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Interpolation of near offsets using multiples and prediction-error filters
William Curry and Guojian Shan
Abstract:
Most conventional marine reflection seismic data lack sampling of near
offsets. We address this problem by interpolating data with a
nonstationary prediction-error filter (PEF) that is first estimated
from fully-sampled training data and then is used to interpolate
missing data to produce an interpolated output. These training data
need not be perfect, and may differ in amplitude and phase but should
contain the local multi-dimensional amplitude spectra of the data we
wish to recreate. We generate pseudo-primary data by crosscorrelating
multiples and primaries in the recorded data. These pseudo-primary
data can be generated at missing near offsets, but contain many
artifacts, so it is undesirable simply to replace the missing data
with the pseudo-primaries. Fortunately, many of the problems with the
pseudo-primaries do not influence PEF estimation, so a desirable PEF
can be obtained from these data, and then used to interpolate the
missing near inline offsets to produce a result that is superior to
direct substitution of the pseudo-primaries into the missing offsets.
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 | Interpolation of near offsets using multiples and prediction-error filters |  |
![[pdf]](icons/pdf.png) |
Next: Introduction
Up: Reproducible Documents
2009-04-13