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Figure 32 Reflector model for the constant-velocity test | ![]() |
A sinusoidal reflector shown in Figure creates
complicated reflection data, shown in Figures
and
. To set up a test for regularization by offset
continuation, I removed 90% of randomly selected shot gathers from
the input data. The syncline parts of the reflector lead to
traveltime triplications at large offsets. A mixture of different dips
from the triplications would make it extremely difficult to
interpolate the data in individual common-offset gathers, such as
those shown in Figure
. The plots of time slices
after NMO (Figure
) clearly show that the data are
also non-stationary in the offset direction. Therefore, a simple
offset interpolation scheme is also doomed.
![]() |
![]() |
Figure shows the reconstruction process on individual
frequency slices. Despite the complex and non-stationary character of
the reflection events in the frequency domain, the offset continuation
equation is able to reconstruct them quite accurately from the
decimated data.
![]() |
Figure shows the result of interpolation after the data
are transformed back to the time domain. The offset continuation
result (right plots in Figure
) reconstructs the ideal
data (left plots in Figure
) very accurately even in
the complex triplication zones, while the result of simple offset
interpolation (left plots in Figure
) fails as expected.
![]() |
The constant-velocity test results allow us to conclude that, when all the assumptions of the offset continuation theory are met, it provides a powerful method of data regularization.
Being encouraged by the synthetic results, I proceed to a three-dimensional real data test.