Photoelectric factor prediction using automated learning and uncertainty quantification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08911-4.pdf
Reference54 articles.
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3. Atlas D (1982) Well logging and interpretation techniques: The course for home study. Dresser Atlas.
4. Asoodeh M, Shadizadeh SR (2015) The prediction of photoelectric factor, formation true resistivity, and formation water saturation from petrophysical Well log data: a committee neural network approach. Energy Sour Part A: Recover Utilization Environ Eff 37:557–566. https://doi.org/10.1080/15567036.2011.594859
5. Akinnikawe O, Lyne S, Roberts J (2018) Synthetic well log generation using machine learning techniques. In: Proceedings of the 6th Unconventional Resources Technology Conference. American Association of Petroleum Geologists, Tulsa, OK, USA
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