Published February 28, 2020
| Version v1
Dataset
Open
Seismic simulation of paleokarst systems and deep learning for characterizing paleokarst features in 3D seismic images
Authors/Creators
- 1. University of Science and Technology of China
- 2. Geophysical Insights
- 3. Bureau of Economic Geology
Description
To train our deep convolutional neural network for paleokarst delineation in 3D seismic images, we automatically generate 120 pairs of synthetic training datasets including 3D seismic images and the corresponding label images with the ground truth of the paleokarst systems simulated in the seismic images.
1) The "seismic.zip" contains 120 3D seismic images, each image is with the dimension of 256X256X256;
2) The "karst.zip" contains 120 3D label images of the karsts. Each label image is with the same dimension of 256X256X256. The values in a label image are set with ones in the karst areas while zeros elsewhere, which is why the compressed label images in the karst.zip is much smaller than the seismic images compressed in the seismic.zip