Study on Geological Feature Extraction from FMI Logging Data by Using Deep Learning Neural Network

References

1. YuanZeng Ren
   . Artificial neural network and its application [M]. Beijing: Tsinghua University Press, 1999.
   [Google Scholar]
2. Glorot, Bordes, Bengio
   . Deep sparse rectifier neural networks [J]. 14th International Conference on Artificial Intelligence and Statistics. 2011: 315–323.
   [Google Scholar]
3. Geoffrey E.Hinton, SimonOsindero, Yee-WhyeTeh
   . A fast learning algorithm for deep belief nets[J]. Neral Computation, 2006, 18: 1527–1554.
   [Google Scholar]
4. YannLeCun, YoshuaBengio, GeoffreyHinton
   . Deep learning [J]. NATURE, 2015, 28: 436–444.
   [Google Scholar]
5. Lidaolun
   . Neural network implicit method and its application in petroleum data [D]. Anhui: China University of science and technology, 2007.
   [Google Scholar]
6. YangBin, KuangLichun, sunZhongchun, Shizejin
   . Neural network and its application in oil logging [M]. Beijing: Petroleum Industry Press, 2005:94–191.
   [Google Scholar]
7. ZhouYuncai, LiuRuilin
   . Application of image recognition method in FMI image processing [J]. Journal of petroleum and natural gas, 2003, 25 (S1): 50–51.
   [Google Scholar]
8. LiMaobing
   . Study on automatic recognition and quantitative evaluation of electrical imaging logging [D]. Shandong: China University of Petroleum (East China), 2010.
   [Google Scholar]
9. LaiFuqiang
   . Study on the processing and interpretation methods of electrical imaging logging [D]. Shandong: China University of Petroleum (East China), 2011.
   [Google Scholar]