This dataset was developed at the School of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology as part of joint activities at the Center for Energy and Geo-Processing (CeGP) at Georgia Tech and KFUPM. LANDMASS stands for “LArge North-Sea Dataset of Migrated Aggregated Seismic Structures”. This dataset was extracted from the North Sea F3 block under the Creative Commons license (CC BY-SA 3.0). For the purposes of this work, four classes of seismic structures: Horizons, Chaotics, Faults, and Salt Domes, were automatically extracted from the F3 block using a curvelet based distance measure for seismic images also proposed by the CeGP. Then the extracted images where manually verified and all outliers or images that had more than one structure were removed. Instructions: The LANDMASS database includes two different datasets. The first, denoted LANDMASS-1, contains 17667 small “patches” of size 99x99 pixels. it includes 9385 Horizon patches, 5140 chaotic patches, 1251 Fault patches, and 1891 Salt Dome patches. The images in this database have values in the range [-1,1]. The second dataset, denoted LANDMASS-2, contains 4000 images. Each image is of size 150x300 pixels and normalized to values in the range [0,1]. Each one of the four classes has 1000 images. Sample images from each database for each class can be found under the /samples file.

{"references": ["AlRegib G., Alaudah Y., Alfarraj M. (2015). LANDMASS Seismic Dataset. https://github.com/olivesgatech/LANDMASS.", "Alaudah, Y., & AlRegib, G. (2015, September). A curvelet-based distance measure for seismic images. In 2015 IEEE International Conference on Image Processing (ICIP) (pp. 4200-4204). IEEE.", "O. J. Aribido, G. AlRegib, and M. Deriche, \"Self-Supervised Annotation of Seismic Images Using Latent Space Factorization,\" in IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, Oct. 2020."]}