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Ocean waves as a passive MASW source
Journal Pre-proof Ocean waves as a passive MASW source
John H. McBride, Stephen T. Nelson, Choon B. Park, Eugene E. Wolfe, David G. Tingey, Kevin A. Rey PII:
S0926-9851(19)30222-8
DOI:
https://doi.org/10.1016/j.jappgeo.2019.103860
Reference:
APPGEO 103860
To appear in:
Journal of Applied Geophysics
Received date:
13 March 2019
Revised date:
11 September 2019
Accepted date:
19 September 2019
Please cite this article as: J.H. McBride, S.T. Nelson, C.B. Park, et al., Ocean waves as a passive MASW source, Journal of Applied Geophysics(2019), https://doi.org/10.1016/ j.jappgeo.2019.103860
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© 2019 Published by Elsevier.
Journal Pre-proof
Ocean Waves as a Passive MASW Source
John H. McBride1,* [email protected], Stephen T. Nelson1, Choon B. Park2, Eugene E. Wolfe3, David G. Tingey1, and Kevin A. Rey1 1
Department of Geological Sciences, Brigham Young University, Provo, Utah 84602 USA Park Seismic LLC, 2 Balsam Circle, Shelton, Connecticut 06484 USA 3 Halliburton Software and Asset Solutions, 1805 Shea Center Drive Suite 400, Highlands Ranch, Colorado 80129 USA * Corresponding author.
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Journal Pre-proof ABSTRACT Ocean waves have been considered to be a source of seismic surface-wave energy for subsurface exploration. We test the utility of ocean-source seismic recording, the sensitivity to array orientation with respect to the shoreline direction, and the equivalence of passive- and active-source data acquired in a near-shore environment. The Kohala peninsula of northwestern Hawaiʻi (Big Island), with its exposure to strong trade winds and prominent rock and soil
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outcrops along sea cliffs, provides an ideal natural laboratory to study ocean noise as a passive
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seismic source. The results show that passive-source data recorded from ocean waves over a prominent headland in Kohala produce coherent surface-wave dispersion relationships (phase
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velocity as a function of frequency) that can be modeled for shear-wave velocity in the shallow We also demonstrate the
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subsurface, especially when combined with active-source data.
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dependence of the array orientation on the quality of the dispersion spectra—an array perpendicular to the shoreline produces a more complete frequency range and higher coherency,
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relative to an array oriented parallel to the shoreline. Previous geophysical investigations of the
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site, constrained by the geologic outcrop along the adjacent sea cliff, confirm the utility of the shear-wave velocity-depth modeling based on our recordings. Ocean waves can be used for
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modeling of shear-wave velocity in the upper 10-50 m of the subsurface with a relatively short array, but can be improved by combining active and passive sources and by orienting the array parallel to the direction of ocean-wave propagation.
Journal Pre-proof INTRODUCTION Surface wave dispersion has been used to measure shear-wave velocity structure of the shallow subsurface for at least the past 20 years (Park et al., 1999). These measurements aid geotechnical evaluations of construction or urban sites (Penumadu and Park, 2005; Park, 2013; Bekler et al., 2019) and constrain geological investigation of the critical zone (i.e., the shallow layer of the earth where plant and animal life, groundwater, and soils and weathered bedrock
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interact) (Parsekian et al., 2015). Active-source Multi-Channel Analysis of Survey Waves
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(MASW) and active-source Spectral Analysis of Surface Waves (SASW) are commonly used to
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obtain shear-wave velocity structure in the upper 30 m of the earth or deeper (Park et al., 1999; Lin et al., 2017). Passive-source techniques, such as Refraction Microtremor (ReMi) (Louie,
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2001; Stephenson et al., 2005; Dumont et al., 2017; Pamuk et al., 2017; Karabulut, 2018), and
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H/V Spectral Ratio (HVSR) (Nakamura, 1989; Sivaram et al., 2018), have also been developed
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for deeper investigations or for sites where an active seismic source (e.g., hammers and strike plates, weight droppers, vibrators) is impractical. Active- and passive-source techniques (Lontsi
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et al., 2016; Bajaj et al., 2019; Onnis et al., 2019) complement each other as to their advantages
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and disadvantages, the former being better suited for high-frequency, high-resolution, but shallower investigation and the latter for low-frequency, lower-resolution, but deeper investigation (given identical parameters of geophone resonant frequency, channel spacing, etc.) (Morton et al., 2015). The seismic source for MASW passive methods can be background “noise” (or microseisms) caused by industrial activities, road traffic, wind (atmospheric pressure variations), or ocean waves. Roughly speaking, seismic noise dominated by frequencies greater than 1 Hz is typically considered to be caused by human activity, while noise dominated by frequencies less than 1 Hz is considered to be natural (Okada, 2003; Yong et al., 2013). Thus, natural sources have greater potential for deeper investigation of shear-wave velocity structure
Journal Pre-proof (Park et al., 2004). Perhaps the classic passive seismic source is that emanating from ocean waves, which generate vibrations with frequencies of about 0.14 Hz (Hobiger, 2011) and for which the energy depends on the wave height (Dolenc and Dreger, 2005); however, the behavior of ocean waves for MASW inversion of shear-wave velocity is not well-documented compared to active seismic sources.
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The purpose of this study is to (1) demonstrate that ocean energy is a viable seismic source for MASW measurements of shear-wave velocity, using a sea-cliff site with strong ocean waves
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(and wind); (2) show the influence of recording array orientation (i.e., parallel and perpendicular
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to the cliff face along which the ocean waves break); (3) invert phase velocity dispersion to
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derive a shear-wave velocity model verified by outcrop and previous geophysical observations.
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The study site is located along a remote coast of the Kohala Peninsula of the Big Island of Hawaiʻi (Fig. 1), where the trade winds are strong year-round. The site provides an ideal
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laboratory to assess the influence of ocean energy for passive MASW far away from human-
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induced seismic noise. Our study confirms the utility of ocean waves as an ideal source for surface-wave-derived shallow shear-wave velocity measurements, along with examining the
source.
