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Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: A feasibility study
Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: a feasibility study Steven D. Sloan, Jeffery J. Nolan, Seth W. Broadfoot, Jason R. McKenna, Owen M. Metheny PII: DOI: Reference:
S0926-9851(13)00217-6 doi: 10.1016/j.jappgeo.2013.10.004 APPGEO 2372
To appear in:
Journal of Applied Geophysics
Received date: Accepted date:
23 May 2013 17 October 2013
Please cite this article as: Sloan, Steven D., Nolan, Jeffery J., Broadfoot, Seth W., McKenna, Jason R., Metheny, Owen M., Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: a feasibility study, Journal of Applied Geophysics (2013), doi: 10.1016/j.jappgeo.2013.10.004
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: a feasibility study
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Steven D. Sloana, Jeffery J. Nolanb, Seth W. Broadfoota, Jason R. McKennac, and Owen M. Methenya a
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XRI Geophysics, LLC, 6207 Highway 80, Vicksburg, MS, USA, 39180, Email: [email protected], [email protected], [email protected]. b
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Kansas Geological Survey, 1930 Constant Avenue, Lawrence, KS, USA, 66047, Email: [email protected]. c
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Corresponding author: Steve Sloan [email protected], +1-407-592-2171 XRI Geophysics ATTN: Steve Sloan 6207 Hwy 80 Vicksburg, MS 39180
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U.S. Army Engineer Research & Development Center, 7701 Telegraph Road, Alexandria, VA, USA, 22315, Email: [email protected].
ACCEPTED MANUSCRIPT Abstract
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Near-surface seismic refraction and surface wave data were collected at a site to determine the feasibility and limitations of using these seismic methods to detect and localize a Data sets were collected both before and after the
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shallow tunnel in unconsolidated sediments.
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construction of the tunnel. We were able to detect the air-filled cavity using multichannel analysis of surface waves. The refraction tomography results showed the tunnel location in the
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raypath coverage plots, but only small velocity variations were observed. In tandem the two
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methods would reduce false positives, but individually the false alarm rate would likely be high due to non-uniqueness of the results. In this geologic setting, these methods are not the best
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choice of geophysical methods to detect clandestine tunnels and should be combined with other
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geophysical techniques to improve and constrain interpretations.
1. Introduction
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Keywords: near-surface, seismic, refraction, surface wave, void
Illegal tunnels pose a threat to several nations around the world for various reasons including narcotic trafficking (USA-Mexico border), unregulated trade (Egypt-Gaza border), and attacks (Israel-Gaza border), to name a few. Research using geophysical methods to detect these tunnels has been ongoing for multiple decades with much of the early work focusing on large and deep targets in hard rock environments on the Korean peninsula (Ballard, 1982; Rechtien, 1995) and more recent work looking at shallower features in unconsolidated sediments (Llopis et al., 2005; Tucker et al., 2007). Despite the volume of previous studies, no individual technology
ACCEPTED MANUSCRIPT or method has been identified or developed that can detect and localize clandestine tunnels efficiently, consistently, and across a variety of geological settings. Whereas one method, such
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as GPR, may work great at a particular site, it may not work at all at another depending on
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subsurface properties such as clay content, dielectric permittivity, etc., or target parameters (depth, size) and the same can be said for all geophysical methods, not just GPR. As with most
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geophysical studies, appropriate methods are chosen based on the goal of the study and
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properties of the site to be surveyed. The study presented here focuses on the use of seismic refraction tomography and multichannel analysis of surface waves (MASW) to determine the
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potential of the two methods for tunnel detection at shallow depths. Multiple examples of different geophysical techniques have been applied to tunnel
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detection (Cho et al., 2006; Choi et al., 1999; Greenfield et al., 1991; Llopis et al., 2005; Mahrer and List, 1995; Rechtien et al., 1995; and Sloan et al., 2011), including seismic, electromagnetic,
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and radar, among others. Near-surface seismic methods in particular have been used for both general void detection (Branham and Steeples, 1988; Dobecki, 1988; Inazaki et al., 2005; Peterie et al., 2009) and tunnel detection (Belfer et al., 1998; Llopis et al., 2005; Rechtien et al., 1995; Sloan et al., 2011; Tucker et al., 2007; Walters et al., 2007; Walters et al., 2009). From a theoretical standpoint, seismic methods would be a good choice for void detection due to the drastic change in seismic properties from a geologic medium to an air-filled void (Sloan et al., 2011). Sheehan et al. (2005) describe an example of locating an interpreted water-filled void in a karst environment using seismic refraction tomography at a depth of approximately 20 m. The cavity in this case was much larger than a typical tunnel, but did exhibit noticeable variations in
ACCEPTED MANUSCRIPT the P-wave velocity profile. More recent examples have applied refraction tomography methods to detect voids at depths of 0.6 and 6 m. Hickey et al. (2009) buried a plastic pipe at 0.6 m depth
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using cut-and-fill and subsequently completed a seismic refraction survey orthogonal to the
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buried pipe. The authors noted reduced P-wave velocity (VP) around and above the pipe; however, the method of emplacement also disturbed the overlying material, which would be
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expected to produce a similar result. Riddle et al. (2010) used refraction tomography to detect a
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concrete tunnel 1 m x 1.6 m in size approximately 6 m deep. Their results show subtle changes in raypath coverage and VP compared to the surrounding material. The main difference between
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past studies and the work presented here is that an actual tunnel is used that was constructed in a similar fashion to illegal cross-border tunnels, providing a more representative target and
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removing extraneous influences such as overburden that has been disturbed by target emplacement. This study is the first that we are aware of to use an actual tunnel in a controlled
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environment for research purposes.
The objective of the research presented here was to determine the feasibility and limitations of using near-surface seismic refraction traveltime tomography and MASW methods to detect and locate a small-diameter, shallow tunnel in an environment comprised of dry unconsolidated materials. Baseline data were collected prior to the construction of the tunnel and are compared with coincident data collected after the tunnel was completed. Results of this study show that these methods can be used to detect voids in the right geologic setting; however, individually the results of one method alone may be inconclusive and would be best used by combining with other seismic or geophysical methods to reduce uncertainty and increase
ACCEPTED MANUSCRIPT confidence in the results. This work was done as part of an undergraduate senior research
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project.
