Three-dimensional explicit depth migration via McClellan transformations on hexagonal sampling grids
Technical Report
·
OSTI ID:5194980
The computational cost of three-dimensional depth migration depends almost entirely on the cost of depth extrapolation. Each frequency of a 3-D seismic wavefield can be extrapolated by two-dimensional filters that vary spatially according to frequency and velocity. 2-D extrapolation filters are efficiently designed and implemented by use of McClellan transformations. McClellan transformations convert 1-D extrapolation filters to approximately circularly symmetric 2-D extrapolation filters at computational cost that is proportional to the number of unique coefficients, N, in the 1-D extrapolation filters. In contrast, the cost of direct convolution of 2-D extrapolation filters is proportional to N{sup 2}. Imaging of steep digs requires long extrapolation filters, i.e., large N, making direct 2-D convolution very expensive. Although efficient, McClellan transformations only approximate circularly symmetric 2-D filters for depth extrapolation. The accuracy of a 2-D extrapolation filter can be improved only at an increase in the cost of implementing that filter. By applying McClellan transformations on a hexagonal sampling grid, the accuracy of 2-D extrapolation filters can be improved at a reduction in cost. Furthermore, hexagonal sampling grids are the most efficient for spatially circularly band-limited seismic data, reducing the number of samples that are repeatedly processed during recursive, depth extrapolation. 17 refs., 30 figs.
- Research Organization:
- Colorado School of Mines, Golden, CO (United States). Center for Wave Phenomena
- Sponsoring Organization:
- DOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- FG02-89ER14079
- OSTI ID:
- 5194980
- Report Number(s):
- DOE/ER/14079-10; CWP--110; ON: DE91017370
- Country of Publication:
- United States
- Language:
- English
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