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Curvelet-based Gather Conditioning for Effective Depth Imaging of Legacy Seismic Data -Case Study from Central Poland
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 76th EAGE Conference and Exhibition 2014, Jun 2014, Volume 2014, p.1 - 5
Abstract
Here we demonstrate a case study of depth imaging applied to legacy data (shot in 70s and 80s) from Central Poland with a strong overprint of salt tectonics. We use a novel, curvelet-based approach to condition the low-fold gathers in order to improve the performance of the autopicker and subsequent tomographic model updates. Superior results are obtained when a proper conditioning of the gathers is done before running autopicker for tomography. Our 2D Discrete Curvelet Transform based conditioning algorithm run in a two-step mode on the common offset sections and on the depth-slices seems to improve the performance of the autopicker and thus provide more reliable input to grid tomography. Additionally, in case of legacy data, such conditioning acts as a trace regularization.