Automatic Detection and Classification of Unconformities on Seismic Data Using Machine Learning

References

1. Boggs, S.
   [1987] Principles of sedimentology and stratigraphy. Macmillan Publishing Company, New York.
   [Google Scholar]
2. Bugge, A.J., Clark, S.R., Lie, J.E. and Faleide, J.I.
   [2018] A case study on semiautomatic seismic interpretation of unconformities and faults in the southwestern Barents Sea. Interpretation, 6 (2), SD29–SD40.
   [Google Scholar]
3. Dramsch, J.S. and Lüthje, M.
   [2018] Deep-learning seismic facies on state-of-the-art CNN architectures. SEG Technical Program Expanded Abstracts 2018, 2036–2040.
   [Google Scholar]
4. Fehmers, G.C. and Höcker, C.F.
   [2003] Fast structural interpretation with structure oriented filtering. Geophysics, 68, 1286–1293.
   [Google Scholar]
5. Gramstad, O. and Nickel, M.
   [2018] Automated top salt interpretation using a deep convolutional net. 80th EAGE Conference and Exhibition 2018, Copenhagen, Denmark.
   [Google Scholar]
6. Gonzalez, R. and Woods, R.
   [2008] Digital image processing (3rd ed.). Upper Saddle River, N.J.: Pearson/Prentice Hall.
   [Google Scholar]
7. Henriksen, E., Bjørnseth, H.M., Hals, T.K, Heide, T., Kiryukhina, T., Kløvjan, O.S., Larssen, G.B., Ryseth, A.E., Rønning, K. Sollid, K. & Stoupakova, A.
   [2011] Uplift and erosion of the greater Barents Sea: impact on prospectivity and petroleum systems. In: Spencer, A.M., Embry, A.F., Gautier, D.L., Stoupakova, A.V. and Sørensen, K. (eds) Arctic Petroleum Geology. Geological Society, London, Memoirs, 35, 271–281.
   [Google Scholar]
8. Herron, D.H.
   [2015] Picking unconformities. The Leading Edge, 34 (2), 238–239.
   [Google Scholar]
9. Veillard, A., Morère, O., Grout, M. and Gruffeille, J.
   [2018] Fast 3D seismic interpretation with unsupervised deep learning: Application to a Potash network in the North Sea. 80th EAGE Conference and Exhibition 2018, Copenhagen, Denmark.
   [Google Scholar]
10. Waldeland, A. and Solberg, A.H.S.S.
    [2017] Salt classification using deep learning. 79th EAGE Conference and Exhibition 2017, Paris, France.
    [Google Scholar]
11. Wrona, T., Pan, I., Gawthorpe, R.L. and Fossen, H.
    [2018] Seismic facies analysis using machine learning. Geophysics, 83 (5), O83–O95.
    [Google Scholar]
12. Wu, X. and Hale, D.
    [2015] 3D seismic image processing for unconformities. Geophysics, 80 (2), IM35–IM44.
    [Google Scholar]