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2. Site Description
The tunnel used for this study was dug using a 6 m by 6 m vertical shaft for entry, exit,
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and spoil removal. Digging was done using mechanical hand tools similar to those discovered in
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recent tunnel seizures along the southwest US border, such as hammer drills, to accurately represent the target of interest. Overlying and surface material was not disturbed during
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construction. The roof of the tunnel is located at 3 m depth and the tunnel has a size of 1.25 m width and 1.25 m height (Figure 1). The tunnel is shored using wooden beams and the walls and
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ceiling are also lined with wooden boards.
The site of investigation is located in the northeastern portion of the Great Basin near the
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Great Salt Lake, a sub-province of the Basin and Range province in the United States. The area of investigation is underlain by a thin layer of Holocene-age eolian sheet-sand deposits overlying Pleistocene-age lacustrine deposits related to the former existence of Lake Bonneville. Drilling at the site yielded 0.5-1.0 m of eolian sheet sands across the entire site, underlain by fine-grained lacustrine deposits. The eolian deposits consist of fine-grained, loose to medium-dense silty sand and sandy silt. The lacustrine deposits are comprised of alternating layers of silt, sandy silt, and silty sand, overlying gravelly sands and clayey sand toward the bottom of the borings.
3. Methods
ACCEPTED MANUSCRIPT Multiple shallow seismic data sets were collected at the site including refraction tomography (P and S), and MASW over a three day period in July and again in November of
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2010 (Figure 2). Each survey was conducted along a coincident line with similar acquisition
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geometries and parameters (Table 1). Data sets were acquired both before and after construction of the tunnel, besides the MASW dataset which was acquired only after. The pre-construction P-
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wave seismic refraction data were collected using 144 100-Hz vertical-component geophones
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with 0.25 m spacing. The source was a 1.36 kg (3 lb) hammer struck on a steel plate with 0.5 m spacing. The first shot point was 5 meters away from the first geophone and the last shot point
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was 5.25 meters beyond the last geophone. Ninety-three source locations were occupied over a total distance of 46 m. Data were recorded using six 24-channel seismographs with 24-bit A/D
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conversion, 0.25-ms sampling interval, and 256 ms trace lengths. Post-construction data were acquired using 144 40-Hz vertical-component geophones with 0.25 m spacing due to equipment
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availability constraints, but the other acquisition parameters remained the same. Shear-wave refraction data were also acquired using the same parameters with the exception that 14.5-Hz horizontal-component geophones were used, with the same hammer impacting a horizontal shear block for the source. The source and receivers were oriented to collect horizontally polarized (SH) data. Each data set was collected during the same visit for both pre- and post-construction surveys. However, the post-construction S-wave data proved too noisy to reliably pick first breaks due to wind noise and required another return visit one year later in the fall of 2011. Surface wave data were collected using 96 4.5-Hz vertical-component geophones spaced at 1 meter intervals. An accelerated weight drop provided the input energy
ACCEPTED MANUSCRIPT every 1 meter. The first source location was 20 meters in front of the first geophone and ended 8 meters past the last geophone. This resulted in a total of 124 shot locations.
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Seismic refraction tomography methods typically utilize a grid of either fixed or variable
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sized cells to represent the subsurface. Forward modeling methods, such as a finite difference method, are used to predict ray paths and travel times between source locations and receivers.
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Cell velocities are iteratively adjusted until the misfit between the observed and predicted travel
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times is within some acceptable range. In this case the wavepath eikonal traveltime (WET) inversion scheme is used (Schuster and Quintus-Bosz, 1993).
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The data were processed using commercial software packages, including SurfSeis 3 and Rayfract. The refraction data were processed by inputting raw field files, defining geometry, and
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picking the first arrivals for each shot. There are a total of 13,392 time-offset pairs from 144 first arrival picks on each of 93 different shot locations. The cell size used was 12.5 cm on each side,
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for a total of 100 cells representing the tunnel. The surface wave data processing included geometry definition, overtone analysis, manual picking of fundamental mode dispersion curves (Figure 3), and inverting the dispersion curves to calculate shear-wave velocity. In-depth explanations on the theory and processing for MASW and refraction tomography can be found in Park et al. (1999), Xia et al. (1999), and Sheehan et al. (2005). All source and receiver locations were used for the refraction analysis; however, the surface wave field files were cut to mimic an off-end configuration with constant source-to-receiver offset. We chose a one-meter offset with a 24-channel spread in this case after testing various parameters.
4. Results and Discussion
ACCEPTED MANUSCRIPT The pre- and post-construction ray coverage plots for the P- and S-wave data are displayed in figures 4a and 5a, respectively. The pre- and post-construction VP and VS profiles
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are shown in figures 4b and 5b, top and bottom, respectively. The void is located at 19 m along
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the x-axis in Figure 4 and 17.5 m in Figure 5, with the top at approximately 3 m depth (the center of the dashed circle). The lateral discrepancy in the void location between the P and S data sets
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is due to the monument used as a reference point for positioning the lines being accidentally
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dislodged between the collection of the pre-construction P- and S-wave lines. VP remains relatively constant from pre- to post-construction; however, there is a slight decrease in the post-
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construction VP where the void is located, dropping from approximately 550 m/s to 450 m/s. The VP profiles exhibit a change in velocity of approximately 22% when comparing the before and
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after. VS drops from approximately 400 to 325 m/s, which is a 23% change. Intuitively we expected a greater change in the S-wave data compared to the P-wave data, but the percent
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change is very similar. Although both the P-and S-wave results show changes greater than 20%, seismic velocity variations of that scale are not uncommon in the shallow subsurface. Even within a short ~35-m long line there are changes equal to or greater than those observed at the tunnel location and do not appear anomalous.
