High Performance GPGPU Structure-preserving Smoothing for Seismic Amplitude Data by Anisotropic Diffusion
G.M. Faustino, P.C. Pampanelli, J.M.V. Duarte Junior, E.A. Perez, E.R. Silva, P. Frederick and P.M.C. Silva
Event name: 78th EAGE Conference and Exhibition 2016
Session: HPC for Geophysical Applications
Publication date: 31 May 2016
Info: Extended abstract, PDF ( 2.39Mb )
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Noise attenuation plays an important role in seismic data processing and interpretation. In recent years, the anisotropic diffusion filter has received much attention since it has superior performance in edge-preserving while smoothing noise from noisy signals. This work presents a high-performance General Purpose Graphics Processing Unit (GPGPU) structure-preserving smoothing for seismic amplitude data by anisotropic diffusion. The obtained results show that the proposed method runs in iterative time, and is able to remove noise and preserves structural features efficiently. We also compare the computational performance of CPU and GPU implementations and show that GPU is about 14 times faster.