Masw Sheet

Nonreflection seismic and inversion of surface and guided waves

656 The Leading Edge June 2013


MASW for geotechnical site investigation

Multichannel anaylsis of surface waves (MASW) is a seismic surface-wave technique developed specifically

for near-surface applications at depths usually shallower than a few tens of meters (Park et al., 1999). Since its introduction in the late 1990s, use of the technique has rapidly increased for two reasons: (1) it provides the shear-wave velocity (VS) of ground materials, which is one of the most important geotechnical parameters in civil engineering, and (2) it is easier to use than other common seismic approaches (e.g., refraction, reflection, and surface-wave surveys).

Elastic moduli are commonly used in geotechnical en-gineering to describe the behavior of Earth materials under stress, which is ultimately related to such tasks as properly designing earthworks and structural foundations, risk assess-ment under specific site conditions, and monitoring various types of existing infrastructures for public safety. Among three primary types of modulus—Young’s (E), shear (μ), and bulk ( ) moduli—the first two are most commonly used because of what they represent. Young’s modulus simply describes the deforma-tion tendency along the axis of stress, whereas the shear modulus describes the tendency of shape deformation (“shearing”) that, in turn, is related to the viscosity of material.

Young’s and shear moduli are determined from the pa-rameters of density ( ), shear-wave velocity (VS), and Pois-son’s ratio ( ) (Figure 1). From the two defining equations shown in the figure, it is obvious that VS plays the most im-portant role as it is included as squared terms. In addition, VS in reality changes through a broader range than density and Poisson’s ratio. Therefore, accurate evaluation of VS can be ex-tremely valuable in geotechnical engineering. As shown in the equations, the shear modulus can be determined fairly accu-rately once VS is known. On the other hand, Young’s modulus requires Poisson’s ratio to obtain a comparable accuracy.

MASW provides VS information of ground materials by processing Rayleigh-type surface waves that are dispersive when travelling through a layered media (different frequen-cies travel at different speeds). This dispersion property is de-termined from a material’s shear-wave velocity (VS) (by more than 95%), P-wave velocity (VP) (≤ 3%), and density ( ) (≤ 2%). By analyzing dispersion properties, we can therefore de-termine VS fairly accurately by assuming some realistic values for VP and . The accurate evaluation of the dispersion prop-erty is most important with any surface-wave method in this sense.

By using a 2D wavefield transformation (for example, f-k transformation), the MASW method converts raw field data in a time-offset (t-x) domain directly into a frequency-phase velocity (f-v) domain in which dispersion patterns are evident through the wavefield maxima. The remaining procedure ex-tracts a dispersion curve of, usually, fundamental mode that will be used in a subsequent process in search for the one-dimensional (1D) VS profile. An accurate dispersion analysis is obviously an important part of data processing, and this is

CHOON PARK, Park Seismic LLC

Figure 1. Defining equations for Young’s and shear moduli showing relationship with shear-wave velocity ( VS ) and other parameters.

Figure 2. A diagram showing the relative amplitude change with offset among surface waves, body waves, and ambient noise indicating that the most commonly used offset range for MASW data acquisition is usually shorter than 100 m. This almost always falls into the “optimum offset” due to the strong energy of surface waves.

Site Class S-velocity (VS)(ft/s)

S-velocity (VS)(m/s)

A(Hard rock)

> 5000 > 1500

B(Rock)

2500−5000 760−1500

C(Very dense soil and

soft rock)

1200−2500 360−760

D(Stiff soil)

600−1200 180−360

E(Soft clay soil)

< 600 < 180

F(Soils requiring

additional response)

< 600, and meeting some additional

conditions

< 180, and meeting some additional

conditions

Table 1. NEHRP seismic site classification based on shear-wave velocity ( VS ) ranges.

