Abstract
Summary Nonlinear beamforming is an effective method to enhance the quality of noisy seismic data. It uses local kinematic operators to describe local wavefronts, and then stack neighboring traces guided by these operators to improve the signal-to-noise ratio of data. Although the 2+2+1 method is a pragmatic solver to estimate local kinematic operators from input data, its computation efficiency is still challenging when the solution space is big. We propose to speed up the 2+2+1 method using graphics processing unit (GPU) computing with the Compute Unified Device Architecture (CUDA) programming language. We introduce our GPU-based 2+2+1 algorithm, and demonstrate its efficiency improvement using a field data example. A speed-up factor of ∼10 is obtained compared to the CPU version of the 2+2+1 method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