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sensitivity of recording array orientation, recording time, and combining an active with a passive
GEOLOGICAL AND GEOPHYSICAL SETTING The rocks of the Kohala promontory at the study site are weathered Pololu tholeiitic basalt lavas, 0.303 Ma old (Sowards et al., 2018; see also Sherrod et al., 2007). These rocks, and their weathered products, are exposed in a prominent 15-to-20-m high sea cliff, flanked by a broad, mostly flat headland to the south, which provides the platform for our seismic recordings. The
Journal Pre-proof sea cliff juts northeastward into the ocean and is flanked by Hapuu Bay to the west (Fig. 1). The headland shelters the bay from ocean waves and trade winds arriving from the northeast (Stopa et al., 2011). Because the Pololu basalts erupted from the oldest of the five shield volcanoes on the Big Island, they have the thickest weathering profile and therefore the thickest low-velocity critical zone (Chadwick et al., 2003). Further, since the rocks beneath the study site are all chemically similar tholeiitic basalt, any variation in elastic parameters is largely a function of
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chemical and mechanical weathering, along with textural variation (e.g., a’a versus pahoehoe
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flows) (Yaede et al., 2015; Sowards et al., 2018). The sea cliff is mostly vertical except for a
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small seaward-sloping ledge near the top, composed of weak soil. The material exposed in the
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cliff is saprolite derived from a’a flows, pahoehoe lava, and other volcanic products (Sowards et al., 2018) (Fig. 2). Beneath the uppermost weak soil layer is a relatively stiff layer with high
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gibbsite abundance (Sowards et al., 2018). At the base of the cliff, a prominent wave-cut
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platform exposes basalt dikes and relatively fresh, hard lava (Fig. 2). In summary, we have a thick zone of mechanically weak (thus low-seismic velocity) weathered basaltic rock with
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occasional core stones (spheroidal and less weathered remnants within a deeply weathered
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section), overlying stiff, relatively unweathered basaltic rock. The northeast margin of the Kohala Peninsula bears the full brunt of the trade winds and presents an outstanding site for studying the influence of wind and sea waves as a passive seismic source. The Kohala region has been described as having one of the best wind energy resources in the USA (Ramage, 1979; Schroeder, 1981). At our site, strong waves arrive from the northeast, breaking along the southeast-trending headland (Fig. 1). The nearest busy paved highway (Akoni Pule Highway) is about 1.6 km to the southwest, no electrical installations or houses were located near the site, and pedestrian traffic is very light, all of which means that the
Journal Pre-proof primary source of vibration is the breaking of waves against the sea cliffs and similarly directed wind. The ground surface immediately adjacent to the sea cliffs is mostly clear with a few trees, bushes, and short grass. METHODOLOGY Two linear arrays of geophones were initially deployed for passive recording, one parallel
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(BIH-2) to the trend of the sea cliff and one perpendicular (BIH-3) to it (Fig. 1). The parallel
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array (BIH-2) was located roughly 100 m away from the northeast-facing sea cliff in order to
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reduce the effect of breaking wave energy as a systematic arrival with an infinite (or very high) apparent velocity, broadside along the array. The southeastern end of this array is directly in line
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with wave energy propagating from ocean waves impinging the east-facing sea cliff, which is
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located a relatively long distance away, about 360 m southeast of the array (Fig. 1). We deployed 72 recording channels with 4.5-Hz vertical geophones and no field frequency filters.
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The record length and sample rate were 60 s and 4 ms, respectively. The records were also
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collected at 30 s record length and 2 ms sample rate. A geophone spacing of 1.52 m (5 ft) was
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chosen to provide a shallow minimum depth of investigation and with spatial sampling consistent with the thickness of the low-velocity saprolite (e.g., Wubda et al., 2017), as observed in the sea cliff. This provides an array length of 109.7 m (360 ft). The recording commenced with manual triggering and no artificial seismic source (“passive” only).
Multiple records
(usually five) were made for each experiment and stacked in the velocity-frequency domain during the inversion procedure. The geophone array perpendicular to the sea cliffs (BIH-3) was deployed with the same acquisition parameters, but with only 66 channels, due to private property limitations. The array
Journal Pre-proof length was 100.6 m (330 ft). The northeastern end of this array was located 10.7 m (35 ft) from the cliff edge (Fig. 1). The southwestern end of the array intersected the parallel array (BIH-2) as shown in Figure 1. For the perpendicular array, we produced two versions of each recording, one with a hammer strike (10 lb (4.5 kg)) on an aluminum plate that triggered the onset of the recording (combined “passive-active” (Park et al., 2005; Onnis et al., 2019)) and one with manual triggering (“passive” only) (e.g., Pang et al., 2019; Zhou et al., 2018). The hammer
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strike was located in line with the geophone array at the edge of the sea cliff, 10.7 m (35 ft)
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northeast of the first geophone, so as to have a wave propagation direction approximately equal
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to that of the breaking waves. Note that no hammer strike was used for the parallel array (BIH-
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2) since the wave propagation direction from a hammer strike would have been approximately 90° to that of the ocean wave energy arriving from the northeast-facing sea cliff and thus would
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have interfered with the design of the experiment (Fig. 1). These seismic data were recorded
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over a two-day period in July, 2015, during which time we observed strong wind and wave action arriving from the north and east, with high surf conditions. No appreciable ocean waves
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were observed arriving along the western boundary of the headland in Hapuu Bay, 135 m west of
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the western end of BIH-2 (Fig. 1).
As a check on the repeatability of our initial observations, we redeployed a recording array (BIH-4; Fig. 1) in August, 2017 with the same parameters as for BIH-3 (except 64 recording channels instead of 66, due to private property limitations). BIH-4 was shifted about 35 m east of BIH-3, keeping the distance from the sea cliff edge about constant. As can be seen from the location map (Fig. 1), the northeast end of BIH-4 is a little closer to breaking waves at the base of the cliff.
Journal Pre-proof RESULTS AND INTERPRETATION We display our results with seismic recordings (Fig. 3), frequency-wavenumber (f-k) spectra (Fig. 4), dispersion spectra (phase velocity as a function of frequency) (Figs. 5-7), as well as shear-wave modeling results for verification (Fig. 8). The recordings provide a general view of the raw data, the f-k spectra indicate directions of arriving seismic energy, and the dispersion
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spectra indicate the quality of the transformation from the time-offset distance domain to the
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phase velocity-frequency domain.
