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Most of
the time the acquisition footprint is based on  source and receiver line
spacings and orientations; the larger the line spacing, the more severe
the footprint. In land situations where access is very open and,
therefore, the lines are very regularly spaced, we may be able to
recognize the footprint very clearly. Because the geometry is regular,
the footprint also will have the same periodicity.
Fold
variations themselves are the simplest form of an acquisition footprint.
Fold changes with offset (or rather mute distance from the source
point); each offset range, therefore, has differing fold contributions.
Because
each individual bin of a 3-D survey has changing offset distributions,
the CMP stack of all traces in a bin will display bin-to-bin amplitude
variations. This variation in itself can produce an acquisition
footprint (Figure 1).
Some
processors compensate for this with simple trace borrowing from
surrounding bins to fill in the missing offsets and to provide smooth
offset distributions in all bins. Although this may be successful in
reducing the footprint, it also may reduce the resolution by degrading
the high frequency content.
Generally
it has been thought that acquisition footprint is far worse in the
shallow part of the seismic -- and therefore, of course, the geological
-- section, mainly because the fold is lower, and amplitude variations
necessarily are far more dramatic. Offset limited fold variations alone
may produce a recognizable footprint. The higher the fold, the better
the signal-to-noise ratio; therefore, less footprint is evident.
Wide
recording patch geometries are far more accepted these days than narrow
patch geometries. The reasons are numerous and range from reduction in
acquisition footprint (particularly that due to back-scattered shot
noise) to improved statics solutions and the availability of large
channel capacities on seismic recording crews (also leading to higher
fold).
In
addition to the impact of the fold variations, acquisition footprints
are made worse by source-generated noise trains that penetrate our data
sets (Figure 2). The lower the signal-to-noise ratio is, the worse the
footprint will be.
Unfortunately, the noise typically has a low frequency content that is
much less affected by attenuation. Therefore, the noise becomes more
prominent relative to the signal content deeper in the section. Our
experiences have shown that acquisition footprint problems can be just
as prevalent in the deep section as they are in the shallower section.
If surface
access is poor because of topography variations, tree cover, towns,
etc., we irregularize the geometry by moving source points to locations
of easier access, and, therefore mask the acquisition footprint. It is
still present, however. The footprint is just so much harder to
identify.
Weather
and surface conditions may also impact the recorded amplitudes. A swamp
in the middle of a 3-D survey can have a significant impact on the
amplitude of a stack volume. The interpreter reviewing the 3-D volume
has to decide what is a geological anomaly and what is acquisition
footprint. Not always an easy task!
We can
model an acquisition footprint by creating a stack response on either
synthetic or real data. Starting out with a geological model of the
subsurface, any source-generated noise can and should be included if the
noise velocities and frequencies are well known.
We stack
the data in a 3-D cube (Figure 3) and display the resulting seismic data
over a small time window; e.g., 60 ms (Figure 4, depending on the
frequency of the data). This process can be repeated using real seismic
data as an input. The best input is a single NMO and static-corrected,
offset-sorted 2-D (or 3-D) CMP gather. These traces will be applied to
each CMP bin in the recording geometry.
The
correct offsets for each bin are then stacked in that bin to create NMO-corrected
CMP gathers and the time interval of interest studied. This process is
repeated for any acquisition geometry under consideration for the
recording of the seismic data. The geometry with the least variation in
this modeled stack response (acquisition footprint) should be chosen.
Processing
artifacts also can leave an imprint on stacked seismic data, for
example, by applying wrong NMO velocities. Choosing incorrect velocities
will leave remnant moveout on the horizons that should have been stacked
as flat data. This affects the primaries as well as multiples and
source-generated noise; now possibly all of them leave undesirable
amplitude and phase distortions in our data.
Interpreters have lived with footprint since the advent of 3-D. In order
to advance our interpretations further, we need to understand and
recognize footprint, and make every effort to distinguish it from
geology.
Acquisition footprint has many different sources. It should be minimized
as much as possible, preferably at the recording stage. Therefore, one
should always model the acquisition footprint for different recording
geometries under consideration.
Generally,
wider acquisition patches are better. Increasing the fold will help
reduce the footprint. Moving source points (and receiver stations) in
the field produces an irregular acquisition geometry, and, therefore,
the footprint may not be as severe.
Removal of
an acquisition footprint is possible to some degree in the sophisticated
seismic data processing centers, but is not performed on a routine
basis.
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