Published March 4, 2024 | Version v1
Dataset Open

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

Creators

  • 1. School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China;
  • 2. Institute of Advanced Technology, University of Science and Technology of China, Hefei, China
  • 3. Institute of Sedimentary Geology, Chengdu University of Technology, Chengdu, China
  • 4. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu, China

Description

cigFacies is a dataset create by the Computational Interpretation Group (CIG) for the AI-based automatic seismic facies classification in 3-D seismic data, Hui Gao, Xinming Wu, Xiaoming Sun and Mingcai Hou are the main contributors to the dataset.

This is the benchmark skeletonization datasets of seismic facies, guided by the knowledge graph of seismic facies and constructed from three different stategies (field seismic data, synthetic data and GAN-based generation).

Below are some brief desription of the datasets:

1) The "The benchmark skeletonization datasets" file consists of 5 classes of seismic facies.

2) The "parallel_class", "clinoform_class", "fill_class", "hummocky_class" and "chaotic_class" consist of 2000, 1500, 1500, 1500, 1500 stratigraphic skeletonization data constructed from field seismic data, synthetic data and GAN-based generation, respectively.

The source codes for constructing the benchmark dataset of seismic facies and deep learning for seismic facies classification have been uploaded to Github and are freely available at cigFaciesNet.

 

 

Files

The_benchmark_skeletonization_datasets.zip

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