The left-hand side of figures 4 and 5 (a) show raypath coverage plots for the pre- and post-construction cases (top and bottom, respectively) for the P- and S-wave data. Seismic waves propagate in accordance with Fermat’s principle of least time, so it is expected that fewer rays pass through the void area due to the decreased velocity. This response is expected since the excavation of geologic material has left behind an air-filled void with a velocity of approximately 335 m/s, which is less than that of the surrounding medium. Comparing the
ACCEPTED MANUSCRIPT before and after plots in Figure 4 shows a decrease in the number of rays from ~1400 to 600, representing a decrease of 57% in the P-wave data. The raypath coverage of the S-wave data
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drops from approximately 1780 to 730, marking a 41% change. In this example, the raypath
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coverage plot does the best job of highlighting the influence of the void and presents a noticeable contrast in both the P- and S-wave data. Both pre- and post-construction plots are comparable,
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containing similar features in both. The contrast between the surrounding medium and the void
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would become even more pronounced in an environment with higher seismic velocities.
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Figure 6 shows difference plots calculated by subtracting the post-construction grid files from those of the pre-construction. The difference in ray coverage is on the top and velocity is
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on the bottom. P-wave data are on the left in Figure 6a and S-wave data are on the right in
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Figure 6b. As with the pre and post comparison plots, the change in ray coverage is the most
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evident, indicated by the areas within the dashed circles. The high events to the left of the void location and and the low events beneath it in the P-wave data are not representative of the void, but are a byproduct of the differencing where the rays have traveled around the void location. The velocity difference plot shows minor changes in the velocity where the tunnel is located, but nothing that sticks out anomalously compared to the surroundings. The surface wave data in Figure 7 also show an anomaly in the shear-wave velocity profile that is coincident with the known tunnel location. The location of the void is at station number 1023 in this profile (marked by the red-dashed circle). The MASW plot shows an increase in velocity above the void, overlying a zone of decreased velocity at the tunnel location, marked by the high-velocity halo. These high-velocity haloes have been observed above voids in other studies and are interpreted to be caused by zones of increased stress due to the removal of
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Refraction tomography data presented here were acquired using 0.25-m receiver spacing and 0.5-
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m source spacing; however, this high-density data acquisition is unrealistic outside of a research environment, especially when covering large areas. To determine the feasibility of using this
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type of method in a production mode using larger spacings, the P-wave data set was decimated to
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simulate 0.5, 1.0, and 2.0 m spacings. Figure 8a-e shows velocity plots for 0.5-m receiver and 0.5-m source spacing, 1.0-m and 1.0-m, 2.0-m and 1.0-m, and 2.0-m and 2.0-m receiver and
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source spacing, respectively. Figure 8f-j show the corresponding ray coverage plots. The velocity plots do not noticeably change as the receiver and source spacings are altered; however,
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the ray coverage plots exhibit a noticeable degradation as the number of data points is reduced. Based on a qualitative comparison of the plots displayed, the optimum receiver/source spacings
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with respect to both subsurface coverage and labor required to acquire the data would be 1.0-m receiver and 1.0-m source spacing, which is also the same as the parameters used to acquire the MASW data. In that regard, a single data set collected with these parameters could be used for both refraction tomography and MASW. In this study the MASW and raypath coverage plots were the most indicative of the tunnel location. The refraction velocity plots show subtle changes in velocity that can be attributed to the void; however, these small variations would not serve as a suitable indicator of a subsurface anomaly independently without previous knowledge of the location and depth of the tunnel and are not anomalous with respect to geology related velocity variations. From a practical application standpoint, neither of these methods alone would be the optimal choice to
ACCEPTED MANUSCRIPT locate a small-diameter tunnel due to the high number of anomalies that would likely be observed because of the small change in velocity from unconsolidated sediments to an air-filled
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cavity. Ideally multiple seismic and/or other geophysical methods would be applied and as more
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methods are combined to refine the interpretation, more positive detections would accumulate at a common anomaly to further define its location. In this case, the true-positive percentage would
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likely increase, along with the reduction of false positives, by using multiple techniques for
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redundancy and cross-validation, which also increases the confidence in results.
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5. Conclusions
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In conclusion, voids in the shallow subsurface, including tunnels, are challenging to
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successfully image due to the non-uniqueness inherent to all geophysical methods and limited resolution. In both of the seismic refraction tomography surveys described here, we attempted to detect a man-made tunnel measuring 1.25 m wide, 1.25 m tall, and 3 m deep. The refraction tomography data show a drop in velocity of 22-23% and a noticeable decrease in ray coverage at the tunnel location, which is expected since the void is air filled and has a lower seismic velocity compared to the surrounding medium. MASW results from the same site also show a lowvelocity zone at the tunnel location. The results from these data are in good agreement with what we would expect based on theory. In most instances it is a given that the applications described here, including shallow void or tunnel detection, would not afford the luxury of having pre-void data sets to compare to. However, for the purposes of this study—determining the feasibility of using refraction
ACCEPTED MANUSCRIPT traveltime tomography and MASW methods to detect a shallow tunnel in unconsolidated sediments—using pre- and post-construction data sets further demonstrates the nonuniqueness of
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the results and the limitations of the methods when the number of potential anomalies is
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expected to be small. In this case, only subtle variations are observed and are no more anomalous than other changes in velocity related to subsurface heterogeneity. Future work may
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include time-lapse surveys to observe property variations with time, cross-hole tomography, and
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applying the same techniques to deeper targets to determine depth limitations in similar
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environments.
6. Acknowledgements
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The authors wish to thank Ron Elliston, Kenny Mclaughlin, and Ryan Strange for
7. References
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assistance in the field and the reviewers for their constructive edits and suggestions.
Ballard, R.F., 1982. Tunnel Detection. Technical Report GL-82-9, U.S. Army Engineer Waterways Experiment Station, 1-94. Belfer, I., Bruner, I., Keydar, S., Kravtsov, A., Landa, E., 1998. Detection of shallow objects using refracted and diffracted seismic waves. J. of Applied Geophysics, 38, 155-168. Branham, K.L., Steeples, D.W., 1988. Cavity detection using high-resolution seismic reflection methods. Mining Eng., 40, 115-119 Cho, S., Kim, J., Kim, C., Sung, N., 2006. Tunnel detection using borehole radar survey. SEGJ Annu. Meeting, Abstract.
ACCEPTED MANUSCRIPT Choi, H.K., Ra, J.W., 1999. Detection and identification of a tunnel by iterative inversion from cross-borehole CW measurements. Microw. and Optical Technology Letters, 21,
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458-465.
mine workings. SAGEEP Proceedings, 666-690.
