DOI: 10.5281/zenodo.11079950
title: cigChannel: A large-scale 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation

description: Submarine canyon (formerly submarine channel) subset of the cigChannel dataset (V1.0)

cigChannel (V1.0) is a dataset created by the Computational Interpretation Group (CIG) for the deep-learning-based paleochannel interpretation in 3D seismic volumes. Guangyu Wang,  Xinming Wu and Wen Zhang are the main contributors to the dataset.

cigChannel (V1.0) contains 1,600 synthetic 3D seismic volumes with labels of meandering channels, tributary channel networks and submarine canyons. Seismic impedance and sedimentary facies (only for submarine canyons) volumes correspond to the seismic volumes are also included in this dataset. Components of this dataset are listed below:




Subset name
Sample amount & size
Contents
Features


Meandering channel
400, 256x256x256




Seismic volumes (float32)

Binary-class label volumes (uint8)

Seismic impedance volume (float32)






Meandering channels.

Horizontal, inclined, folded and faulted structures.

Noise-free.






Tributary channel network

 (formerly distributary channel)

400, 256x256x256




Seismic volumes (float32)

Binary-class label volumes (uint8)

Seismic impedance volume (float32)






Tributary channel networks.

Horizontal, inclined, folded and faulted structures.

Noise-free.






Submarine canyon

(formerly submarine channel)

400, 256x256x256




Seismic volumes (float32)

Binary-class label volumes (uint8)

Seismic impedance volumes (float32)

Sedimentary facies volumes (int16)






Submarine canyons.

Horizontal, inclined, folded and faulted structures.

Noise-free.




Assorted channel
400, 256x256x256




Seismic volumes (float32)

Multi-class label volumes (int16)

Seismic impedance volumes (float32)






Meandering, tributary channel networks and submarine canyons.

Horizontal, inclined, folded and faulted structures.

Noise-free.






Further details about this dataset are available in our paper published in Earth System Science Data:

Wang, G., Wu, X., and Zhang, W.: cigChannel: a large-scale 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation, Earth Syst. Sci. Data, 17, 3447–3471, https://doi.org/10.5194/essd-17-3447-2025, 2025.



Due to the size limitation of the uploaded files, we have to publish the dataset in separated versions. This version includes the submarine canyon subset, which contains the following zip files:




Submarine_Channel_Facies_xx-xx.zip: Sedimentary facies volumes of sample No.xx to No.xx, where the value 0 represents the background (non-channel facies), 2 represents the point bar facies, 3 represents the natural levee facies and 4 represents the oxbow lake facies.

Submarine_Channel_Ip_xx-xx.zip: Seismic impedance volumes of sample No.xx to No.xx.

Submarine_Channel_Label_xx-xx.zip: Binary-class label volumes of sample No.xx to No.xx, where the value 0 represents the background (non-channel areas) and 1 represents the submarine channel.

Submarine_Channel_Seismic_xx-xx.zip: Seismic (amplitude) volumes of sample No.xx to No.xx.


Samples in this subset feature different geologic structures:



Sample No. 0 to No. 49 feature horizontal structure. 

Sample No. 50 to No. 99 feature inclined structure.

Sample No. 100 to No. 299 feature folded structure. 

Sample No. 300 to No. 399 feature folded and faulted structures (uploaded as an expansion package).


Portal to the expansion package: https://doi.org/10.5281/zenodo.15448215

Portals to the other subsets:



Assorted channel subset: https://doi.org/10.5281/zenodo.11044512

Tributary channel network subset: https://doi.org/10.5281/zenodo.11073030

Meandering channel subset: https://doi.org/10.5281/zenodo.11078794