Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration
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Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration. 2024. S. 469-477.
Publikationen: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Konferenzband
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TY - GEN
T1 - Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration
AU - Jason, Cheah
AU - Umer Ilyas, Suhaib
AU - Ridha, Syahrir
AU - Sehar, Umara
AU - Alsaady, Mustafa
AU - Krishna, Shwetank
PY - 2024
Y1 - 2024
U2 - 10.1007/978-981-97-8345-8_57
DO - 10.1007/978-981-97-8345-8_57
M3 - Conference contribution
SP - 469
EP - 477
BT - Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration
ER -