
628
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China University of Petroleum, Beijing
Beijing, China
13 h-index
43 publications
2.3K citations
Sinopec (China)
Beijing, China
11 h-index
13 publications
995 citations
China University of Geosciences
Wuhan, China
11 h-index
36 publications
1.7K citations
China University of Petroleum, East China
Qingdao, China
9 h-index
36 publications
1.4K citations

China University of Geosciences (Beijing)
Beijing, China
6 h-index
16 publications
661 citations

University of Tasmania
Hobart, Australia
5 h-index
13 publications
1.9K citations
University of Science and Technology of China
Hefei, China
5 h-index
15 publications
699 citations

Hohai University
Nanjing, China
5 h-index
22 publications
1.3K citations
1–8 of 224
25 publications · 1.9K citations
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7 publications · 215 citations
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GRSL · 6 publications · 299 citations
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6 publications · 274 citations
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CAGEO · 6 publications · 1.4K citations
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