참고문헌 (23)

1. Lead Edge M Bahorich 14 10 1053 1995 10.1190/1.1437077 Bahorich M, Farmer S (1995) 3-D seismic discontinuity for faults and stratigraphic features: the coherence cube[J]. Lead Edge 14(10):1053-1058 

   상세보기

2. Mach Learn S Ben-David 79 1 151 2010 10.1007/s10994-009-5152-4 Ben-David S, Blitzer J, Crammer K et al (2010) A theory of learning from different domains[J]. Mach Learn 79(1):151-175 

   상세보기

3. Comput Geosci H Di 72 192 2014 10.1016/j.cageo.2014.07.011 Di H, Gao D (2014) Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement[J]. Comput Geosci 72:192-200 

   상세보기

4. Geophysics R Feng 86 3 M41 2021 10.1190/geo2020-0424.1 Feng R, Grana D, Balling N (2021) Uncertainty quantification in fault detection using convolutional neural networks[J]. Geophysics 86(3):M41-M48 

   상세보기

5. J Mach Learn Res Y Ganin 17 1 2096 2016 Ganin Y, Ustinova E, Ajakan H et al (2016) Domain-adversarial training of neural networks[J]. J Mach Learn Res 17(1):2096-2030 

6. 10.1109/LGRS.2020.3035568 Gao J, Song Z, Gui J, et al. (2020) Gas-bearing prediction using transfer learning and CNNs: an application to a deep tight Dolomite Reservoir[J]. IEEE Geoscience and Remote Sensing Letters 

   상세보기

7. Soc Explor Geophys S Guillon 2019 2423 2019 Guillon S, Joncour F, Goutorbe P et al (2019) Reducing training dataset bias for automatic fault detection[M]//SEG technical program expanded abstracts. Soc Explor Geophys 2019:2423-2427 

8. Lead Edge L Huang 36 3 249 2017 10.1190/tle36030249.1 Huang L, Dong X, Clee TE (2017) A scalable deep learning platform for identifying geologic features from seismic attributes[J]. Lead Edge 36(3):249-256 

   상세보기

9. 10.1145/1015330.1015426 Jebara T (2004) Multi-task feature and kernel selection for SVMs[C]//Proceedings of the twenty-first international conference on Machine learning. 55 

   

10. Geophysics KJ Marfurt 63 4 1150 1998 10.1190/1.1444415 Marfurt KJ, Kirlin RL, Farmer SL et al (1998) 3-D seismic attributes using a semblance-based coherency algorithm[J]. Geophysics 63(4):1150-1165 

    상세보기

11. Geophysics KJ Marfurt 64 1 104 1999 10.1190/1.1444508 Marfurt KJ, Sudhaker V, Gersztenkorn A et al (1999) Coherency calculations in the presence of structural dip[J]. Geophysics 64(1):104-111 

    상세보기

12. IEEE Trans Knowl Data Eng SJ Pan 22 10 1345 2009 10.1109/TKDE.2009.191 Pan SJ, Yang Q (2009) A survey on transfer learning[J]. IEEE Trans Knowl Data Eng 22(10):1345-1359 

    상세보기

13. Soc Explor Geophys T Randen 2001 551 2001 Randen T, Pedersen SI, Sønneland L (2001) Automatic extraction of fault surfaces from three-dimensional seismic data[M]//SEG technical program expanded abstracts. Soc Explor Geophys 2001:551-554 

14. Van Bemmel PP, Pepper REF (2000) Seismic signal processing method and apparatus for generating a cube of variance values. U.S. Patent 6,151,555 

15. 10.1109/LGRS.2020.3034960 Wang Z, Li B, Liu N et al. (2020) Distilling knowledge from an ensemble of convolutional neural networks for seismic fault detection[J]. IEEE Geoscience and Remote Sensing Letters 

    상세보기

16. Williams C, Bonilla EV, Chai KM (2007) Multi-task Gaussian process prediction[J]. Adv Neural Inf Process Syst, 153-160 

17. Geophysics X Wu 82 2 A13 2017 10.1190/geo2016-0473.1 Wu X (2017) Directional structure-tensor-based coherence to detect seismic faults and channels[J]. Geophysics 82(2):A13-A17 

    상세보기

18. Geophysics X Wu 83 5 O67 2018 10.1190/geo2018-0115.1 Wu X, Fomel S (2018) Automatic fault interpretation with optimal surface voting[J]. Geophysics 83(5):O67-O82 

    상세보기

19. Soc Explor Geophys X Wu 2018 1946 2018 Wu X, Shi Y, Fomel S et al (2018) Convolutional neural networks for fault interpretation in seismic images[M]//SEG technical program expanded abstracts. Soc Explor Geophys 2018:1946-1950 

20. Geophysics X Wu 84 3 IM35 2019 10.1190/geo2018-0646.1 Wu X, Liang L, Shi Y et al (2019) FaultSeg3D: Using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation[J]. Geophysics 84(3):IM35-IM45 

    상세보기

21. IEEE Geosci Remote Sens Lett B Wu 17 12 2140 2020 10.1109/LGRS.2019.2963106 Wu B, Meng D, Wang L et al (2020) Seismic impedance inversion using fully convolutional residual network and transfer learning[J]. IEEE Geosci Remote Sens Lett 17(12):2140-2144 

    상세보기

22. Geophysics W Xiong 83 5 O97 2018 10.1190/geo2017-0666.1 Xiong W, Ji X, Ma Y et al (2018) Seismic fault detection with convolutional neural network[J]. Geophysics 83(5):O97-O103 

    상세보기

23. Geophysics S Yuan 85 6 IM37 2020 10.1190/geo2019-0431.1 Yuan S, Wang J, Liu T et al (2020) 6D phase-difference attributes for wide-azimuth seismic data interpretation[J]. Geophysics 85(6):IM37-IM49 

    상세보기