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Dobecki, T.L., 1988. A rapid seismic technique for detecting subsurface voids and unmapped
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Greenfield, R.J., Cameron, C.P., MacLean, H.D., Moran, M.L., 1991. Interpretation of cross-
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borehole radar signals propagating along a tunnel containing a wire. SEG International Meeting, Abstract, 411-413.
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Hickey, C.J., Schmitt, D.R., Sabatier, J.M., Riddle, G., 2009. Seismic measurements for detecting underground high-contrast voids. SAGEEP Conference Proceedings, 929-936.
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Inazaki, T., Kawamura, S., Tazawa, O., Yamanaka, Y., Kano, N., 2005. Near-surface cavity detection by high-resolution seismic reflection methods using short-spacing type land
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streamer. SAGEEP Proceedings, 959-970. Llopis, J.L., Dunbar, J.B., Wakeley, L.D., Corcoran, M.K., 2005. Tunnel detection along the southwest U.S. border. SAGEEP Proceedings, 430-443. Mahrer, K.D., List, D.F., 1995. Radio frequency electromagnetic tunnel detection and delineation at the Otey Mesa site. Geophysics, 60, 413-422. Park, C.B., Miller, R.D., Xia, J., 1999. Multichannel analysis of surface waves. Geophysics, 64, 800-808. Peterie, S.L., Miller, R.D., Steeples, D.W., 2009. Diffraction imaging versus reflection processing for shallow void detection. SEG International Annu. Meeting, Abstract, 14211424.
ACCEPTED MANUSCRIPT Rechtien, R.D., Greenfield, R.J., Ballard, R.F., 1995. Tunnel signature prediction for a crossborehole seismic survey. Geophysics, 60, 76-86.
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Riddle, G.I., Hickey, C.J., Schmitt, D.R., 2010. Subsurface tunnel detection using electrical
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resistivity tomography and seismic refraction tomography: a case study. SAGEEP Proceedings, 552-562.
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Schuster, G.T., Quintus-Bosz, A., 1993. Wavepath eikonal traveltime inversion: Theory.
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Geophysics, 58, 1314-1323.
Sheehan, J.R., Doll, W.E., Mandell, W.A., 2005. An evaluation of methods and available
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software for seismic refraction tomography analysis. J. of Env. and Eng. Geophysics, 10, 21-34.
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Sloan, S.D., Peterie, S.L., Ivanov, J., Miller, R.D., McKenna, J.R., 2011. Void detection using near-surface seismic methods. Advances in Near-Surface Seismology and Ground-
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Penetrating Radar, SEG Geophysical Developments Series, 15, 201-218. Tucker, R.E., McKenna, J.R., McKenna, M.H., Mattice, M.S., 2007. Detecting underground penetration attempts at secure facilities. Engineer, 37, 31-34. Walters, S.L., Miller, R.D., Xia, J., 2007. Near surface tunnel detection using diffracted p-waves: a feasibility study. SEG International Meeting, Abstract, 1128-1132. Walters, S.L., Miller, R.D., Steeples, D.W., Xia, J., Zeng, C., 2009. Detecting tunnels and underground facilities using diffracted P-waves. SAGEEP Proceedings, 937-942. Xia, J., Miller, R.D., Park, C.B., 1999. Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics, 64, 691-700.
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8. Figures; Figures 3-7 should be in color in the print and online versions.
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Figure 1. Picture of the tunnel used in this study during construction.
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Figure 2. Illustration depicting the layout of the surface wave line (a), S-wave lines (b), and P-
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wave lines (c). Note that that all data sets were collected along the same coincident line (a), but
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have been spread out for illustration purposes as indicated by the dashed arrows.
Figure 3. Representative overtone image and interpreted fundamental mode dispersion curve (indicated by the line with white squares) for the MASW line.
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Figure 4. P-wave velocity profiles (right) and ray coverage profiles (left) produced by the
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seismic refraction tomography surveys. The top profiles are pre-construction velocity and the bottom profiles are post-construction. There is a slight decrease in velocity and change in raypath coverage after construction of the void. The middle of the circle indicates the position of the tunnel.
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Figure 5. S-wave velocity profiles (right) and ray coverage profiles (left) produced by the seismic refraction tomography surveys. The top profiles are pre-construction and the bottom
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profiles are post-construction. There is a slight decrease in velocity and change in raypath
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tunnel.
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coverage after construction of the void. The middle of the circle indicates the position of the
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Figure 6. Difference plots for ray coverage (top) and velocity (bottom), calculated by subtracting the post-construction data from the pre-construction data for the P- (left) and S-wave (right) data.
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The middle of the circle indicates the position of the tunnel.
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Figure 7. A shear-wave velocity profile produced by the MASW method. The high-velocity halo
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is noticeable in the locality of the void, indicated by the red-dashed circle. The middle of the
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circle indicates the position of the tunnel.
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Figure 8. Plots showing the change in velocity (left) and ray coverage (right) for decimated source/receiver spacing combinations of 0.5-m/0.25-m (a, f), 0.5-m/0.5-m (b, g), 1.0-m/1.0-m (c, h), 1.0-m/2.0-m (d, i), and 2.0-m/2.0-m (e, j). The middle of the circle indicates the position of the tunnel.
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MASW
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Refraction (P) Refraction (S)
1m
1m
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Refraction (P) Refraction (S)
Seismic Acquisition Parameters Receiver Spacing Source Spacing Channels Geophone Pre-Construction 0.25 m 0.5 m 144 100-Hz 0.25 m 0.5 m 144 14.5-Hz Post-Construction 0.25 m 0.5 m 144 40-Hz 0.25 m 0.5 m 144 14.5-Hz
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Seismic Line
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9. Table
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4.5-Hz
Source Hammer Hammer Hammer Hammer Weight Drop
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Table 1. Summary of the seismic acquisition parameters for the different lines collected.
ACCEPTED MANUSCRIPT Highlights
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This study was done as part of an undergraduate research project. Seismic methods were used to determine feasibility of detecting shallow tunnels. Tomography velocity results were non-unique independently. Raypath plots were the best indicator from the tomography data. Surface wave data detected the tunnel accurately.
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1. 2. 3. 4. 5.
