Automatic statics and residual statics correction with low-rank approximation

Seismic data, mainly on land, suffers from long-wavelength statics due to the laterally varying and heterogeneous nature of the near-surface weathering layers. We propose an automatic, data-driven and computationally efficient statics correction method based on low-rank approximation to correct for such statics. The method does not require a model to estimate static time shifts, which is the case for other static correction methods; rather it applies the appropriate static corrections on the data such that it becomes low rank in a certain domain. As of now, the method is applicable to data that has been corrected for elevation statics. Due to the near-surface irregularities and due to approximations used by static correction methods that lead to not fully correcting for statics, an iterative residual statics correction becomes necessary. Our proposed method corrects for residual statics without the necessity of the surface consistency assumption and a multi-iterate process. Additional benefits of the method include artifacts and noise suppression. We demonstrate the successful application of our method on several synthetic data examples.

https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2018/alfara...