Open Access
Issue
E3S Web Conf.
Volume 358, 2022
5th International Conference on Green Energy and Sustainable Development (GESD 2022)
Article Number 01027
Number of page(s) 5
Section Invited Contributions
DOI https://doi.org/10.1051/e3sconf/202235801027
Published online 27 October 2022
  1. Liu Yanhong, Luo Xingwang, Zhang Wu, Li Chen, Zhang Ruixue, Luo Qiang, Wang Bin, Zhang Yanmei. Study on logging identification method and influencing factors of waterlogged layer in tight sandstone reservoir. Special hydrocarbon reservoirs. [Google Scholar]
  2. Ma Tao. Analysis of flume delta depositional system in continental large depression basin under arid climate conditions: A case study of Quan-4 Member of Fuxin Uplift belt in southern Songliao Basin [D]. Beijing: China University of Geosciences (Beijing), 2006. [Google Scholar]
  3. Andrew D. Miall. Reconstructing the architecture and sequence stratigraphy of the preserved fluvial record as a tool Reservoir development: A reality check[J]. AAPG Bulletin, 2006, 90(7): 989–1002. [CrossRef] [Google Scholar]
  4. Ju Wu, Shen Huilin, Yang Hong, et al. Research on logging evaluation method of water-flooded layer in conglomerate reservoir in junggar basin [J]. Progress in geophysics, 2009, 24(3):974–980 [Google Scholar]
  5. Tian Zhongyuan, Mu Longxin, Sun Deming, et al. Study on logging characteristics and mechanism of conglomerate water-flooded layer [J]. Acta Petrolei Sinica, 2002, (6) : 50–55+3 [Google Scholar]
  6. Chen Ganghua, Liang Shasha, Wang Jun, et al. Application of machine learning AdaBoost.M2 algorithm in conglomerate fluid identification. Oil geophysical prospecting, 2019, 54 (6) :1357–1362. [Google Scholar]
  7. Chen Xin, Chen Kegui, Wang Zhaofeng, Dai Xiongjun, Fan Xiangyu. Logging response characteristics and waterlogging analysis of flooded zone in Aryskum oilfield. Progress in geophysics. [Google Scholar]
  8. Mingren Yang, Huilin Shen, Sa Qu, Qipeng Sun, Limin Zhang, Shuming Xiao. Application of AdaBoost algorithm in water-flooded layer identification of tight sandstone. China offshore oil and gas (in Chinese), 2021, 33(4):1673–1506 [Google Scholar]
  9. Li Jianping, Yang Du, Fan Yougui. Quantum AD hoc network model and its application in oilfield waterlogged layer identification [J]. Microcomputer applications, 2020, 36 (12): 9–11+15. [Google Scholar]
  10. Wang B. T., Gao Y. F., Fan Y. X., et al. Study on logging evaluation method of remaining oil in Lamadian Oilfield [J]. Journal of oil and gas technology, 2014, 36 (7): 84–88+6. [Google Scholar]
  11. He Zhongsheng, Cui Zhigang, Chen Guanghui, et al. Evaluation of residual oil and water flooding degree using hydrocarbon ratio logging technology [J]. Journal of southwest petroleum university (science & technology edition), 2016, 38 (5) : 41–49. [Google Scholar]
  12. The white deer. Study on main controlling factors of Fuyang reservoir formation in Xingbei Oilfield, Daqing Placanticline, Northeast Petroleum University. 2015. [Google Scholar]
  13. Zhang Haiying. Development strategy of Xingbei Oilfield in ultra-high water cut stage. Scientific management. 2019.3:256. [Google Scholar]
  14. Sun Peipei, Zhang Ning, Zhao Linjing, Peng Yuanyuan, Liu Xijian, Liu Xiaohui, Zhai Yassen, Feng Meiqing. Effects of subinhibitory concentration of cinnamon essential oil on lipid homeostasis in Candida albicans [J]. Chinese Journal of Analytical Chemistry, 2002, 50(01):92–107. [Google Scholar]
  15. Cao Taoyun. Research on variable importance based on random forest [J]. Statistics and Decision, 2002, 38(04):60–63. [Google Scholar]
  16. Li Sihan, Wang Changquan, Wu Hua, Liu Tao, Zhao Xu. Normalization method of capillary pressure curve based on effective reservoir thickness [J]. China science and technology papers, 2020, 15(05):593–598. [Google Scholar]
  17. Zhang Junhua, Ren Xiongfeng, Zhao Jie, Tan Mingyou, Yu Zhengjun. Reservoir prediction method and application based on cross-validation support vector machine [J]. Science technology and engineering, 2020, 20(13):5052–5057. [Google Scholar]
  18. Yan Xingyu, Gu Hanming, Xiao Yifei, Ren Hao, Ni Jun. Application of XGBoost algorithm in logging interpretation of tight sandstone gas reservoir [J]. Oil geophysical prospecting, 2019, 54(02):447–455+241. [Google Scholar]
  19. Gu Yufeng, Zhang Daoyong, Bao Zhidong, Feng Zhigang, Li Jinggong. Prediction of permeability by gradient lifting Decision Tree (GBDT) : A case study of tight sandstone reservoir in the west Chang 4+5 member of Jiyuan Oilfield [J]. Progress in geophysics (in Chinese), 2021, 36(02):585–594. [Google Scholar]
  20. Wang Yan, Wang Ruogu, Wei Keying, Lu Haijiao, Xiong Xiaowei, Zhang Tianjie. Classification of tight reservoir based on random forest: A case study of the 8th Member of Eastern Hehe Formation in Yan 'an Gas Field [J]. Journal of xi 'an shiyou university (natural science edition), 2021, 36(06):1–8. [Google Scholar]
  21. Yang C., Zhao H., Bruzzone L., Benediktsson J.A., Liang Y., Liu B., Lunar Impact Crater Identification and Age Estimation with Chang 'e Data by Deep and Transfer learning. Nat Commun 2020; 11 (1). [PubMed] [Google Scholar]

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