Directional structure-tensor-based coherence to detect seismic faults and channels

By Xinming Wu. 2017

157 citations recorded by the source corpus.

Subfields: Geophysics, Mechanical Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/27677bd4ae1bb611b6b249aac14d4c19847919fa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geophysics

1. Yunzhi Shi
2. Sergey Fomel
3. Luming Liang
4. Xinming Wu
5. Yangkang Chen
6. Xiaohong Chen
7. Jianwei Ma
8. Yang Liu

In Mechanical Engineering

1. Yunzhi Shi
2. Sergey Fomel
3. Luming Liang
4. Jianwei Ma
5. Siwei Yu
6. Xiaohong Chen
7. George A. McMechan
8. Hu Jin

In Ocean Engineering

1. Yunzhi Shi
2. Sergey Fomel
3. Luming Liang
4. Xinming Wu
5. Yangkang Chen
6. Xiaohong Chen
7. Siwei Yu
8. Jianwei Ma

Citations in the corpus

• FaultSeg3D: Using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation (2019, methodology): “…the methods of (a) C3 (Gersztenkorn and Marfurt, 1999), (b) C2 (Marfurt et al., 1999), (c) planarity (Hale, 2009), (d) structure-oriented planarity (Wu, 2017), (e) structure-oriented semblance (Hale, 2009), (f) the fault likelihood (Hale, 2013; Wu and Hale, 2016), and (g) optimal surface voting…”