S0926-9851(13)00217-6 doi: 10.1016/j.jappgeo.2013.10.004 APPGEO 2372
To appear in:
Journal of Applied Geophysics
Received date: Accepted date:
23 May 2013 17 October 2013
Please cite this article as: Sloan, Steven D., Nolan, Jeffery J., Broadfoot, Seth W., McKenna, Jason R., Metheny, Owen M., Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: a feasibility study, Journal of Applied Geophysics (2013), doi: 10.1016/j.jappgeo.2013.10.004
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Using near-surface seismic refraction tomography and multichannel analysis of surface waves to detect shallow tunnels: a feasibility study
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Steven D. Sloana, Jeffery J. Nolanb, Seth W. Broadfoota, Jason R. McKennac, and Owen M. Methenya a
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XRI Geophysics, LLC, 6207 Highway 80, Vicksburg, MS, USA, 39180, Email: [email protected], [email protected], [email protected]. b
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Kansas Geological Survey, 1930 Constant Avenue, Lawrence, KS, USA, 66047, Email: [email protected]. c
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Corresponding author: Steve Sloan [email protected], +1-407-592-2171 XRI Geophysics ATTN: Steve Sloan 6207 Hwy 80 Vicksburg, MS 39180
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U.S. Army Engineer Research & Development Center, 7701 Telegraph Road, Alexandria, VA, USA, 22315, Email: [email protected].
ACCEPTED MANUSCRIPT Abstract
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Near-surface seismic refraction and surface wave data were collected at a site to determine the feasibility and limitations of using these seismic methods to detect and localize a Data sets were collected both before and after the
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shallow tunnel in unconsolidated sediments.
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construction of the tunnel. We were able to detect the air-filled cavity using multichannel analysis of surface waves. The refraction tomography results showed the tunnel location in the
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raypath coverage plots, but only small velocity variations were observed. In tandem the two
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methods would reduce false positives, but individually the false alarm rate would likely be high due to non-uniqueness of the results. In this geologic setting, these methods are not the best
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choice of geophysical methods to detect clandestine tunnels and should be combined with other
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geophysical techniques to improve and constrain interpretations.
1. Introduction
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Keywords: near-surface, seismic, refraction, surface wave, void
Illegal tunnels pose a threat to several nations around the world for various reasons including narcotic trafficking (USA-Mexico border), unregulated trade (Egypt-Gaza border), and attacks (Israel-Gaza border), to name a few. Research using geophysical methods to detect these tunnels has been ongoing for multiple decades with much of the early work focusing on large and deep targets in hard rock environments on the Korean peninsula (Ballard, 1982; Rechtien, 1995) and more recent work looking at shallower features in unconsolidated sediments (Llopis et al., 2005; Tucker et al., 2007). Despite the volume of previous studies, no individual technology
ACCEPTED MANUSCRIPT or method has been identified or developed that can detect and localize clandestine tunnels efficiently, consistently, and across a variety of geological settings. Whereas one method, such
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as GPR, may work great at a particular site, it may not work at all at another depending on
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subsurface properties such as clay content, dielectric permittivity, etc., or target parameters (depth, size) and the same can be said for all geophysical methods, not just GPR. As with most
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geophysical studies, appropriate methods are chosen based on the goal of the study and
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properties of the site to be surveyed. The study presented here focuses on the use of seismic refraction tomography and multichannel analysis of surface waves (MASW) to determine the
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potential of the two methods for tunnel detection at shallow depths. Multiple examples of different geophysical techniques have been applied to tunnel
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detection (Cho et al., 2006; Choi et al., 1999; Greenfield et al., 1991; Llopis et al., 2005; Mahrer and List, 1995; Rechtien et al., 1995; and Sloan et al., 2011), including seismic, electromagnetic,
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and radar, among others. Near-surface seismic methods in particular have been used for both general void detection (Branham and Steeples, 1988; Dobecki, 1988; Inazaki et al., 2005; Peterie et al., 2009) and tunnel detection (Belfer et al., 1998; Llopis et al., 2005; Rechtien et al., 1995; Sloan et al., 2011; Tucker et al., 2007; Walters et al., 2007; Walters et al., 2009). From a theoretical standpoint, seismic methods would be a good choice for void detection due to the drastic change in seismic properties from a geologic medium to an air-filled void (Sloan et al., 2011). Sheehan et al. (2005) describe an example of locating an interpreted water-filled void in a karst environment using seismic refraction tomography at a depth of approximately 20 m. The cavity in this case was much larger than a typical tunnel, but did exhibit noticeable variations in
ACCEPTED MANUSCRIPT the P-wave velocity profile. More recent examples have applied refraction tomography methods to detect voids at depths of 0.6 and 6 m. Hickey et al. (2009) buried a plastic pipe at 0.6 m depth
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using cut-and-fill and subsequently completed a seismic refraction survey orthogonal to the
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buried pipe. The authors noted reduced P-wave velocity (VP) around and above the pipe; however, the method of emplacement also disturbed the overlying material, which would be
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expected to produce a similar result. Riddle et al. (2010) used refraction tomography to detect a
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concrete tunnel 1 m x 1.6 m in size approximately 6 m deep. Their results show subtle changes in raypath coverage and VP compared to the surrounding material. The main difference between
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past studies and the work presented here is that an actual tunnel is used that was constructed in a similar fashion to illegal cross-border tunnels, providing a more representative target and
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removing extraneous influences such as overburden that has been disturbed by target emplacement. This study is the first that we are aware of to use an actual tunnel in a controlled
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environment for research purposes.
The objective of the research presented here was to determine the feasibility and limitations of using near-surface seismic refraction traveltime tomography and MASW methods to detect and locate a small-diameter, shallow tunnel in an environment comprised of dry unconsolidated materials. Baseline data were collected prior to the construction of the tunnel and are compared with coincident data collected after the tunnel was completed. Results of this study show that these methods can be used to detect voids in the right geologic setting; however, individually the results of one method alone may be inconclusive and would be best used by combining with other seismic or geophysical methods to reduce uncertainty and increase
ACCEPTED MANUSCRIPT confidence in the results. This work was done as part of an undergraduate senior research
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project.