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Frequency-wavenumber (f-k) spectra. F-k spectra (Yilmaz, 2001) were computed for passive recordings, with and without a hammer strike, along geophone arrays parallel (BIH-2) and
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perpendicular (BIH-3) to the northeast-facing sea cliff (Fig. 1). Records for BIH-3 with a strike
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(combined passive-active source) have f-k spectra (Fig. 4a) with readily identifiable apparent velocity trends propagating along the array (increasing channel number is the positive signed
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direction). These include a high-apparent velocity trend and a low-apparent velocity trend (Fig.
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4a). Higher-apparent velocities correspond to body-wave arrivals (refractions, diving waves, and
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reflections) and/or higher-mode surface waves, whereas lower-apparent velocities correspond to the fundamental mode surface waves visible on the field records (Fig. 3a, b, c), as evidenced by their dispersive (i.e., “shingled” arrivals) character. A directional dependence in the positive direction is obvious on the f-k spectra (Fig. 4a). The BIH-3 records with a hammer strike (combined passive-active source) provide a baseline observation of what trends can be identified as active-source Rayleigh waves arriving perpendicular to the northeast-facing sea cliff. F-k spectra along the same BIH-3 recording array, but with no hammer strike (completely passive source), show a similar positive, but weaker, directional dependence (i.e., inland-
Journal Pre-proof directed), but with less amplitude and with no conspicuous high-apparent velocity trends (Fig. 4b). The difference between positive and negative apparent velocity directions for these records is obviously not as prominent as on the combined passive-active source records (Fig. 4a). Although it remains possible that arrivals with a negative apparent velocity could originate from the nearest main paved highway (Akoni Pule Highway), 1.6 km distant, we believe natural sound sources dominate the records due to the site location being much nearer the sea cliffs (or due to
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backscattered energy). Because the expression of the lower apparent-velocity trend on the
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passive-source spectra (Fig. 4b) is similar to that on the combined passive-active spectra
Since there was no hammer strike for these records, ocean waves
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mode surface waves.
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identifiable as Rayleigh waves (Fig. 4a), we interpret this trend as originating from fundamental
impinging the cliff face are interpreted to be the sole energy source. We note that on both the
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passive-only and combined passive-active records for BIH-3, low-apparent velocity inland-
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propagating arrivals (i.e., positive wavenumber) predominate (Fig. 3), which is consistent with
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the interpretation of ocean waves as the energy source. Along the passive recording array, oriented parallel to the northeast-facing sea cliff (BIH-2,
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Fig. 1), there is also a positive directional dependence on the f-k spectra (Fig. 4c), propagating from east to west; however, the dependence of the amplitude on direction is less prominent, compared to the passive recording on the array perpendicular to the cliff (BIH-3, Fig. 4b). Ocean wave energy propagating from the east-facing sea cliff must travel a relatively significant distance (~360 m) in order to be recorded in-line along the array. Thus, we do not expect in-linedirected wave energy to be as strong as that received along array BIH-3, from the northeastfacing cliff. This is consistent with the observation from the BIH-2 field records of a mix of
Journal Pre-proof positive (in-line, “dipping” down the BIH-2 array) arrivals and negative (up-line) arrivals (Fig. 3c), but with the former dominating. In summary, the f-k spectra indicate that the passive seismic records are affected by energy directed in a manner consistent with ocean waves breaking on nearby headlands, but somewhat more strongly on those records from the perpendicular array, closest to sea cliffs. The ability to
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detect directed ocean wave energy on the passive records, with a preference for orientation of the array with respect to the trend of sea cliff, implies a directional sensitivity for computation of
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dispersion relationships for surface wave energy and the ability to extract shear-wave velocity
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information. In view of the focus of this study on linear arrays to detect a directional dependence
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for the energy source (in this case, ocean waves breaking along a sea cliff), the assumption that a
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linear array of receivers can accurately sample arriving surface waves, whose source is not well known, remains somewhat controversial (e.g., for the ReMi method (Louie, 2001)). This topic
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of "offline-slant-angle" propagation of surface waves being included in the conventional linear For example, one of the fundamental
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array is well discussed in Park and Miller (2008).
assumptions of the ReMi method that has been under scrutiny relates to the omnidirectional
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distribution of surface-wave sources. However, our study is not related to this aspect of the source, but related to the optimum orientation of a linear array recording a unidirectional surface wave source. Phase velocity vs. frequency (dispersion) spectra. Dispersion spectra, depicting phase velocity as a function of frequency (Park et al., 2004; Park, 2008), were computed for both combined passive-active and passive source records, parallel (BIH-2) and perpendicular (BIH-3) to the northeast-facing sea cliff (Fig. 1). The spectra show a well-defined dispersion relationship within the frequency range of 5 to 20 Hz, interpreted to express fundamental-mode Rayleigh
Journal Pre-proof waves (Fig. 5). The spectra indicate the effect of the orientation of the recording array with respect to the trend of the northeast-facing sea cliff. Spectra from the parallel array (BIH-2) show a response up to almost 10 Hz, but with poor continuity in the dispersion relation down to lower frequencies (Fig. 5b). On the other hand, spectra from the perpendicular array (BIH-3) provide a broader and more continuous dispersion relation, with a frequency response extending to 14 Hz (Fig. 5d). The definition of the spectra for frequencies less than about 9 Hz is also
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improved for the perpendicular array (cf. Figs. 5a, b and 5 c, d).
