Well-Logging-Based Lithology Classification Using Machine Learning Methods for High-Quality Reservoir Identification: A Case Study of Baikouquan Formation in Mahu Area of Junggar Basin, NW China
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- Yunxin Xie & Chenyang Zhu & Yue Lu & Zhengwei Zhu, 2019. "Towards Optimization of Boosting Models for Formation Lithology Identification," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-13, August.
- Timur Merembayev & Darkhan Kurmangaliyev & Bakhbergen Bekbauov & Yerlan Amanbek, 2021. "A Comparison of Machine Learning Algorithms in Predicting Lithofacies: Case Studies from Norway and Kazakhstan," Energies, MDPI, vol. 14(7), pages 1-16, March.
- Antonio Mucherino & Petraq J. Papajorgji & Panos M. Pardalos, 2009. "Data Mining in Agriculture," Springer Optimization and Its Applications, Springer, number 978-0-387-88615-2, December.
- Matthias Schonlau & Rosie Yuyan Zou, 2020. "The random forest algorithm for statistical learning," Stata Journal, StataCorp LLC, vol. 20(1), pages 3-29, March.
- Zhixue Sun & Baosheng Jiang & Xiangling Li & Jikang Li & Kang Xiao, 2020. "A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning," Energies, MDPI, vol. 13(15), pages 1-15, July.
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Keywords
machine learning; supervised classification; lithology identification; well-logging; ensemble methods; gradient-boosted decision trees;All these keywords.
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