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June 2013 The Leading Edge 657


as liquefaction evaluation, is related to the elastic property of VS that is closely linked to the viscosity of material; the lower the VS, the more viscous is the material. On the other hand, ground amplification for a given earthquake mag-nitude, which causes most earthquake-related damages, changes with ground stiffness at relatively shallow depths. Based on the premise established from empirical studies that the top 30 m influences the most, and also from the fact that the shear-wave velocity (VS) is the best indicator of stiffness, the average VS in the top 30 m (usually denoted as Vs30m) is used as an important criterion in the design of building structures. In general, a site with a lower Vs30m would be subject to a greater ground amplification (and suffer more damage from an earthquake).

The National Earthquake Hazard Reduction Program (NEHRP) established by the U.S. Congress in 1977 adopts this criterion and classifies a site into one of several categories (Table 1). The International Building Code (IBC) published the same classification designations in 2000 as one of the pa-rameters that should be accounted for in structural design.

Calculation of the average VS for a certain depth range (for example, the top 30 m) can be accomplished in two ways: (1) based on relative thickness-contribution of each layer (method 1 in Figure 3), and (2) based on the defini-tion of velocity—total distance (∑di) divided by total travel time (∑ti) that is calculated by summation of thickness (di) divided by velocity (Vsi) of each layer (method 2 in Figure 3). Both methods can yield significantly different results for the same VS profile as illustrated by using a simple two-layer VS profile. Vs30m as defined in International Building Code (IBC 2000 and later editions) uses the second method, which tends to put a heavier weight on the lower VS:

Vs30m = ∑di / ∑ti = 30 / ∑(di/Vsi) (m/s) (1)

One of the most demanding applications for Vs30m evaluation occurs in wind-turbine site characterization (Park

and Miller, 2005). In this case, the VS value provided by MASW is important to account in the foundation design not only for the potential earthquake hazard, but also for the continuous and prolonged vibration of the ground pro-duced by rotating blades. Vs30m values and corresponding site classes presented in Figure 4 are selected from sites at sev-eral different wind farms in the midwest and the northeast. They are presented in the typical format to deliver the results to the engineers.

Site characterization of a potential nuclear power plantAnother example of the application of MASW for 1D (depth) site character-ization comes from the seismic hazard assessment of potential nuclear power

why it is often the signal-to-noise ratio (SNR) of dispersion image that directly influences reliability of MASW results.

A high SNR is required in all types of wave-based tech-niques to achieve highly accurate results. The surface-wave method utilizes Rayleigh waves as signal—the most trouble-some source-generated noise in the history of exploration seismology, commonly known as ground roll. Surface waves provide the highest SNR possible in any type of seismic ap-proach. As a consequence, the field operation for data acqui-sition and subsequent data analysis become extremely simple and effective, almost always ensuring the most reliable results.

MASW is the most advanced surface-wave method be-cause of its full adaptation of the multichannel principles long used in seismic exploration for natural resources. Figure 2 illustrates the tolerance in data acquisition with MASW by showing that the common range of source-receiver offsets re-quired for most geotechnical projects—usually shorter than 100 m—is optimal within which a high SNR is almost always guaranteed. The area too close to the source (for example, ≤ 5 m) is usually avoided because of the near-field effects that pre-vent full development of surface waves. On the other hand, an excessively far offset (for example, ≥ 100 m) is also avoided because of far-field effects that can make the energy level of surface waves drop below that of ambient noise.

Because shear-wave velocity (VS) information is a good indicator of the material stiffness, MASW is often applied in civil engineering to deal with mechanical aspects of ground materials (for example, assessment of load-bearing capacity, ground behavior under continuous and prolonged vibration, and ground amplification and liquefaction potential under earthquake). MASW also finds application in mapping the soil/bedrock interface, which is often more usefully and re-alistically defined from the stiffness concept than any other characteristics (Miller et al., 1999).

Seismic site classification—Vs30mOne application of MASW in earthquake engineering, such

Figure 3. Two possible ways to calculate an average shear-wave velocity ( VS ). The second method used for Vs30m tends to put a heavier weight on the lower VS .

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plants that are routinely subjected to machinery vibration and potential ground motion from earthquake. An instance recently implemented at Thyspunt, South Africa, is presented.

