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Figure Captions
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Acquisition and
 Processing
In deepwater
multicomponent seismic data acquisition, there is a large elevation
difference between source stations (an air gun at the sea surface) and
receiver stations on the seafloor. Conventional processing of deepwater
4-C seismic data involves a wave-equation datuming step that transforms
the data to a domain in which sources and receivers are on the same
depth plane. This step effectively removes the water layer and allows
the data to be processed as if the source was on the seafloor. This
adjustment of source-receiver geometry also allows deepwater
multicomponent data to be processed with software already developed for
shallow-water environments where marine multicomponent data acquisition
technology was originally developed and applied.
An example of a
good-quality, deepwater P-P image of near-seafloor geology made with
this wave-equation datuming approach is shown as
Figure 1a. This image shows local geology associated with a
fluid-gas expulsion chimney that extends to the seafloor.
If a person wishes
to study near-seafloor strata, a new approach to P-P imaging of
deepwater multicomponent seismic data is to not eliminate the large
elevation difference between sources and receivers but to take advantage
of that elevation difference. The objective is to process deepwater
multicomponent data similar to the way vertical seismic profile (VSP)
data are processed, because VSP data acquisition also involves large
elevation differences between sources and receivers (Figure
2).
Users of VSP
technology know VSP data provide high-resolution images of geology near
downhole receiver stations. That same logic leads to the conclusion that
deep-water multicomponent seismic data processed with VSP-style
techniques should yield higher resolution images of geology near deep
seafloor receivers.
The P-P processing
illustrated here can be done with either 2-C or 4-C seafloor sensors.
The fundamental requirement is to acquire data with a sensor having a
hydrophone and a vertical geophone. The seafloor hydrophone response (P)
and the seafloor vertical-geophone response (Z) are combined to create
downgoing (D) and upgoing (U) P-P wavefields as:
D=P+Z/cos(F)
U=P--Z/cos(F)
“F”
defines the incident angle at which the downgoing compressional wave
arrives at the seafloor. Once this wavefield separation is done,
deepwater multicomponent seismic data are defined in terms of downgoing
and upgoing wavefields, just as are VSP data.
Having access to
downgoing (D) and upgoing (U) wavefields means sub-seafloor reflectivity
can be determined by taking the ratio U/D. This reflectivity wavefield
is then segregated into stacking corridors, and data inside these
corridors are summed to create image traces just like VSP data have been
processed for the past 20-plus years.
Figure 1b shows a P-P image made with this technique using the same
deep-water data displayed in Figure 1a. The
improvement in resolution is obvious.
Applications and
Constraints
Applying this VSP-style
imaging technique to deepwater multicomponent seismic data is proving to
be invaluable for gas hydrate studies, geomechanical evaluations of
deepwater seafloors and other applications where it is critical to image
near-seafloor geology with optimal resolution.
Every seismic
data-processing technique, however, has constraints and pitfalls. Two
principal constraints of the technology described here are:
In
Part 1, we considered how to improve the seismic resolution of
deepwater, near-seafloor geology using P-P data acquired with
seafloor-positioned multicomponent sensors.
In Part 2, we show
how P-SV (converted-shear) data acquired with these same sensors provide
even greater resolution of deepwater, near-seafloor strata.
Wave Length
To achieve better
resolution of geologic targets with seismic data, it is necessary to
acquire data that have shorter wavelengths. The wavelength
l
of a propagating seismic wave is given by:
l
= V/f
where V is
propagation velocity and f is frequency.
This equation shows
there are two ways to reduce an imaging wavelength
l:
either increase f, or reduce V.
If deepwater strata
are illuminated with conventional air gun seismic sources towed at the
sea surface, there is really no way to cause a significant increase in
the frequency content of the illuminating wavefield that reaches the
seafloor. A different data-acquisition strategy has to be used to
acquire shorter-wavelength marine P-P data.
An approach now
used for acquiring deepwater, short-wavelength P-P data is to use an
Autonomous Underwater Vehicle (AUV) system.
An AUV travels only
50 meters or so above the seafloor and illuminates seafloor strata with
chirp-sonar pulses having frequency bandwidths of 2-10 kHz. This
increase in signal frequency shortens P-P wavelengths by about a factor
of 100 compared to the wavelengths of an air gun signal. The result is
an illuminating wavefield having wavelengths of less than a meter when
P-wave velocity VP is 1500 to 1600 m/s, a common range of VP for
deepwater, near-seafloor sediments across the Gulf of Mexico (GOM).
An example of an
AUV chirp-sonar image acquired in water depths of approximately 900
meters in one area of the GOM is shown in Figure
3a. The image makes the same traverse across a targeted seafloor
expulsion chimney that was illustrated in last month’s article.
These
high-frequency P-P signals penetrate only 40 or 50 meters into the
seafloor, but they image bedding and fault throws of meter-scale
dimensions across this image space.
It is not possible
to acquire shorter-wavelength P-P data by reducing VP in a seismic
propagation medium. The value of VP within a system of targeted strata
is fixed and cannot be altered.
A seismic imaging
effort, however, can switch from the conventional approach of using the
P-P seismic mode and focus on using another wave mode that does have
reduced velocity within a targeted interval. That logic has great
benefit for imaging deepwater, near-seafloor geology when the imaging
effort focuses on P-SV data rather than on P-P data.
Across most
deep-water areas, S-wave velocity VS in near-seafloor sediments tends to
be 20 to 50 times less than P-wave velocity VP. Thus, if P-P and P-SV
data have equivalent frequency content, which they do for shallow
penetration distances of an illuminating P-P wavefield into the
seafloor, P-SV data will have wavelengths much shorter than P-P
wavelengths.
Shown as
Figure 3b is a P-SV image constructed from
4C data acquired with seafloor sensors deployed along the same profile
as the AUV data in Figure 3a. The illuminating wavefield that created
these P-SV data was a 10-100 Hz P-P wavefield produced by a
conventional air gun array positioned at the sea surface.
Because VS in
near-seafloor sediment along this profile is less than 100 m/s, the P-SV
data have many wavelengths less than one meter in length, just as do the
high-frequency chirp-sonar data. Visual inspection of the images in
Figure 3 shows the spatial resolutions of
kilohertz-range P-P data and low-frequency P-SV data are equivalent in
deep-water, near-seafloor geology.
The same data are
shown again in Figure 4, with
depth-equivalent horizons superimposed to emphasize the amazing
resolution of the low-frequency P-SV data. Horizon A shown on the AUV
image is not easily seen on this particular P-SV image, so no P-SV
equivalent horizon is labeled.
Note the large
magnitudes of the interval values of the VP/VS velocity ratio. Also note
how easy it is to identify where stratigraphy first becomes
unconformable to the seafloor in these seafloor-flattened data (Horizon
B).
Unfortunately,
these high-resolution P-SV images cannot be extended to great
sub-seafloor depths. P-SV wavelengths increase and P-SV resolution then
decreases with increasing depth below the seafloor because:
·
VS increases with depth.
·
Higher frequencies attenuate
more rapidly with depth for P-SV wavefields than for their companion P-P
wavefields.
At sub-seafloor
depths of several kilometers, P-P and P-SV data have approximately the
same resolution. However, for deepwater strata close to the seafloor,
the spatial resolution of P-SV data is most impressive (Figures
3b and 4b).
Information about
this technology is available at
www.beg.utexas.edu/indassoc/egl/.
WesternGeco provided the seismic data used in this research. Research
funding was provided by Minerals Management Service (Contract
0105CT39388) and DOE/NETL (Program DE-PS26-05NT42405).
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