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As a check on the repeatability of the purely passive 60-s dispersion curves, we also
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computed dispersion spectra for the 30-s passive records (2 ms instead of 4 ms sample rate)
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(Figs. 5a and 5c). One might possibly expect some difference between a 30-s and a 60-s record
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due to the integration of more diverse wave energy with increasing listening time. For BIH-2 and BIH-3 passive arrays, there was little difference in the spectra above 6 Hz between different
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record lengths or sample rates (Fig. 5). For example, the start and end points of the fundamental-
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mode dispersion curves interpreted from both images in Figures 6a and 6b are almost identical to 6 Hz and 17 Hz, respectively. On the other hand, comparing the 30-s to the 60-s spectra for the
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passive-active recordings (Figs. 6a and 6b, respectively), the latter are easier interpret between 5 and 10 Hz (clearer dominant dispersion peak). This is also confirmed by comparing the 30-s and 60-s versions for the passive-only spectra (Fig. 5). Spectra for the combined passive-active data from BIH-3 (perpendicular array, Fig. 6) display an extension of the dispersion curve, from 14 Hz up to 18 Hz relative to the passive records (Figs. 5c and 5d).
This demonstrates the repeatability of the passive dispersion
relationships, in that the spectra for each are very similar except for the extension of the higher-
Journal Pre-proof frequency fundamental mode component (Fig. 6). Note that a stronger higher mode appears in the BIH-3 passive-active spectra (Fig. 6), relative to the purely passive versions (Fig. 5). Lastly, since BIH-2 was recorded with 72 channels and BIH-3 was recorded with only 66 channels, we re-computed BIH-2 with only 66 channels in order to afford a more robust comparison and found no appreciable difference in the spectra.
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Repeatability of dispersion spectral observations. The purely passive and combined passive-
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active results from the BIH-4 array (parallel to and offset from BIH-3 by 35 m; Fig. 7) show
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spectra similar to those for the 60-s passive and passive-active records for BIH-3 (cf. Figs. 5 and
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6 with Fig. 7).
Inversion of dispersion curve for shear-wave velocity modeling. In order to evaluate the surface-
Shear-wave velocity is a standard inversion target for modeling surface-wave
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inversion.
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wave results, we chose subsurface shear-wave velocity as the target parameter of geophysical
dispersion (Xia et al., 1999; Xia et al., 2012; Dal Moro, G., 2015; Dumont et al., 2017;
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Karabulut, 2018; Bajaj and Anbazhagan, 2019) and thus provides a useful parameter for
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evaluation. One-dimensional (1D) inversion was performed using the results derived in this study compared with previously published two-dimensional (2D) inversion from the same area. Data processing and inverse modeling were performed using ParkSEIS (Park, 2019). The optimization algorithms and necessary equations, upon which the inversion procedure is based, can be found in Park et al. (1999), Xia et al. (1999), Ryden and Park (2006), Park (2011), and Olafsdottir et al. (2018). Specifically, the inversion algorithm is based on the most common surface-wave inversion scheme, which optimizes each layer velocity based on examination of the Jacobian matrix as exemplified in Xia et al. (1999).
Journal Pre-proof We began our comparison by extracting a dispersion curve from the version of the BIH-3 spectra with the most complete frequency range (60-s, passive-active, Fig. 6; Fig. 8a), then inverting to derive a one-dimensional (1D) shear-wave velocity model (Park, 2003; Park, 2013) (Fig. 8b). Results from the model were then compared with the saprolite thickness observed in the sea-cliff geological outcrop (Fig. 2) and with previous conventional 2D roll-along MASW results (Fig. 8b) (Sowards et al., 2018). The initial 1D velocity profile was obtained through the
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normal automatic inversion method based on the optimization algorithm given in Xia et al.
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(1999). The velocity of each layer was then iteratively adjusted to obtain an improved match
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between the modeled and measured dispersion curves. The resulting 1D velocity model (Fig. 8b)
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depicts a depth-trend and range of values typical for weathered basaltic lavas (e.g., on Oahu, Yaede et al. (2015)). The function shows a low-velocity zone (175-210 m/s) just beneath the
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ground surface, underlain by a 2.5-m thick high velocity zone (~775 m/s) that approximately
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matches the observed stiff, gibbsite layer in outcrop (Sowards et al., 2018), which is then underlain by a second, thick low-velocity zone (~325 m/s). The base of this latter zone is
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defined by a jump back up to about 650 m/s, below which velocities then gradually increase
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down to the base of the model in a manner typical for unweathered Hawaiian and other tholeiitic basalts (Wong et al., 2011; Yaede et al., 2015). Yaede et al. (2015) derived a typical value of 500 m/s for the onset of unweathered basalt beneath a zone of (weathered) saprolite. This was based on correlating MASW-derived 2D shear-wave velocity models to the thickness of mechanically weak saprolite over basalt observed from logged drill holes and outcrops. Applying this relationship to our results (Fig. 8b), we conclude that the onset of unweathered basalt is at about 17 m, which is within the 15-20-m thickness range of the weathered zone at the sea cliff outcrop (Fig. 2). The velocity model also is
Journal Pre-proof qualitatively consistent with the higher-resolution 2D roll-along MASW results (Fig. 8b) obtained along the line of the BIH-2 array (Sowards et al., 2018), including the shallow velocity inversion and the depth to the base of the weathered zone, marked by the onset of increasing shear-wave velocity beginning at 500 m/s. The pattern of the velocity variation is similar between the two methods, including the depth to the onset of velocities higher than 500 m/s, although the maximum velocity values for the passive 1D experiment are somewhat higher than
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those for the 2D MASW results. In particular, the higher resolution (but shallower investigation)
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2D and the lower-resolution (but deeper investigation) 1D results (Fig. 8b) show a similar
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arrangement of high and low velocity layers, but with somewhat varying thicknesses and
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velocities. The variation in the velocity models could express either differing levels of resolution between the two methods or geological variation within what are otherwise laterally continuous
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layers in the saprolite, considering that the two models are not exactly co-located (Fig. 1).