To meet the increasing demands for electricity generation, the gov-ernment of South Africa is commit-ted to the construction of several new nuclear power plants, with the coastal site at Thyspunt, west of Port Elizabeth, being considered as one of the sites for characterization (Figure 5) (Bommer et al., 2013). Although South Africa is not a region of elevat-ed seismicity, destructive earthquakes have occurred. The most recent had a magnitude 6.2 and occurred in 1969. Commissioned by the state-owned energy utility (Eskom), the Council for Geoscience (CGS), one of the National Science Councils of South Africa, conducted a seismic hazard analysis following the most stringent international standards. The MASW survey, adopted as one of the several approaches for this comprehensive analysis, was conducted at six differ-ent locations in the area (Figure 5). The purpose was to evaluate VS struc-ture to depths as deep as possible, preferably down to 100 m.

Because of the unusually deep in-vestigation depth being sought, both active and passive surveys were con-ducted using a 48-channel seismic acquisition system and 4.5-Hz geo-phones as receivers. Since all the sites were in remote coastal areas without strong vibration sources available, such as traffic, passive surveys relied on ocean activities for lower frequen-cy surface waves (for example, 10 Hz or lower). In addition, two different active surveys were conducted at each site: one with relatively short receiver spacing (dx) of 1 m and a 5-kg sledge hammer source, and another with a longer dx of 4 m and a rock-drop source facilitated by a tracked hoe (Figure 6). The former survey setup was designed to investigate relatively shallow depths (for example, ≤ 30 m) and the latter was designed to investigate deeper depths (≤ 50 m).

Most sites had soft sandy overburden of varying thick-nesses, thereby attenuating surface waves quite rapidly, especially in the short-spread surveys using a sledge hammer source. The long spread surveys with the rock-drop source

generated sufficient energy at frequencies as low as 10 Hz and lower at some sites (Figure 7). The passive survey adopted a two-dimensional cross-receiver array with a 10-m separation between receivers (Figure 6).

Dispersion imaging results from these passive surveys also showed remarkable energy at the lowest frequencies in the range of 4 −20 Hz (Figure 7). The results from the long-spread active surveys were quite similar, with differences mainly in

Figure 5. Site map of a potential nuclear power plant in Thyspunt, South Africa, that shows six MASW sites and deep borehole sites.

Figure 4. Shear-wave velocity (VS ) profiles selected from five different wind-turbine sites that fall into each different class in seismic site classification (as defined in Table 1).

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the higher-frequency content and resolution. All three types of dispersion images were stacked on top of each other to extend the usable bandwidth and increase the overall SNR of images. This stacking also enhanced higher-mode patterns that existed in different frequency bands on different images (Figure 7).

The inversion process to produce a 1D VS profile at each site consisted of two phases. The first phase used only the fundamental-mode (M0) curve to produce the first approxi-mation of the velocity profile. Then, using this as an initial model in the second phase, fundamental and higher-mode dispersion curves were generated through the forward model-ing process. These multimodal dispersion curves were then examined against observed patterns in the stacked dispersion image. This second phase of multimodal inversion was car-ried out and repeated after manually changing the velocity (VS) and thickness models until satisfactory matches were found. Figure 8 shows the final VS profiles at all six sites obtained through this two-phase inversion approach. Theo-retical bounds for 50% change in dispersion curves are also indicated in the profile. Borehole data from PS-suspension logging are also presented in Figure 9 with their locations marked on the map in Figure 5.

No borehole sites were close enough to any MASW site to allow a meaningful direct comparison. Nonetheless, borehole data can show possible VS ranges of overburden and bedrock in the area. They show bedrock depths change significantly from one site to another in an unpredictable manner. They indicate VS of overburden at about 200 m/s and that of bed-rock at about 1500−3500 m/s with fluctuations between the two. MASW results also show VS values of bedrock in a similar but slightly lower range and almost the same VS of overburden (Figure 8). Depths of bedrock are also observed changing without any predictable pattern.

