Özet
This paper present a hybrid Machine Learning and seismic structural attributes approach to extract detailed major and minor discontinuities from seismic data from a complex fault system that present a challenge using conventional interpretation techniques. Fault interpretation is image segmentation problem and we thus adopted U-net encoder-decoder architecture as a first step in this hybrid workflow, it is well suited for seismic discontinuities. Image segmentation can not only figure out whether a particular feature such as faults exist but can also create a mask showing where in the volume those features exist.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | 2nd EAGE Subsurface Intelligence Workshop |
Yayınlayan | European Association of Geoscientists and Engineers, EAGE |
ISBN (Elektronik) | 9789462824409 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2022 |
Harici olarak yayınlandı | Evet |
Etkinlik | 2nd EAGE Subsurface Intelligence Workshop 2022 - Manama, Bahrain Süre: 28 Eki 2022 → 31 Eki 2022 |
Yayın serisi
Adı | 2nd EAGE Subsurface Intelligence Workshop |
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???event.eventtypes.event.conference??? | 2nd EAGE Subsurface Intelligence Workshop 2022 |
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Ülke/Bölge | Bahrain |
Şehir | Manama |
Periyot | 28/10/22 → 31/10/22 |
Bibliyografik not
Publisher Copyright:© 2nd EAGE Subsurface Intelligence Workshop 2022.