Enrich the interpretation of seismic image segmentation by estimating epistemic uncertainty

Author(s):  
Tao Zhao ◽  
Xiaoli Chen
2001 ◽  
Vol 50 (4) ◽  
pp. 1014-1018 ◽  
Author(s):  
L. Valet ◽  
G. Mauris ◽  
P. Bolon ◽  
N. Keskes

2014 ◽  
Vol 2 (2) ◽  
pp. T79-T88 ◽  
Author(s):  
Adam D. Halpert ◽  
Robert G. Clapp ◽  
Biondo Biondi

Although it is a crucial component of seismic velocity model building, salt delineation is often a major bottleneck in the interpretation workflow. Automatic methods like image segmentation can help to alleviate this bottleneck, but issues with accuracy and efficiency can hinder their effectiveness. However, a new graph-based segmentation algorithm can, after modifications to account for the unique nature of seismic data, quickly and accurately delineate salt bodies on 3D seismic images. In areas where salt boundaries are poorly imaged, limited manual interpretations can be used to guide the automatic segmentation, allowing for interpreter insight to be combined with modern computational capabilities. A successful 3D field data example demonstrates that this method could become an important tool for interactive interpretation tasks.


2010 ◽  
Author(s):  
Adam D. Halpert ◽  
Robert G. Clapp ◽  
Biondo Biondi

2009 ◽  
Author(s):  
Adam D. Halpert ◽  
Robert G. Clapp ◽  
Biondo Biondi

Geophysics ◽  
2020 ◽  
Vol 86 (1) ◽  
pp. A1-A5
Author(s):  
Yunzhi Shi ◽  
Xinming Wu ◽  
Sergey Fomel

We have designed a deep-learning workflow to interactively track seismic geobodies. The algorithm is based on a flood-filling network, which performs iterative segmentation and moving the field of view (FoV). The proposed network takes the previous mask output, together with the seismic image in a new FoV, as a combined input to predict the mask at this FoV. The movement of the FoV is guided by the flood-filling algorithm to visit and segment the full extent of a geobody. Unlike conventional seismic image segmentation methods, the proposed workflow can not only detect geobodies, but it can also track individual geobody instances.


2022 ◽  
Vol 209 ◽  
pp. 109971
Author(s):  
Esmail Hosseini-Fard ◽  
Amin Roshandel-Kahoo ◽  
Mehrdad Soleimani-Monfared ◽  
Keyvan Khayer ◽  
Ali Reza Ahmadi-Fard

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