Automatic lithological mapping from potential field data using machine learning: a case study from Mundiyawas-Khera Cu deposit, Rajasthan, India
Author:
Funder
Science & Engineering Research Board
Department of Science & Technology
Publisher
Springer Science and Business Media LLC
Subject
Geophysics
Link
https://link.springer.com/content/pdf/10.1007/s11600-023-01151-z.pdf
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3. Anifowose F, Labadin J, Abdulraheem A (2015) Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines. Appl Soft Comput 26:483–496
4. Azam MS, Khan MS, Raza M (2015) Petrogenetic study of Mesoproterozoic volcanic rocks of North Delhi fold belt, NW Indian shield: implications for mantle conditions during Proterozoic. Chin j Geochem 34:93–114
5. Bhattacharya S, Carr TR, Pal M (2016) Comparison of supervised and unsupervised approaches for mudstone lithofacies classification: case studies from the Bakken and Mahantango-Marcellus Shale, USA. J Natl Gas Sci Eng 33:1119–1133
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