Name
Abstract | ||
|---|---|---|
In this paper, we introduce a new technique for multidimen- sional filtering of irregularly sampled seismic data. In this context filtering may be used for coherent noise and interfer- ence attenuation, as well as the generation of seismic images. The filtering operation consists of the convolution of the fil- ter operator with the seismic data. The filter operator is usu- ally computed on a regular grid (rectangular or hexagonal) that corresponds to the nominal sampling of the seismic data. Unfortunately, in the physical world the seismic data are of- ten sampled at irregular spatial locations. Hence the two functions (the filter and the data) are defined on grids that do not match. Convolving these two functions without due re- gard to this fact would result in a degradation of the filtering performance. One way to solve this problem would be to interpolate the seismic data onto the regular grid. However, due to the shear volume of seismic data this approach would be prohibitively expensive in practice. We propose a meth- odology to solve the filtering problem in an accurate and economical way. In the proposed approach, the filter coeffi- cients are first interpolated onto the irregular grid on which the seismic data are sampled. This is followed by the convo- lution of the filter operator and the seismic data over the common irregular grid. The convolution requires the numeri- cal integration of the product of two irregularly sampled spa- tial functions, which can be performed by a 2D generaliza- tion of the trapezoidal rule. The numerical integration can be achieved by tessellating the irregular grid through Delaunay triangularization and computing geometry-dependent scaling factors for each grid point. The interpolated filter coefficients are then scaled by the geometry-dependent weights. The re- sultant filter coefficients can be optionally renormalized such that the filter response within a selected subset of the multi- dimensional spectrum is identical to that of the ideal filter. Finally, the modified filter can be applied to the seismic data using any conventional convolution procedure. |
Year | Venue | Field |
|---|---|---|
2005 | European Signal Processing Conference | Mathematical optimization,Digital filter,Root-raised-cosine filter,Convolution,Filter (signal processing),Algorithm,Filtering problem,Separable filter,Grid,Mathematics,Filter design |
DocType | ISBN | Citations |
Conference | 978-160-4238-21-1 | 1 |
PageRank | References | Authors |
0.37 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Ozbek | 1 | 1 | 0.71 |
| Ralf Ferber | 2 | 1 | 0.37 |
| Western Geco | 3 | 1 | 0.37 |