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We remark that the spectra for the combined passive-active records from the BIH-3 array
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show a prominent mode (Fig. 6), relative to the passive-only spectra (Fig. 5). Further inverse modeling could be performed to jointly derive a velocity model using both fundamental and
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higher mode surface waves (Luo et al., 2007). Using a multi-mode inversion could improve the accuracy of the model results for deeper layers (Luo et al., 2007). SUMMARY AND CONCLUSIONS We demonstrate the ability of ocean waves impinging a headland to produce surface-wave dispersion curves that can be inverted for shear-wave velocity models. Ocean waves are well known for their low-frequency contribution to ambient noise. This study illustrates their value down into the traditional microtremor range (≥1 Hz). Our sea cliff site provides an ideal natural
Journal Pre-proof laboratory for testing the correspondence of the shear-wave modeling results with known lithologic and mechanical strength properties of the shallow subsurface (i.e., the soft saprolite over hard basalt bedrock from which the former is derived). F-k analysis helps to constrain the interpretation of the influence and directionality of ocean wave energy. As expected, there can be a strong dependence of the array orientation with respect to the shoreline on the completeness of the dispersion spectra. The recording array oriented perpendicular to the sea cliff furnished
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the best spectra, with a higher frequency response and an improved definition for the lower Adding an active source to the passive recordings further extended the Spectra quality was unaffected by record lengths or sample rates for
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frequency response.
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frequency range.
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frequencies higher than about 10 Hz; however, spectra for the 60-s passive records had improved
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definition between 5 and 10 Hz.
In general, inclusion of an active source in any type of surface-wave survey is advantageous.
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Using only a passive survey may not be adequate for a broad enough depth coverage--this being
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especially true where no ambient noise (e.g., wind, vehicle traffic, etc.) is present. Nevertheless, an active survey usually generates surface waves in frequencies higher than 10 Hz that sample
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relatively shallow depths (e.g., ≤ 20 m), while a passive survey can provide the lower frequencies for greater depths. Thus, a mix of active and strong passive (e.g., ocean waves) sources is optimal. We verified the quality of the spectra by modeling dispersion curves extracted from them and comparing the results with outcrop in the adjacent sea cliff, which extends all the way down to stiff and unweathered basalt lava bedrock, and with previous 2D modeling. When combined with an active triggering source and an array oriented perpendicular to the shore, passive sources provide an easy and unobtrusive way to obtain the thickness of a saprolite overburden, developed
Journal Pre-proof from chemical weathering of basalt. Our analysis does not reveal any specific features of an ocean-wave source that makes it an improvement over traditional vehicle traffic noise, except that the frequency of wave impacts along a cliff face compares favorably with a light-duty road with infrequent traffic (e.g., one vehicle per 5 minutes). An ocean-wave source can be utilized to good effect when vehicle traffic is light, sporadic, or too far distant.
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Acknowledgments This research was supported in part by funding from the College of Physical and
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Mathematical Sciences at Brigham Young University. The displays of records and the f-k
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analysis were made possible by a generous software grant from the Landmark (Halliburton)
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University Grant Program. Inverse modeling was performed using ParkSEIS software. The final
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version of the paper was greatly improved by comments and recommendations from three
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journal reviewers.
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Journal Pre-proof Luo, Y., Xia, J., Liu, J., Liu, Q., and Xu, S., 2007, Joint inversion of high-frequency surface waves with fundamental and higher modes, Journal of Applied Geophysics v. 62, p. 375– 384, doi:10.1016/j.jappgeo.2007.02.004. Morton, S. L. C., Peterie, S., Livers, A., Ivanov, J., and Miller, R. D., 2015, Advantages and disadvantages of passive Multichannel Analysis of Surface Waves (MASW) for observing subsurface discontinuities, American Geophysical Union, Fall Meeting 2015, abstract id. NS41A-1921.
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Onnis, L. E., Osella, A., and Carcione, J. M., 2019, Retrieving shallow shear-wave velocity profiles from 2D seismic-reflection data with severely aliased surface waves, Journal of Applied Geophysics, v. 161, p. 15–25, doi.org/10.1016/j.jappgeo.2018.11.014.
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Pamuk, E., Akgün, M., Özdağ. Ö. C., and Gönenç, T., 2017, 2D soil and engineering-seismic bedrock modeling of eastern part of Izmir inner bay/Turkey, Journal of Applied Geophysics, v. 137, p. 104–117, dx.doi.org/10.1016/j.jappgeo.2016.12.016.
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Pang, J., Cheng, F., Shen, C., Dai, T., Ning, L., and Zhang, K., 2019, Automatic passive data selection in time domain for imaging near-surface surface waves, Journal of Applied Geophysics, v. 162, 108–117. Park, C.B., 2003, SurfSeis: MASW Data Processing Software published from Kansas Geological Survey, University of Kansas, Lawrence, Kansas. Park, C.B., 2011, Imaging dispersion of MASW data—full vs. selective offset scheme, Journal of Environmental and Engineering Geophysics, v. 16, p. 13-23. Park, C., 2013, MASW for geotechnical site investigation: The Leading Edge, v. 32, p. 656-662. Park, C. B., 2008, Imaging dispersion of passive surface waves with active scheme: Symposium on the Application of Geophysics to Engineering and Environmental Problems, Philadelphia, April 6-10, 2008, Proceedings on CD Rom.
Journal Pre-proof Park, C. B., ParkSEIS, http://www.parkseismic.com/, accessed February, 2019. Park, C. B. and Miller, R. D., 2008, Roadside passive multi-channel analysis of surface waves (MASW): Journal of Environmental and Engineering Geophysics, v. 13, p. 1–11. Park, C. B., Miller, R. D., Ryden, N., Xia, J., and Ivanov, J., 2005, Combined use of active and passive surface waves: Journal of Environmental and Engineering Geophysics, v. 10, p. 323334. Park, C. B., Miller, R. D., and Xia J., 1999, Multichannel analysis of surface waves MASW: Geophysics, v. 64, p. 800–808.
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Ramage, C. S., 1979, Prospecting for meteorological energy in Hawaii: Bulletin of the American Meteorological Society, v. 60, p. 430-438.
