Articles | Volume 17, issue 2
https://doi.org/10.5194/essd-17-595-2025
https://doi.org/10.5194/essd-17-595-2025
Data description paper
 | 
10 Feb 2025
Data description paper |  | 10 Feb 2025

cigFacies: a massive-scale benchmark dataset of seismic facies and its application

Hui Gao, Xinming Wu, Xiaoming Sun, Mingcai Hou, Hang Gao, Guangyu Wang, and Hanlin Sheng

Viewed

Total article views: 869 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
562 175 132 869 20 22
  • HTML: 562
  • PDF: 175
  • XML: 132
  • Total: 869
  • BibTeX: 20
  • EndNote: 22
Views and downloads (calculated since 07 Oct 2024)
Cumulative views and downloads (calculated since 07 Oct 2024)

Viewed (geographical distribution)

Total article views: 869 (including HTML, PDF, and XML) Thereof 869 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Mar 2025
Download
Short summary
We propose three strategies for field seismic data curation, knowledge-guided synthesization, and generative adversarial network (GAN)-based generation to construct a massive-scale, feature-rich, and high-realism benchmark dataset of seismic facies and evaluate its effectiveness in training a deep-learning model for automatic seismic facies classification.
Share
Altmetrics
Final-revised paper
Preprint