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2. Site Description
The tunnel used for this study was dug using a 6 m by 6 m vertical shaft for entry, exit,
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and spoil removal. Digging was done using mechanical hand tools similar to those discovered in
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recent tunnel seizures along the southwest US border, such as hammer drills, to accurately represent the target of interest. Overlying and surface material was not disturbed during
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construction. The roof of the tunnel is located at 3 m depth and the tunnel has a size of 1.25 m width and 1.25 m height (Figure 1). The tunnel is shored using wooden beams and the walls and
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ceiling are also lined with wooden boards.
The site of investigation is located in the northeastern portion of the Great Basin near the
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Great Salt Lake, a sub-province of the Basin and Range province in the United States. The area of investigation is underlain by a thin layer of Holocene-age eolian sheet-sand deposits overlying Pleistocene-age lacustrine deposits related to the former existence of Lake Bonneville. Drilling at the site yielded 0.5-1.0 m of eolian sheet sands across the entire site, underlain by fine-grained lacustrine deposits. The eolian deposits consist of fine-grained, loose to medium-dense silty sand and sandy silt. The lacustrine deposits are comprised of alternating layers of silt, sandy silt, and silty sand, overlying gravelly sands and clayey sand toward the bottom of the borings.
3. Methods
ACCEPTED MANUSCRIPT Multiple shallow seismic data sets were collected at the site including refraction tomography (P and S), and MASW over a three day period in July and again in November of
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2010 (Figure 2). Each survey was conducted along a coincident line with similar acquisition
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geometries and parameters (Table 1). Data sets were acquired both before and after construction of the tunnel, besides the MASW dataset which was acquired only after. The pre-construction P-
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wave seismic refraction data were collected using 144 100-Hz vertical-component geophones
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with 0.25 m spacing. The source was a 1.36 kg (3 lb) hammer struck on a steel plate with 0.5 m spacing. The first shot point was 5 meters away from the first geophone and the last shot point
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was 5.25 meters beyond the last geophone. Ninety-three source locations were occupied over a total distance of 46 m. Data were recorded using six 24-channel seismographs with 24-bit A/D
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conversion, 0.25-ms sampling interval, and 256 ms trace lengths. Post-construction data were acquired using 144 40-Hz vertical-component geophones with 0.25 m spacing due to equipment
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availability constraints, but the other acquisition parameters remained the same. Shear-wave refraction data were also acquired using the same parameters with the exception that 14.5-Hz horizontal-component geophones were used, with the same hammer impacting a horizontal shear block for the source. The source and receivers were oriented to collect horizontally polarized (SH) data. Each data set was collected during the same visit for both pre- and post-construction surveys. However, the post-construction S-wave data proved too noisy to reliably pick first breaks due to wind noise and required another return visit one year later in the fall of 2011. Surface wave data were collected using 96 4.5-Hz vertical-component geophones spaced at 1 meter intervals. An accelerated weight drop provided the input energy
ACCEPTED MANUSCRIPT every 1 meter. The first source location was 20 meters in front of the first geophone and ended 8 meters past the last geophone. This resulted in a total of 124 shot locations.
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Seismic refraction tomography methods typically utilize a grid of either fixed or variable
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sized cells to represent the subsurface. Forward modeling methods, such as a finite difference method, are used to predict ray paths and travel times between source locations and receivers.
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Cell velocities are iteratively adjusted until the misfit between the observed and predicted travel
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times is within some acceptable range. In this case the wavepath eikonal traveltime (WET) inversion scheme is used (Schuster and Quintus-Bosz, 1993).
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The data were processed using commercial software packages, including SurfSeis 3 and Rayfract. The refraction data were processed by inputting raw field files, defining geometry, and
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picking the first arrivals for each shot. There are a total of 13,392 time-offset pairs from 144 first arrival picks on each of 93 different shot locations. The cell size used was 12.5 cm on each side,
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for a total of 100 cells representing the tunnel. The surface wave data processing included geometry definition, overtone analysis, manual picking of fundamental mode dispersion curves (Figure 3), and inverting the dispersion curves to calculate shear-wave velocity. In-depth explanations on the theory and processing for MASW and refraction tomography can be found in Park et al. (1999), Xia et al. (1999), and Sheehan et al. (2005). All source and receiver locations were used for the refraction analysis; however, the surface wave field files were cut to mimic an off-end configuration with constant source-to-receiver offset. We chose a one-meter offset with a 24-channel spread in this case after testing various parameters.
4. Results and Discussion
ACCEPTED MANUSCRIPT The pre- and post-construction ray coverage plots for the P- and S-wave data are displayed in figures 4a and 5a, respectively. The pre- and post-construction VP and VS profiles
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are shown in figures 4b and 5b, top and bottom, respectively. The void is located at 19 m along
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the x-axis in Figure 4 and 17.5 m in Figure 5, with the top at approximately 3 m depth (the center of the dashed circle). The lateral discrepancy in the void location between the P and S data sets
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is due to the monument used as a reference point for positioning the lines being accidentally
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dislodged between the collection of the pre-construction P- and S-wave lines. VP remains relatively constant from pre- to post-construction; however, there is a slight decrease in the post-
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construction VP where the void is located, dropping from approximately 550 m/s to 450 m/s. The VP profiles exhibit a change in velocity of approximately 22% when comparing the before and
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after. VS drops from approximately 400 to 325 m/s, which is a 23% change. Intuitively we expected a greater change in the S-wave data compared to the P-wave data, but the percent
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change is very similar. Although both the P-and S-wave results show changes greater than 20%, seismic velocity variations of that scale are not uncommon in the shallow subsurface. Even within a short ~35-m long line there are changes equal to or greater than those observed at the tunnel location and do not appear anomalous.
The left-hand side of figures 4 and 5 (a) show raypath coverage plots for the pre- and post-construction cases (top and bottom, respectively) for the P- and S-wave data. Seismic waves propagate in accordance with Fermat’s principle of least time, so it is expected that fewer rays pass through the void area due to the decreased velocity. This response is expected since the excavation of geologic material has left behind an air-filled void with a velocity of approximately 335 m/s, which is less than that of the surrounding medium. Comparing the
ACCEPTED MANUSCRIPT before and after plots in Figure 4 shows a decrease in the number of rays from ~1400 to 600, representing a decrease of 57% in the P-wave data. The raypath coverage of the S-wave data
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drops from approximately 1780 to 730, marking a 41% change. In this example, the raypath
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coverage plot does the best job of highlighting the influence of the void and presents a noticeable contrast in both the P- and S-wave data. Both pre- and post-construction plots are comparable,
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containing similar features in both. The contrast between the surrounding medium and the void
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would become even more pronounced in an environment with higher seismic velocities.