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Schroeder, T. A., 1981, Characteristics of local winds in Northwest Hawaii: Journal of Applied Meteorology, v. 20, p. 874-881. Sherrod, D. R., Sinton, J. M., Watkins, S. E., and Brunt, K. M., 2007, Geologic map of the State of Hawai`i: U.S. Geological Survey Open-File Report 2007-1089 pubs.usgs.gov/of/2007/1089. Sivaram, K., Gupta, S., Kumar, S., and Prasad, B. N. V., 2018, Shear velocity structural characterization around the Lonar crater using joint inversion of ambient noise HVSR and Rayleigh wave dispersion, Journal of Applied Geophysics, v. 159, p. 773–784, doi.org/10.1016/j.jappgeo.2018.10.022. Sowards, K., Nelson, S., McBride, J., Bickmore, B., Heizler, M., Tingey, D., Rey, K., and Yaede, J., A conceptual model for the rapid weathering of tropical ocean islands: A synthesis
Journal Pre-proof of geochemistry and geophysics, Kohala Peninsula, Hawaii, USA: Geosphere, v. 14, no. 3, p. 1–3, doi .org/10 .1130 /GES01642.1. Stephenson, W. J., Louie, J. N., Pullammanappallil, S, Williams, R. A, and Odum, J. K., 2005, Blind shear-wave velocity comparison of REMI and MASW results with boreholes to 200 m in Santa Clara Valley: Implications for Earthquake Ground-Motion Assessment, Bulletin of the Seismological Society of America, v. 95, p. 2506–2516. doi.org/10.1785/0120040240. Stopa, J. E., Cheung, K. F., and Chen, Y.-L., 2011, Assessment of wave energy resources in Hawaii, Renewable Energy, v. 36, p. 554-567.
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Wong, I. G., Stokoe, K. H., Cox, B. R., Yuan, J., Knudsen, K. L., Terra, F., Okubo, P., and Lin, Y., 2011, Shear-wave velocity characterization of the USGS Hawaiian strong-motion network on the island of Hawaii and development of an NEHRP site-class map, Bulletin of the Seismological Society of America, v. 101, p. 2252–2269.
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Yaede, J. R., McBride, J. H., Nelson, S. T., Park, C. B., Flores, J. A., Turnbull, S. J., Tingey, D. G., Jacobsen, R. T., Dong, C. D., and Gardner, N. L., 2015, A geophysical strategy for measuring the thickness of the critical zone developed over basalt lavas, Geosphere, v. 11, p. 514-532, doi:10.1130/GES01142.1.
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Xia, J., Miller, R. D., and Park, C. B., 1999, Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves, Geophysics, v. 64, p. 691-700.
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Xia, J., Miller, R. D., Park, C. B., Hunter, J. A., and Harris, J. B., 2012, Comparing Shear-Wave Velocity Profiles from MASW with Borehole Measurements in Unconsolidated Sediments, Fraser River Delta, B.C., Canada, Journal of Environmental and Engineering Geophysics, v. 5, p. 1-13. Yilmaz, O., 2001, Seismic Data Analysis. Society of Exploration Geophysicists, Tulsa, U.S.A. Yong, A., Martin, A., Stokoe, K., and Diehl, J., 2013, ARRA-funded VS30 measurements using multi-technique approach at strong-motion stations in California and central-eastern United States: U.S. Geological Survey Open-File Report 2013–1102, 59 p. and data files, pubs.usgs.gov/of/2013/1102/. Zhou, C., Xi, C., Pang, J., and Liu, Y., 2018, Ambient noise data selection based on the asymmetry of crosscorrelation functions for near surface applications, Journal of Applied Geophysics, v. 159, 803–813, doi.org/10.1016/j.jappgeo.2018.09.033.
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FIGURES
Figure 1. Location maps of study site, Kohala Peninsula, Big Island of Hawaiʻi. Map on the bottom shows close-up of study site with three recording arrays (BIH-2, 3, 4), along with beginning and ending channel numbers for each. The usual direction of trade winds (blue arrow) is from Stopa et al. (2011).
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Figure 2. Photo of sea cliff at the study site showing the thick saprolite layer (double arrow) over relatively unweathered basalt lava platform at sea level. Note that the thickness of the weathered zone is variable, but ranges between 15 and 20 m. View is looking southeast, taken down and to the northwest from the beginning of BIH-3 (Fig. 1). Photo by J. H. McBride.
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Figure 3. (a) Excerpt of field record for BIH-3 combined passive-active source array. The interpreted parts of wave field are noted. Seismic data displayed as variable density (grayscale) (top row) and as variable area wiggle trace (bottom row). Amplitude scale is referenced to the last trace on each individual record. Recording time is 60 s. (b) Same as in (a), but for the passive-only source array. Arrows indicate examples of ocean-wave impact arrivals. (c) Same as in (b), but for BIH-2 array, showing interpreted mixed ocean-wave arrivals (arrows indicate examples) from approximately 360 m to the east (as inclined events) and from approximately 100 m to the north (as flatter events). See Figure 1 for location. Note that increasing channel number, from northeast to southwest, is the positive signed direction for BIH-3 and from southeast to northwest for BIH-2.
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Figure 4. (a) Frequency-wavenumber (f-k) spectrum for a typical field record from the combined passive-active BIH-3 array (60-s record). Hot colors are high amplitude, cold colors are low amplitude (a color relative amplitude scale is shown). The regions of low-apparent velocity (dominated by surface waves from the hammer strike) and high-apparent velocity (dominated by body waves from the hammer strike) are noted. Examples of two apparent velocities are shown for reference. (b) Same as in (a), but for passive only BIH-3 array. Spectrum is dominated by ocean waves arriving mainly from the northeast, along the nearest shoreline. (c) Same as in (b), but from the BIH-2 passive array. High-amplitude response is dominated by distant ocean-wave arrivals from the southeast (lower apparent velocities) and approximately broadside from the northeast (higher apparent velocities). Note that backscattered events occur in the passive spectra (negative wavenumbers).
Figure 5. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for purely passive 30-s record (sample rate, 2 ms) from BIH-2. (b) Same as in (a), but for 60-s record (sample rate, 4 ms). (c) Same as in (a), but for BIH-3 array. (d) Same as in (b), for BIH-3 array. See Figure 1 for location of arrays.
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Figure 6. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for combined passive-active records from the BIH-3 array for 30-s record length (sample rate, 2 ms). Note the stronger higher mode, relative to the purely passive versions (Fig. 5). (b) Same as in (a), but for 60-s record length (sample rate, 4 ms) (compare with purely passive spectra for BIH-3 in Figures 5c, d).