Underground mine investigationAnother common application area of MASW is mapping bedrock in depth and relative competence related to stress

Figure 6. A costal view (left) from an MASW site at the potential nuclear power-plant location in Thyspunt, South Africa. Ocean activities generated surface waves for passive surveys that used a 2D receiver array (center). A rock-drop source using a tracked hoe (right) was used for the active survey.

Figure 7. Dispersion images obtained from passive and active data sets acquired at site 1 in Thyspunt, South Africa. The image created from combining (stacking) the two images is shown at the bottom.

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these newly constructed highway segments as a means to monitor the general condition of the bedrock. MASW sur-veys were conducted as one of the approaches at the four target locations marked on the map in Figure 10. The main purpose of the MASW surveying was to map the general to-pography of bedrock and any other noteworthy subsurface features that could be linked to potential progression of bed-rock weakening or vertical migration of collapse structures.

To simultaneously survey two 12-ft wide lanes (both driv-ing and passing), a specially built double land streamer was

from overburden and cultural activities. The interface be-tween overburden and underlying bedrock can be a sharp boundary such as soil over competent basement rock, or a gradational transition such as the buried bedrock influenced by a severe weathering process with no physically distinct boundary. From a perspective of elastic property, the inter-face is also a sharp boundary in the former case, whereas it is a gradational change in the latter case because the weathered top portion would consist of varying degree of rock stiffness. This suggests the stiffness mapping by MASW would show the interface from a highly realistic standpoint.

MASW is known to provide highly effective and accurate informa-tion about bedrock depth, especially at depths shallower than 20 m or so. This is because surface-wave disper-sion properties are highly sensitive to change in this depth range. Although the shear-wave velocity (VS) of over-burden can be accurately estimated, VS of the bedrock tends to be slightly underestimated as depth increases be-yond the most sensitive range of 20 m unless special care is taken during the initial model creation at the be-ginning of inversion process.

Naturally, a common application would be the bedrock mapping in as-sociation with public safety where a potential hazard of bedrock collapse exists due to man-made or natu-ral causes in the subsurface such as mining and karst sinkhole develop-ment. Mapping bedrock topography can delineate the collapsed features, whereas a zone of bedrock with sig-nificantly lower VS than adjacent ar-eas may indicate a potential for verti-cal migration of a void.

In 2009, the Minnesota Depart-ment of Transportation (MnDOT) built a special type of pavement called CRCP (continuously reinforced con-crete pavement) along several seg-ments of Trunk Highway (TH) 169 in Chisholm, Minnesota (Figure 10). This construction followed several surface collapse features in the area near TH169 that were deemed to be related to previous mining activities for more than 100 years that left a subsurface maze of abandoned mine shafts and tunnels (Figure 10).

In 2011, the Office of MnDOT Materials launched a project that in-cluded geophysical approaches to in-vestigate subsurface conditions below

Figure 9. Deep borehole data from PS-suspension logging at six locations in Thyspunt, South Africa.

Figure 8. MASW results of five-layer shear-wave velocity ( VS ) profiles at six sites in Thyspunt, South Africa.

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used to collect surface-wave data by using a 48-channel ac-quisition system with each land streamer equipped with 24 4.5-Hz geophones installed at 1-m spacing (Figure 11). The left- and right-side land streamers (facing from source) were connected to channels 1−24 and 25−48 of the seismograph, surveying on driving and passing lanes, respectively. A pow-erful weight-drop source specially designed and built at the University of Saskatchewan in Canada was used to generate surface waves 6 m ahead and at the midpoint between the two streamers (Figure 11). To minimize traffic control and to avoid traffic-generated noise as much as possible, surveying took place during the night.

Figure 12 shows typical field records from each land streamer and corresponding images of fundamental-mode dispersion patterns that possess an almost ideal SNR (i.e., 100% signal) in a broad frequency band of approximately 5−40 Hz. Figure 13 shows analyzed 2D shear-wave velocity

(VS) maps for the longest survey line on the eastbound lanes (line 3) that were obtained with a maximum analysis depth of 25 m.

