DIG-Kaust/VolveSynthetic: A Volve-alike synthetic dataset for testing of seismic processing and imaging algorithms
Type
SoftwareKAUST Department
School of Earth Science and Engineering, Physical Science and Engineering Division, and KAUST Extreme Computing Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.Physical Science and Engineering (PSE) Division
Extreme Computing Research Center
Earth Science and Engineering Program
Date
2021-10-31Permanent link to this record
http://hdl.handle.net/10754/678675
Metadata
Show full item recordAbstract
A Volve-alike synthetic dataset for testing of seismic processing and imaging algorithmsPublisher
GithubAdditional Links
https://github.com/DIG-Kaust/VolveSyntheticRelations
Is Supplement To:- [Article]
Ravasi, M., Selvan, T., & Luiken, N. (2022). Stochastic Multi-Dimensional Deconvolution. IEEE Transactions on Geoscience and Remote Sensing, 1–1. https://doi.org/10.1109/tgrs.2022.3179626. DOI: 10.1109/tgrs.2022.3179626 Handle: 10754/677969 - [Preprint]
Title: Stochastic Multi-Dimensional Deconvolution. Publication Date: 2022-02-09. Handle: 10754/677969 arXiv: 2202.04486