Application of Support Vector Machine (SVM) Method in Reservoir Lithology Classification in Sichuan Basin

Author:

Yu Jin-chen

Publisher

Springer Nature Singapore

Reference11 articles.

1. He, X., Chen, G., Wu, J., et al.: New progress and challenges of deep shale gas exploration and development in southern Sichuan Basin. Nat. Gas Ind. 42(8) (2022)

2. Dong, S., Zeng, L., Che, X., et al.: Application of artificial intelligence in fracture logging identification of tight reservoir. Earth Sci. (2022)

3. Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. Comput. Sci. 1409–1556 (2014)

4. He, Z., Zhao, X., Zhang, W., et al.: Progress and challenging directions of fine geological modeling techniques for deep and ultra-deep carbonate reservoirs. Oil Gas Geol. 44(1) (2023)

5. Zou, C., Yang, Z., Zhu, R., et al.: Progress in China’s unconventional oil & gas exploration and development and theoretical technologies. Acta Geol. Sinica (Engl. Edn.) 89(03), 938–971 (2015)

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