Brady Flinchum and Russ Carr
Refraction Methods
GPH 492
4/11/12
Survey Design
The objective of the seismic reflection and refraction survey was to image the West
Tahoe fault. Using LIDAR data Gretchen Schmauder selected an easily accessible
location near US Highway 50. Due to winter conditions we dug a trench in the snow to
reach the ground and place the geophones. The first survey used a 48-channel array
with 100-Hz geophone groups spaced at 3 meters. Each group had 6 elements planted
in-line, between channel takeouts. Due to the snow pack, the geophones that could not
be placed in ground were placed in packed ice and secured with snow. For this survey
the source was a 0.5 x 0.5 meter steel plate hit with a 16-lb (7.3-kg) sledgehammer. The
source triggered ten times at every flag location and stacked in the Bison Galilieo-21
recorder to increase the signal to noise ratio. Two days later a short survey used the
same trench but because a lot of the snow had melted, most geophones were planted
into the ground. The short line was 50 meters long and used a 48-channel array with
geophone spacing of 1 m. We placed the line over the fault that had been identified
using ground penetrating radar. Due to time constraints the source was triggered at
every other geophone on this line, an interval of 2 m.
Figure 1: Location of Seismic Refraction Survey within the South Tahoe Basin. The red line is 150 meters
in length. Another 50-meter line was conducted centered on the fault. (Image courtesy of Google Earth
2012).
Processing
We processed the refraction data using Louie’s open-source JRG package from
crack.seismo.unr.edu/jrg. The correct geometries that correspond to UTM coordinates
were added to the raw data set and the first arrivals were picked. To amplify the first
arrivals in the long line we used a Zplane filter (1.0 + i0.0_/(1.1059+i0.39815). No
filtering was necessary on the 50-meter line because the energy was easily propagated
to both ends because of the 1m offsets.
Results
Once the first arrivals have been picked they are sent to Dr. Pullammanappallil at Optim
SDS for velocity optimization. Figure 2 shows the velocity optimization results for the
two independent data sets. The fault, as identified by ground penetrating radar, was
located around 75 meters in Figure 2A and about 30 meters in Figure 2B.
Figure 2: Velocity Optimizations from both Refraction lines. A) The results from the 3-m geophone
spacing. B) The results from the 1-meter geophone spacing.
To assess how well the 3-meter line correlated with the 1-meter line we used Adobe
Illustrator to overlay the two velocity optimizations. Based on this image we can see
that at a distance of roughly 60 meters the velocities of both lines correlate well. The
only discrepancy is a small area orange color on the 1-m spacing line indicating a
3500m/s velocity. On the 3-meter spacing line this area shows a velocity in the 2000m/s
range. At a distance of 100 meters we see a high velocity section of red color that
indicates a velocity of 4000m/s on the 1-m spacing line. On the 3-m spacing line this
same area indicates a velocity of 2000m/s. This is the biggest discrepancy on the
overlay. The rest of the overlay has medium to strong correlation.
Figure 3: Velocity optimization overlay. The 1-meter line is bounded by the black borders and then
overlaid onto the 3-meter line.
The data sets were collected on two different days and thus are totally independent of
each other. The largest difference is the large low velocity zone that is absent in the
longer line. To investigate how accurate the values are we also received the hit counts.
The hit counts represent the synthetic model ray paths through the optimized velocity
model. Figure 4A shows the hit count through the long seismic refraction line, and
Figure 4B shows the hit count through the short seismic line.
To understand these hit count models, areas with white have virtually no hits and areas
with red have a large number of hits. Areas of red indicate areas with far more data and
thus can be interpreted as more accurate. After looking at the hit count models for both
lines, we can see that the 1-meter spacing line has large gaps with no hits. This is
important because the areas with low hit counts are also areas that did not correlate
well on the velocity optimization overlay in figure 3. The 3-meter spacing line also had
several gaps of low hit counts but at a much deeper depth than the 1-meter spacing
line.
Figure 4: Hit counts for the optimized velocity models. A) The hit count through the long seismic line
with 3-meter offsets. B) The hit count for the short seismic line with 1-meter offsets.
To show the density of hit counts on the seismic lines hit count overlays were
completed. On these models areas of blue had very few hits (0-10) whereas areas of
purple had high numbers of hits (40-50). These overlays correlate well with the previous
hit count models. This overlay also raises questions about the accuracy of the 1-m
spacing line. The 1-m overlay shows large gaps of blue, indicating few hits.
Figure 5: Hit count overlay for the 3-meter spacing line. Areas of blue show no hits whereas areas of
purple show high numbers of hits.
Figure 6: Hit count overlay for the 1-m spacing line. Areas of blue show no hits whereas areas of purple
show high numbers of hits.
Discussion
After looking at which velocity model best represents the ground velocities we looked at
the fits of the synthetic models. The long line which had many more hits within the fault
zone turned out to be more accurate and only had an RMS error of 0.0038 whereas the
short refraction line had an RMS value of 0.0071. Figure 7 shows the observed travel
times as diamonds at three different shot points. The synthetic travel times are marked
with x’s. Figure 4 shows a visual representation of the fits of the synthetic travel times to
the observed travel times.
Figure 7: Observed travel times and the synthetic travel time fits of three different shot points
throughout the long line. A) Fits for the 3-meter line. B) Fits for the 1-meter line.
The 150-meter line optimization was stacked and overlain with the velocity models
completed by the Reflection group. The faulting appears to be observed at x=65 meters
and x=110 meters. The 50-meter line optimization was also stacked and overlain with
the velocity models completed by the reflection group. Faulting offsets can be seen at
the bottom of the model at x=42m. Overall, with the hit count overlays the 150-meter
line appears to be a more accurate model of the West Tahoe Fault.
Figure 8: 150-meter line optimization stacked and overlain with the velocity model.
Figure 9: 50-meter line optimization stacked and overlain with the velocity model.