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Figure 7. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for passive record from the BIH-4 array (parallel to and offset from BIH-3 by 35 m) with a 60-s record length (sample rate, 4 ms) (compare with spectra for BIH-3 in Figure 5d). (b) Same as in (a), but for combined passive-active record (compare with spectra for BIH-3 in Figure 6b).
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Figure 8. (a) Dispersion curve extracted from BIH-3 passive-active recording (Fig. 6a) along with the signal-to-noise-ratio (S/N). The S/N curve indicates the amplitude ratio for each particular frequency in comparison to all other possible modes. For example, S/N=1.0 at 10 Hz means the fundamental mode accounts for 100% of measured seismic waves. On the other hand, S/N=0.5 at 10 Hz means the measured fundamental mode surface wave at 10 Hz takes up 50% of the total seismic amplitude at 10 Hz—the remaining amplitude (i.e., another 50%) can be either noise or other modes (e.g., higher modes or body waves).
Figure 8 (b) Extracted and final modeled dispersion curves from BIH-3 passive-active recording (Fig. 6a). Compare with Figure 8a.
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Figure 8 (c) Left, Excerpt of two-dimensional (2D) shear-wave velocity model obtained by Sowards et al. (2018) near middle of BIH-2 (Fig. 1) based on a moving-source roll-along technique. See Sowards et al. (2018) for details of seismic data acquisition and modeling. Right, One-dimensional shear-wave velocity-depth function, based on modeling the dispersion spectrum from the BIH-3, 60-s combined passive-active record (Fig. 8b). The onset of increasing velocity with depth, beginning at 500 m/s, is at a depth of about 17 m, which is just above the depth to rigid basalt bedrock as exposed in the face of the nearby sea cliff (Fig. 2) and derived independently in the 2D velocity model shown.
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Highlights We demonstrate how ocean waves can be used as a passive seismic source Directionality of the recording array affects quality of dispersion function Example results are tested against geologic outcrop and previous velocity modeling
John H. McBride, Stephen T. Nelson, Choon B. Park, Eugene E. Wolfe, David G. Tingey, Kevin A. Rey PII:
S0926-9851(19)30222-8
DOI:
https://doi.org/10.1016/j.jappgeo.2019.103860
Reference:
APPGEO 103860
To appear in:
Journal of Applied Geophysics
Received date:
13 March 2019
Revised date:
11 September 2019
Accepted date:
19 September 2019
Please cite this article as: J.H. McBride, S.T. Nelson, C.B. Park, et al., Ocean waves as a passive MASW source, Journal of Applied Geophysics(2019), https://doi.org/10.1016/ j.jappgeo.2019.103860
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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.
© 2019 Published by Elsevier.
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Ocean Waves as a Passive MASW Source
John H. McBride1,* [email protected], Stephen T. Nelson1, Choon B. Park2, Eugene E. Wolfe3, David G. Tingey1, and Kevin A. Rey1 1
Department of Geological Sciences, Brigham Young University, Provo, Utah 84602 USA Park Seismic LLC, 2 Balsam Circle, Shelton, Connecticut 06484 USA 3 Halliburton Software and Asset Solutions, 1805 Shea Center Drive Suite 400, Highlands Ranch, Colorado 80129 USA * Corresponding author.
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Journal Pre-proof ABSTRACT Ocean waves have been considered to be a source of seismic surface-wave energy for subsurface exploration. We test the utility of ocean-source seismic recording, the sensitivity to array orientation with respect to the shoreline direction, and the equivalence of passive- and active-source data acquired in a near-shore environment. The Kohala peninsula of northwestern Hawaiʻi (Big Island), with its exposure to strong trade winds and prominent rock and soil
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outcrops along sea cliffs, provides an ideal natural laboratory to study ocean noise as a passive
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seismic source. The results show that passive-source data recorded from ocean waves over a prominent headland in Kohala produce coherent surface-wave dispersion relationships (phase
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velocity as a function of frequency) that can be modeled for shear-wave velocity in the shallow We also demonstrate the
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subsurface, especially when combined with active-source data.
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dependence of the array orientation on the quality of the dispersion spectra—an array perpendicular to the shoreline produces a more complete frequency range and higher coherency,
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relative to an array oriented parallel to the shoreline. Previous geophysical investigations of the
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site, constrained by the geologic outcrop along the adjacent sea cliff, confirm the utility of the shear-wave velocity-depth modeling based on our recordings. Ocean waves can be used for
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modeling of shear-wave velocity in the upper 10-50 m of the subsurface with a relatively short array, but can be improved by combining active and passive sources and by orienting the array parallel to the direction of ocean-wave propagation.
Journal Pre-proof INTRODUCTION Surface wave dispersion has been used to measure shear-wave velocity structure of the shallow subsurface for at least the past 20 years (Park et al., 1999). These measurements aid geotechnical evaluations of construction or urban sites (Penumadu and Park, 2005; Park, 2013; Bekler et al., 2019) and constrain geological investigation of the critical zone (i.e., the shallow layer of the earth where plant and animal life, groundwater, and soils and weathered bedrock
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interact) (Parsekian et al., 2015). Active-source Multi-Channel Analysis of Survey Waves
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(MASW) and active-source Spectral Analysis of Surface Waves (SASW) are commonly used to
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obtain shear-wave velocity structure in the upper 30 m of the earth or deeper (Park et al., 1999; Lin et al., 2017). Passive-source techniques, such as Refraction Microtremor (ReMi) (Louie,
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2001; Stephenson et al., 2005; Dumont et al., 2017; Pamuk et al., 2017; Karabulut, 2018), and
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H/V Spectral Ratio (HVSR) (Nakamura, 1989; Sivaram et al., 2018), have also been developed
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for deeper investigations or for sites where an active seismic source (e.g., hammers and strike plates, weight droppers, vibrators) is impractical. Active- and passive-source techniques (Lontsi
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et al., 2016; Bajaj et al., 2019; Onnis et al., 2019) complement each other as to their advantages
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and disadvantages, the former being better suited for high-frequency, high-resolution, but shallower investigation and the latter for low-frequency, lower-resolution, but deeper investigation (given identical parameters of geophone resonant frequency, channel spacing, etc.) (Morton et al., 2015). The seismic source for MASW passive methods can be background “noise” (or microseisms) caused by industrial activities, road traffic, wind (atmospheric pressure variations), or ocean waves. Roughly speaking, seismic noise dominated by frequencies greater than 1 Hz is typically considered to be caused by human activity, while noise dominated by frequencies less than 1 Hz is considered to be natural (Okada, 2003; Yong et al., 2013). Thus, natural sources have greater potential for deeper investigation of shear-wave velocity structure
Journal Pre-proof (Park et al., 2004). Perhaps the classic passive seismic source is that emanating from ocean waves, which generate vibrations with frequencies of about 0.14 Hz (Hobiger, 2011) and for which the energy depends on the wave height (Dolenc and Dreger, 2005); however, the behavior of ocean waves for MASW inversion of shear-wave velocity is not well-documented compared to active seismic sources.