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Figure 6 shows difference plots calculated by subtracting the post-construction grid files from those of the pre-construction. The difference in ray coverage is on the top and velocity is
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on the bottom. P-wave data are on the left in Figure 6a and S-wave data are on the right in
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Figure 6b. As with the pre and post comparison plots, the change in ray coverage is the most
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evident, indicated by the areas within the dashed circles. The high events to the left of the void location and and the low events beneath it in the P-wave data are not representative of the void, but are a byproduct of the differencing where the rays have traveled around the void location. The velocity difference plot shows minor changes in the velocity where the tunnel is located, but nothing that sticks out anomalously compared to the surroundings. The surface wave data in Figure 7 also show an anomaly in the shear-wave velocity profile that is coincident with the known tunnel location. The location of the void is at station number 1023 in this profile (marked by the red-dashed circle). The MASW plot shows an increase in velocity above the void, overlying a zone of decreased velocity at the tunnel location, marked by the high-velocity halo. These high-velocity haloes have been observed above voids in other studies and are interpreted to be caused by zones of increased stress due to the removal of
ACCEPTED MANUSCRIPT material and subsequent increased load borne by the sidewalls and roof (Sloan et al., 2011), since VS is directly related to stress.
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Refraction tomography data presented here were acquired using 0.25-m receiver spacing and 0.5-
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m source spacing; however, this high-density data acquisition is unrealistic outside of a research environment, especially when covering large areas. To determine the feasibility of using this
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type of method in a production mode using larger spacings, the P-wave data set was decimated to
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simulate 0.5, 1.0, and 2.0 m spacings. Figure 8a-e shows velocity plots for 0.5-m receiver and 0.5-m source spacing, 1.0-m and 1.0-m, 2.0-m and 1.0-m, and 2.0-m and 2.0-m receiver and
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source spacing, respectively. Figure 8f-j show the corresponding ray coverage plots. The velocity plots do not noticeably change as the receiver and source spacings are altered; however,
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the ray coverage plots exhibit a noticeable degradation as the number of data points is reduced. Based on a qualitative comparison of the plots displayed, the optimum receiver/source spacings
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with respect to both subsurface coverage and labor required to acquire the data would be 1.0-m receiver and 1.0-m source spacing, which is also the same as the parameters used to acquire the MASW data. In that regard, a single data set collected with these parameters could be used for both refraction tomography and MASW. In this study the MASW and raypath coverage plots were the most indicative of the tunnel location. The refraction velocity plots show subtle changes in velocity that can be attributed to the void; however, these small variations would not serve as a suitable indicator of a subsurface anomaly independently without previous knowledge of the location and depth of the tunnel and are not anomalous with respect to geology related velocity variations. From a practical application standpoint, neither of these methods alone would be the optimal choice to
ACCEPTED MANUSCRIPT locate a small-diameter tunnel due to the high number of anomalies that would likely be observed because of the small change in velocity from unconsolidated sediments to an air-filled
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cavity. Ideally multiple seismic and/or other geophysical methods would be applied and as more
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methods are combined to refine the interpretation, more positive detections would accumulate at a common anomaly to further define its location. In this case, the true-positive percentage would
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likely increase, along with the reduction of false positives, by using multiple techniques for
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redundancy and cross-validation, which also increases the confidence in results.
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5. Conclusions
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In conclusion, voids in the shallow subsurface, including tunnels, are challenging to
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successfully image due to the non-uniqueness inherent to all geophysical methods and limited resolution. In both of the seismic refraction tomography surveys described here, we attempted to detect a man-made tunnel measuring 1.25 m wide, 1.25 m tall, and 3 m deep. The refraction tomography data show a drop in velocity of 22-23% and a noticeable decrease in ray coverage at the tunnel location, which is expected since the void is air filled and has a lower seismic velocity compared to the surrounding medium. MASW results from the same site also show a lowvelocity zone at the tunnel location. The results from these data are in good agreement with what we would expect based on theory. In most instances it is a given that the applications described here, including shallow void or tunnel detection, would not afford the luxury of having pre-void data sets to compare to. However, for the purposes of this study—determining the feasibility of using refraction
ACCEPTED MANUSCRIPT traveltime tomography and MASW methods to detect a shallow tunnel in unconsolidated sediments—using pre- and post-construction data sets further demonstrates the nonuniqueness of
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the results and the limitations of the methods when the number of potential anomalies is
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expected to be small. In this case, only subtle variations are observed and are no more anomalous than other changes in velocity related to subsurface heterogeneity. Future work may
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include time-lapse surveys to observe property variations with time, cross-hole tomography, and
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applying the same techniques to deeper targets to determine depth limitations in similar
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environments.
6. Acknowledgements
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The authors wish to thank Ron Elliston, Kenny Mclaughlin, and Ryan Strange for
7. References
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assistance in the field and the reviewers for their constructive edits and suggestions.
Ballard, R.F., 1982. Tunnel Detection. Technical Report GL-82-9, U.S. Army Engineer Waterways Experiment Station, 1-94. Belfer, I., Bruner, I., Keydar, S., Kravtsov, A., Landa, E., 1998. Detection of shallow objects using refracted and diffracted seismic waves. J. of Applied Geophysics, 38, 155-168. Branham, K.L., Steeples, D.W., 1988. Cavity detection using high-resolution seismic reflection methods. Mining Eng., 40, 115-119 Cho, S., Kim, J., Kim, C., Sung, N., 2006. Tunnel detection using borehole radar survey. SEGJ Annu. Meeting, Abstract.
ACCEPTED MANUSCRIPT Choi, H.K., Ra, J.W., 1999. Detection and identification of a tunnel by iterative inversion from cross-borehole CW measurements. Microw. and Optical Technology Letters, 21,
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mine workings. SAGEEP Proceedings, 666-690.
