[1] Wang, X., & Yuan, X. (2024). Improved pore structure prediction based on a stacking machine learning model for low-permeability reservoir in Tazhong area, Tarim Basin. Geoenergy Science and Engineering, 241, 213135.
[2] Wang, X., Wang, D., Li, X., & Han, C. (2023).Study on pore structure characterization of strong diagenesis sandstones and the logging response characteristics in Tazhong area, Tarim Basin. Journal of Applied Geophysics, 105117.
[3]Wang, X., Yang, S., Zhao, Y., & Wang, Y. (2018).Improved permeability prediction based on the feature engineering of petrophysics and fuzzy logic analysis in low porosity-permeability reservoir, Journal of Petroleum Exploration and Production technology.
[4] Wang, X., Yang, S., Zhao, Y., & Wang, Y. (2018). Improved Pore Structure Prediction based on MICP with a Data Mining and Machine Learning System Approach in Mesozoic Strata of Gaoqing Field, Jiyang Depression. Journal of Petroleum Science & Engineering.171C (2018) pp. 362-393
[5] Wang, X., Yang, S., Zhao, Y., & Wang, Y. (2018). Lithology identification using an optimized knn clustering method based on entropy-weighed cosine distance in mesozoic strata of gaoqing field, jiyang depression. Journal of Petroleum Science & Engineering. Volume 166, July 2018, Pages 157-174.
[6] Tian, F., Wang, X., Yuan, X., & Wang, D. (2024). Improved pore structure characterization and classification of strong diagenesis sandstones by data-mining analytics in Tazhong area, Tarim Basin. PloS one, 19(8), e0309092.