Stacking seismic data using local correlation |
Guochang Liu, Sergey Fomel, Long Jin, Xiaohong Chen
State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Beijing, China
Bureau of Economic Geology,
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX, USA, 78713-8924
Institute for Geophysics,
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
Austin, TX, USA, 78713-8924
Stacking plays an important role in improving signal-to-noise ratio and imaging quality of seismic data. However, for low-fold-coverage seismic profiles, the result of conventional stacking is not always satisfactory. To address this problem, we have developed a method of stacking in which we use local correlation as a weight for stacking common-midpoint gathers after NMO processing or common-image-point gathers after prestack migration. Application of the method to synthetic and field data showed that stacking using local correlation can be more effective in suppressing random noise and artifacts than other stacking methods.
Stacking seismic data using local correlation |