The bedrock surface is denoted by a relatively sharp tran-sition boundary of velocities from approximately 200 m/s to 500 m/s. The bedrock depth is shown to gradually increase from about 7 m on the western end to the maximum depth of about 20 m on the eastern end, and this general trend con-formed to the boring results from several locations along or near the surveyed line. Interoverburden layers of higher veloc-ity materials are probably lenses of gravels and boulders. They can be identified on both maps of driving and passing lanes, appearing as localized lenses and continuous layers. This in-terpretation is consistent with the general geology of the area as confirmed from borings and other sources.

Although the two maps from each lane look identical at a regional scale, differences are noticeable when examined from a local perspective. For example, bedrock is slightly deeper on the eastern half of the passing-lane map, and interoverburden layers have slightly different depths and lateral extent. Con-sidering the identical and consistent acquisition conditions

Figure 10. Aerial map showing locations of four MASW survey lines on Trunk Highway (TH) 169 near Chisholm, Minnesota. Locations of mine properties and workings are also shown.

Figure 11. The double land streamers (24-channel acquisition each) built at the Minnesota Department of Transportation (MnDOT) for the simultaneous MASW surveys over two (driving and passing) lanes on TH169. The weight-drop source shown in the inset used a polyethylene impact plate that tends to increase surface-wave energy at lower frequencies. To minimize traffic-generated noise and the burden of traffic control, surveys took place during the night.

Figure 12. Typical field records from MASW surveys on TH169, and their corresponding dispersion images from each land streamer that show almost ideal signal-to-noise ratio of 100% signal.

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Figure 13. MASW results of 2D shear-wave velocity (VS ) maps for line 3 from the surveys on TH169. Results from left (channels 1–24, driving lane) and right (25–48, passing lane) land streamers are shown.

the two land streamers were subjected to, it is reasonable to attribute these differences to subtle subsurface realities.

ReferencesBommer, J. J., K. J. Coppersmith, E. Hattingh, and A. P. Nel, 2013,

An application of the SSHAC level 3 process to the probabilistic seismic hazard assessment for the Thyspunt nuclear site in South Africa: Proceedings, 22nd International Conference on Structural Mechanics in Reactor Technology (SMiRT22).

Miller, R. D., J. Xia, C. B. Park, and J. M. Ivanov, 1999, Multichannel analysis of surface waves to map bedrock: The Leading Edge, 18, no. 12, 1392–1396, http://dx.doi.org/10.1190/1.1438226.

Park, C. B., R. D. Miller, and J. Xia, 1999, Multichannel analysis of surface waves: Geophysics, 64, no. 3, 800–808, http://dx.doi.org/10.1190/1.1444590.

Park, C. B. and R. D. Miller, 2005, Seismic characterization of wind turbine sites near Lawton, Oklahoma, by the MASW method: Kansas Geological Survey Open-file Report 2005-22.

Acknowledgments: I thank officials at Eskom in South Africa for permission to use the data sets in this article. Julian J. Bommer at Imperial College, London, UK, and Artur Cichowicz at the Coun-cil for Geosciences (CGS) in South Africa played critical roles in getting permissions. I also acknowledge all those actively involved in the field operation during the MASW surveys at the Thyspunt nuclear site. Cichowicz and Denver Birch from CGS made major contributions to the MASW work. Henni de Beer of ESKOM facilitated access to the site and provided assistance in clearing the MASW test locations. Vincent Jele, Robert Kometsi, and Leonard Tabane of the CGS assisted Birch and two TI team members, Ellen Rathje and Adrian Rodriguez-Marek, with the MASW field work. Wits University provided some equipment for use in the active MASW testing. Institute of Mining Seismology (IMS) performed the passive MASW experiments. Special thanks to Jason Richter at Minnesota Department of Transportation (MnDOT) for the

generosity in allowing TH169 data to be used for this publication as well as sharing other related information.

Corresponding author: [email protected]

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Masw Sheet