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Dobecki, T.L., 1988. A rapid seismic technique for detecting subsurface voids and unmapped
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Greenfield, R.J., Cameron, C.P., MacLean, H.D., Moran, M.L., 1991. Interpretation of cross-
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borehole radar signals propagating along a tunnel containing a wire. SEG International Meeting, Abstract, 411-413.
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Hickey, C.J., Schmitt, D.R., Sabatier, J.M., Riddle, G., 2009. Seismic measurements for detecting underground high-contrast voids. SAGEEP Conference Proceedings, 929-936.
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Inazaki, T., Kawamura, S., Tazawa, O., Yamanaka, Y., Kano, N., 2005. Near-surface cavity detection by high-resolution seismic reflection methods using short-spacing type land
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streamer. SAGEEP Proceedings, 959-970. Llopis, J.L., Dunbar, J.B., Wakeley, L.D., Corcoran, M.K., 2005. Tunnel detection along the southwest U.S. border. SAGEEP Proceedings, 430-443. Mahrer, K.D., List, D.F., 1995. Radio frequency electromagnetic tunnel detection and delineation at the Otey Mesa site. Geophysics, 60, 413-422. Park, C.B., Miller, R.D., Xia, J., 1999. Multichannel analysis of surface waves. Geophysics, 64, 800-808. Peterie, S.L., Miller, R.D., Steeples, D.W., 2009. Diffraction imaging versus reflection processing for shallow void detection. SEG International Annu. Meeting, Abstract, 14211424.
ACCEPTED MANUSCRIPT Rechtien, R.D., Greenfield, R.J., Ballard, R.F., 1995. Tunnel signature prediction for a crossborehole seismic survey. Geophysics, 60, 76-86.
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Riddle, G.I., Hickey, C.J., Schmitt, D.R., 2010. Subsurface tunnel detection using electrical
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resistivity tomography and seismic refraction tomography: a case study. SAGEEP Proceedings, 552-562.
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Schuster, G.T., Quintus-Bosz, A., 1993. Wavepath eikonal traveltime inversion: Theory.
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Geophysics, 58, 1314-1323.
Sheehan, J.R., Doll, W.E., Mandell, W.A., 2005. An evaluation of methods and available
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software for seismic refraction tomography analysis. J. of Env. and Eng. Geophysics, 10, 21-34.
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Sloan, S.D., Peterie, S.L., Ivanov, J., Miller, R.D., McKenna, J.R., 2011. Void detection using near-surface seismic methods. Advances in Near-Surface Seismology and Ground-
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Penetrating Radar, SEG Geophysical Developments Series, 15, 201-218. Tucker, R.E., McKenna, J.R., McKenna, M.H., Mattice, M.S., 2007. Detecting underground penetration attempts at secure facilities. Engineer, 37, 31-34. Walters, S.L., Miller, R.D., Xia, J., 2007. Near surface tunnel detection using diffracted p-waves: a feasibility study. SEG International Meeting, Abstract, 1128-1132. Walters, S.L., Miller, R.D., Steeples, D.W., Xia, J., Zeng, C., 2009. Detecting tunnels and underground facilities using diffracted P-waves. SAGEEP Proceedings, 937-942. Xia, J., Miller, R.D., Park, C.B., 1999. Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics, 64, 691-700.
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8. Figures; Figures 3-7 should be in color in the print and online versions.
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Figure 1. Picture of the tunnel used in this study during construction.
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Figure 2. Illustration depicting the layout of the surface wave line (a), S-wave lines (b), and P-
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wave lines (c). Note that that all data sets were collected along the same coincident line (a), but
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have been spread out for illustration purposes as indicated by the dashed arrows.
Figure 3. Representative overtone image and interpreted fundamental mode dispersion curve (indicated by the line with white squares) for the MASW line.
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Figure 4. P-wave velocity profiles (right) and ray coverage profiles (left) produced by the
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seismic refraction tomography surveys. The top profiles are pre-construction velocity and the bottom profiles are post-construction. There is a slight decrease in velocity and change in raypath coverage after construction of the void. The middle of the circle indicates the position of the tunnel.
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Figure 5. S-wave velocity profiles (right) and ray coverage profiles (left) produced by the seismic refraction tomography surveys. The top profiles are pre-construction and the bottom
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profiles are post-construction. There is a slight decrease in velocity and change in raypath
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tunnel.
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coverage after construction of the void. The middle of the circle indicates the position of the
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Figure 6. Difference plots for ray coverage (top) and velocity (bottom), calculated by subtracting the post-construction data from the pre-construction data for the P- (left) and S-wave (right) data.
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The middle of the circle indicates the position of the tunnel.
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Figure 7. A shear-wave velocity profile produced by the MASW method. The high-velocity halo
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is noticeable in the locality of the void, indicated by the red-dashed circle. The middle of the
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circle indicates the position of the tunnel.
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Figure 8. Plots showing the change in velocity (left) and ray coverage (right) for decimated source/receiver spacing combinations of 0.5-m/0.25-m (a, f), 0.5-m/0.5-m (b, g), 1.0-m/1.0-m (c, h), 1.0-m/2.0-m (d, i), and 2.0-m/2.0-m (e, j). The middle of the circle indicates the position of the tunnel.
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MASW
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Refraction (P) Refraction (S)
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Refraction (P) Refraction (S)
Seismic Acquisition Parameters Receiver Spacing Source Spacing Channels Geophone Pre-Construction 0.25 m 0.5 m 144 100-Hz 0.25 m 0.5 m 144 14.5-Hz Post-Construction 0.25 m 0.5 m 144 40-Hz 0.25 m 0.5 m 144 14.5-Hz
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Seismic Line
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9. Table
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4.5-Hz
Source Hammer Hammer Hammer Hammer Weight Drop
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Table 1. Summary of the seismic acquisition parameters for the different lines collected.
ACCEPTED MANUSCRIPT Highlights
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This study was done as part of an undergraduate research project. Seismic methods were used to determine feasibility of detecting shallow tunnels. Tomography velocity results were non-unique independently. Raypath plots were the best indicator from the tomography data. Surface wave data detected the tunnel accurately.
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1. 2. 3. 4. 5.