cigChannel: A large-scale 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation

Tributary channel network (formerly distributary 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 channels, 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 tributary channel network subset, which contains the following zip files: Distributary_Channel_Ip_xx-xx.zip: Seismic impedance volumes of sample No.xx to No.xx. Distributary_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 distributary channel. Distributary_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.15442162 Portals to the other subsets: Assorted channel subset: https://doi.org/10.5281/zenodo.11044512 Meandering channel subset: https://doi.org/10.5281/zenodo.11078794 Submarine canyon subset: https://doi.org/10.5281/zenodo.11079950