Structure-Constrained NMO Correction Method Based On Sparse Inversion
W. Wei, S. Yuan, D. Wang, T. Xie, G. Yao and S. Wang
Event name: 81st EAGE Conference and Exhibition 2019
Session: Poster: Signal Processing A
Publication date: 03 June 2019
Info: Extended abstract, PDF ( 836.62Kb )
Price: € 20
Normal moveout (NMO) correction is an essential step to eliminate the influence of offsets on the traveltime of reflections for the purpose of subsequent stacking or AVO analysis. The far-offset wide-angle reflections are used in improving the accuracy or creating initial models for inversion, and so on, however, which are often subjected to muting to suppress NMO stretching and distortion, resulting in a loss of valuable information. To avoid stretching and deal with the interfering or intersecting event, we propose a structure-constrained NMO correction method based on sparse inversion, which corrects the sparse reflectivity gather with offset-dependent traveltime different from conventional sample-by-sample NMO correction. Firstly, in order to implement inversion-based reflectivity NMO correction, we introduce an inverse NMO operator and use the known or estimated time invariant wavelets to build the relationship between the uncorrected CMP gather and the flattened reflectivity gather. Then, to obtain the stable sparse flattened reflectivity gather even at interfering or intersecting events, we impose the structural sparsity operator and the lateral L2-norm regularized constraint on the objective function. Finally, synthetic and real data examples illustrate the proposed method can provide significantly flattened, stretch-free and high-quality NMO corrected result.