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Curvelet-based Gather Conditioning for Effective Depth Imaging of Legacy Seismic Data -Case Study from Central PolandNormal access

Authors: M. Cyz, A. Górszczyk, M. Malinowski, P. Krzywiec, M. Mulińska and T. Rosowski
Event name: 76th EAGE Conference and Exhibition 2014
Session: Seismic Noise Attenuation
Publication date: 16 June 2014
DOI: 10.3997/2214-4609.20141586
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 2.23Mb )
Price: € 20

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.

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