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Here we look at the difference between using two 1-D PEFs,
and one 2-D PEF.
Figure shows an example of sparse tracks;
it is not realistic
in the upper-left corner
(where it will be used for testing),
in a quarter-circular disk where
the data covers the model densely.
Such a dense region is ideal for determining the 2-D PEF.
Indeed, we cannot
determine a 2-D PEF from the sparse data lines,
because at any place you put the filter
(unless there are enough adjacent data lines),
unknown filter coefficients will multiply missing data.
So every fitting goal is nonlinear
and hence abandoned by the algorithm.
duelin90
Figure 6
Synthetic wavefield (left) and as observed over survey lines (right).
The wavefield is a superposition of waves from three directions.
The set of test data shown in Figure
is a superposition of three functions like plane waves.
One plane wave looks like low-frequency horizontal layers.
Notice that the various layers vary in strength with depth.
The second wave is dipping about down to the right
and its waveform is perfectly sinusoidal.
The third wave dips down to the left
and its waveform is bandpassed random noise like the horizontal beds.
These waves will be handled differently by different processing schemes,
so I hope you can identify all three.
If you have difficulty,
view the figure at a grazing angle from various directions.
Later we will make use of the dense data region,
but first let be the east-west PE operator
and be the north-south operator
and let the signal or image be .The fitting residuals are
| |
(19) |
where is data (or binned data) and masks the map onto the data.
Figure shows
the result of using a single one-dimensional PEF
along either the vertical or the horizontal axis.
dueleither90
Figure 7
Interpolation by 1-D PEF along the vertical axis (left)
and along the horizontal axis (right).
Figure compares
the use of a pair of 1-D PEFs versus a single 2-D PEF
(which needs the ``cheat'' corner in Figure .
duelversus90
Figure 8
Data infilled by a pair of 1-D PEFs (left)
and by a single 2-D PEF (right).
Studying Figure we conclude
(what theory predicts) that
- These waves are predictable with a pair of 1-D filters:
- Horizontal (or vertical) plane-wave with random waveform
- Dipping plane-wave with a sinusoidal waveform
- These waves are predictable with a single 2-D filter:
- both of the above
- Dipping plane-wave with a random waveform
Next: ALTITUDE OF SEA SURFACE
Up: Noisy data
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Stanford Exploration Project
4/27/2004