3-D DMO processing
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Series | Investigations in Geophysics |
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Author | Öz Yilmaz |
DOI | http://dx.doi.org/10.1190/1.9781560801580 |
ISBN | ISBN 978-1-56080-094-1 |
Store | SEG Online Store |
Prestack signal processing of the data included geometric spreading correction using a t2-scaling function (Figure 10.9-4), spiking deconvolution and time-variant spectral whitening (Figure 10.9-5). This parsimonious sequence sufficed to attain a desired flat and broad spectrum within the passband (Figure 10.9-6). Note that the coherent linear noise that dominates the raw shot record (Figure 10.9-4a) does not stand out in the shot gather after spectral balancing (Figure 10.9-5b).
Following the signal processing, the data are ready for DMO processing:
- Sort the common-shot gathers to common-cell gathers and perform stacking velocity analysis over a sparse grid of 2 × 2 km.
- Apply NMO and 3-D DMO correction to remove source-receiver azimuth and dip effects from the stacking velocities.
- Apply inverse NMO correction and repeat the stacking velocity analysis over a finer grid of 0.5 × 0.5 km. Figure 10.9-7 shows a subset of four velocity analysis panels over the survey area. Each panel comprises the common-cell gather at the analysis location and the velocity spectrum computed from it. Generally, the velocity picking from the DMO-corrected data was consistently reliable over the survey area.
- Create a 3-D DMO velocity field from the vertical functions picked in step (c).
- Apply NMO correction to the 3-D DMO-corrected data from step (c) using the velocity field from step (d) and stack the data. Figures 10.9-8 and 10.9-9 show selected inline and crossline sections, respectively, from the volume of the 3-D DMO stack following poststack deconvolution and band-pass filter.
- Perform 3-D poststack time migration using a laterally smoothed form of the 3-D DMO velocity field from step (d). Figures 10.9-10 and 10.9-11 show selected inline and crossline sections, respectively, from the image volume derived from 3-D poststack time migration. To circumvent the adverse effect of spatial aliasing on migration, especially in the crossline direction, trace interpolation before migration was considered. However, this process deteriorated the stacked data in zones of intensive faulting associated with extensional tectonism. Therefore, in lieu of trace interpolation, the unmigrated data in step (e) were filtered down to a passband of 6-36 Hz; hence the difference in the frequency content between the unmigrated data in Figure 10.9-8 and the migrated data in Figure 10.9-10.
Figure 10.9-4 (a) A raw shot record from the 3-D seismic data associated with the case study presented in 3-D structural inversion applied to seismic data from the Northeast China, (b) after geometric spreading correction.
Figure 10.9-5 (a) The same shot record as in Figure 10.9-4b after deconvolution, and (b) time-variant spectral whitening.
Figure 10.9-7 A selection of four velocity analyses applied to the 3-D data associated with the case study presented in 3-D structural inversion applied to seismic data from the Northeast China after the application of 3-D DMO correction. Shown in each panel are the common-cell gather and the velocity spectrum at the analysis location.
Figure 10.9-10 Selected inline sections from the volume of 3-D poststack time migration of the 3-D DMO-stacked data as in Figure 10.9-8.
The deliverables from phase 1 — 3-D DMO processing, include a set of 3-D DMO-corrected gathers, a volume of 3-D DMO-stacked data, a volume of 3-D DMO velocity field, and an image volume derived from 3-D poststack time migration.
See also
- 3-D structural inversion applied to seismic data from the Northeast China
- 3-D prestack time migration
- From RMS to interval velocities
- Structural inversion
- Structural and stratigraphic interpretation