Abstract
© 2014 European Association of Geoscientists & Engineers. The conventional velocity scan can be computationally expensive for large-scale seismic data sets, particularly when the presence of anisotropy requires multiparameter scanning. We introduce a fast algorithm for 3D azimuthally anisotropic velocity scan by generalizing the previously proposed 2D butterfly algorithm for hyperbolic Radon transforms. To compute semblance in a two-parameter residual moveout domain, the numerical complexity of our algorithm is roughly O(N3logN) as opposed to O(N5) of the straightforward velocity scan, with N being the representative of the number of points in a particular dimension of either data space or parameter space. Synthetic and field data examples demonstrate the superior efficiency of the proposed algorithm.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 368-377 |
| Number of pages | 10 |
| Journal | Geophysical Prospecting |
| Volume | 63 |
| Issue number | 2 |
| DOIs | |
| State | Published - Nov 11 2014 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The authors would like to thank the associate editor and two anonymous reviewers for their valuable comments and suggestions, Chevron for the field data, and King Abdullah University of Science and Technology and sponsors of the Texas Consortium for Computational Seismology (TCCS) for financial support. 1 The log function in this paper refers to logarithm to base 2. 2 An octree is a tree data structure in which each internal node has exactly eight children. 3 All the examples will be made reproducible in Madagascar software package (Fomel et al. 2013). 4 Single-core performance on an Apple Macintosh equipped with 2.2-GHz Intel Core i7. Same for other examples.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.