cigCK: A data of 3D synthetic seismic volumes with labeled channels and karsts for deep-learning-based simultaneous channel and karst interpretation

cigCK is a dataset created by the Computational Interpretation Group (CIG) for the deep-learning-based simultaneous channel and karst interpretation in 3D seismic images, Jiarun Yang, Guangyu Wang, and Xinming Wu are the main contributors to the dataset.

This dataset contains 200 pairs of synthetic 3D seismic images and the corresponding label images with the ground truth of channels and karsts simulated in the seismic images. More detail of building this dataset is discussed in the paper submitted to the journal of JGR Solid Earth:

Yang, J., X. Wu* and G. Wang, 2024, Deep learning for simultaneous karst and channel detection. JGR, Solid Earth, submitted.

Below are some brief description of the dataset:

1) The "gx.zip" file contains 200 3D seismic volumes, each with dimensions of 500x500x250.

2) The "lx.zip" file contains 200 corresponding label volumes, also with dimensions of 500x500x250. In a label image, areas representing karsts are assigned a value of 1, channels are denoted with a 2, and all other regions are marked as 0, which is why the compressed label images in the lx.zip is much smaller than the seismic images compressed in the gx.zip