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GCFootprints in Seismic Data*
By
Surinder Sahai1 and Khalid Soofi2
Search and Discovery Article #40230 (2007)
Posted February 21, 2007
*Adapted from the Geophysical Corner column, prepared by the authors, in AAPG Explorer, January, 2007. Editor of Geophysical Corner is Bob A. Hardage. Managing Editor of AAPG Explorer is Vern Stefanic; Larry Nation is Communications Director.
1Associate professor, Oklahoma State University, Stillwater, Oklahoma ([email protected])
2Senior research fellow, ConocoPhillips, Houston, Texas
The term
“acquisition footprint” is often used to describe amplitude stripes that appear
in time slices or horizon slices produced from 3-D
seismic data volumes.
Although acquisition design of a
3-D
survey has a major influence on the nature
and severity of a footprint, improper data
processing
techniques – such as the
use of incorrect normal moveout (NMO) velocities – can also create footprints.
This article discusses the effect of survey design on footprints and illustrates what can be done to mitigate footprint effects at the interpretation stage.
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Figure 1a is a
time slice extracted from an onshore In this case it is easy to surmise that the footprint tends to mimic the acquisition design. In other cases, a footprint pattern can be unpredictable in real data. Zig-zag geometry is another common Figure 1b is a time slice of data acquired with a mirror zig-zag pattern across an area adjacent to the orthogonal survey displayed in Figure 1a. One feature of this latter image is the absence of an obvious footprint. These examples illustrate that survey design influences the presence or absence of acquisition footprints in seismic data.
Any data-acquisition or data-
A comparison of Figure 2 with Figure 1b illustrates this point: For the mirrored zig-zag survey design, the footprint is hardly noticeable in the time slice at 1020 msec (Figure 1b). However, a time slice at 1200 msec (Figure 2a) has a footprint that appears as north-south vertical striping; whereas, a time slice at 1550 msec (Figure 2b) does not show a footprint. In this data volume, a footprint is absent at a shallower depth (Figure 1b), then appears at a deeper depth (Figure 2a), and then disappears again at yet a deeper depth (Figure 2b). Other factors can modify an acquisition
footprint or create additional footprints. Despite our best efforts to
design In many cases, such as the example in Figure 2a, an interpreter can look past the footprints and do a good job of inferring the geology. In other instances, the footprint may be so severe that it masks important information about the geology. In Figure 1a, for example, the presence of a channel in the image’s northeast corner is completely masked by the footprint. A properly designed filter applied in the frequency-wave number domain can reduce the vertical and horizontal stripes in the time slice and make it easier to see the channel (Figure 3). Some interpretation workstations provide the capability to design and apply such filters to data during an interpretation phase.
Summary
In
summary, we should attempt to minimize footprints by employing proper
seismic acquisition and
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