Open Access3D steerable pyramid decomposition and its application in seismic data processing and interpretation
Author(s) -
Chun Hui Lin,
Tang Xiang-rong
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/569/1/012094
Subject(s) - weighting , pyramid (geometry) , noise (video) , computer science , algorithm , process (computing) , attenuation , scale (ratio) , seismic wave , artificial intelligence , geology , image (mathematics) , mathematics , acoustics , geometry , optics , seismology , physics , quantum mechanics , operating system
The application of 3D multi-scale geometric analysis in seismic data processing and interpretation is still in the preliminary stage. The principle of 3D Steerable Pyramid decomposition and reconstruction in frequency domain is analyzed in detail. Spherical low- pass filters and steerable filters are adopted to realize multi-scale and multi-directional decomposition of 3D Steerable Pyramid, and applied to the actual 3D seismic data for random noise attenuation, detection of faults, channels and sand bodies by selecting weighting function in the process of reconstruction. The application of actual 3D seismic data shows that: 1) When the weights are all equal to 1, perfect reconstruction is achieved, the random noise can be removed by threshold method in the decomposition domain of 3D Steerable Pyramid, the denoising results are clean, and the continuity of the event, the characteristics of the reflected wave group and the breakpoint are clearer; 2) Weighting reconstruction can enhance some features. Compared with amplitude and coherent attribute analysis, the data weighting reconstructed by 3D Steerable Pyramid decomposition not only shows faults and channels completely and meticulously, but also presents an even more impressive picture of sand body’s boundary, thus achieving the optimal application effect.