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The purpose of this study is to (1) demonstrate that ocean energy is a viable seismic source for MASW measurements of shear-wave velocity, using a sea-cliff site with strong ocean waves
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(and wind); (2) show the influence of recording array orientation (i.e., parallel and perpendicular
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to the cliff face along which the ocean waves break); (3) invert phase velocity dispersion to
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derive a shear-wave velocity model verified by outcrop and previous geophysical observations.
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The study site is located along a remote coast of the Kohala Peninsula of the Big Island of Hawaiʻi (Fig. 1), where the trade winds are strong year-round. The site provides an ideal
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laboratory to assess the influence of ocean energy for passive MASW far away from human-
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induced seismic noise. Our study confirms the utility of ocean waves as an ideal source for surface-wave-derived shallow shear-wave velocity measurements, along with examining the
source.
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sensitivity of recording array orientation, recording time, and combining an active with a passive
GEOLOGICAL AND GEOPHYSICAL SETTING The rocks of the Kohala promontory at the study site are weathered Pololu tholeiitic basalt lavas, 0.303 Ma old (Sowards et al., 2018; see also Sherrod et al., 2007). These rocks, and their weathered products, are exposed in a prominent 15-to-20-m high sea cliff, flanked by a broad, mostly flat headland to the south, which provides the platform for our seismic recordings. The
Journal Pre-proof sea cliff juts northeastward into the ocean and is flanked by Hapuu Bay to the west (Fig. 1). The headland shelters the bay from ocean waves and trade winds arriving from the northeast (Stopa et al., 2011). Because the Pololu basalts erupted from the oldest of the five shield volcanoes on the Big Island, they have the thickest weathering profile and therefore the thickest low-velocity critical zone (Chadwick et al., 2003). Further, since the rocks beneath the study site are all chemically similar tholeiitic basalt, any variation in elastic parameters is largely a function of
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chemical and mechanical weathering, along with textural variation (e.g., a’a versus pahoehoe
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flows) (Yaede et al., 2015; Sowards et al., 2018). The sea cliff is mostly vertical except for a
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small seaward-sloping ledge near the top, composed of weak soil. The material exposed in the
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cliff is saprolite derived from a’a flows, pahoehoe lava, and other volcanic products (Sowards et al., 2018) (Fig. 2). Beneath the uppermost weak soil layer is a relatively stiff layer with high
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gibbsite abundance (Sowards et al., 2018). At the base of the cliff, a prominent wave-cut
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platform exposes basalt dikes and relatively fresh, hard lava (Fig. 2). In summary, we have a thick zone of mechanically weak (thus low-seismic velocity) weathered basaltic rock with
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occasional core stones (spheroidal and less weathered remnants within a deeply weathered
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section), overlying stiff, relatively unweathered basaltic rock. The northeast margin of the Kohala Peninsula bears the full brunt of the trade winds and presents an outstanding site for studying the influence of wind and sea waves as a passive seismic source. The Kohala region has been described as having one of the best wind energy resources in the USA (Ramage, 1979; Schroeder, 1981). At our site, strong waves arrive from the northeast, breaking along the southeast-trending headland (Fig. 1). The nearest busy paved highway (Akoni Pule Highway) is about 1.6 km to the southwest, no electrical installations or houses were located near the site, and pedestrian traffic is very light, all of which means that the
Journal Pre-proof primary source of vibration is the breaking of waves against the sea cliffs and similarly directed wind. The ground surface immediately adjacent to the sea cliffs is mostly clear with a few trees, bushes, and short grass. METHODOLOGY Two linear arrays of geophones were initially deployed for passive recording, one parallel
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(BIH-2) to the trend of the sea cliff and one perpendicular (BIH-3) to it (Fig. 1). The parallel
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array (BIH-2) was located roughly 100 m away from the northeast-facing sea cliff in order to
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reduce the effect of breaking wave energy as a systematic arrival with an infinite (or very high) apparent velocity, broadside along the array. The southeastern end of this array is directly in line
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with wave energy propagating from ocean waves impinging the east-facing sea cliff, which is
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located a relatively long distance away, about 360 m southeast of the array (Fig. 1). We deployed 72 recording channels with 4.5-Hz vertical geophones and no field frequency filters.
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The record length and sample rate were 60 s and 4 ms, respectively. The records were also
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collected at 30 s record length and 2 ms sample rate. A geophone spacing of 1.52 m (5 ft) was
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chosen to provide a shallow minimum depth of investigation and with spatial sampling consistent with the thickness of the low-velocity saprolite (e.g., Wubda et al., 2017), as observed in the sea cliff. This provides an array length of 109.7 m (360 ft). The recording commenced with manual triggering and no artificial seismic source (“passive” only).
Multiple records
(usually five) were made for each experiment and stacked in the velocity-frequency domain during the inversion procedure. The geophone array perpendicular to the sea cliffs (BIH-3) was deployed with the same acquisition parameters, but with only 66 channels, due to private property limitations. The array
Journal Pre-proof length was 100.6 m (330 ft). The northeastern end of this array was located 10.7 m (35 ft) from the cliff edge (Fig. 1). The southwestern end of the array intersected the parallel array (BIH-2) as shown in Figure 1. For the perpendicular array, we produced two versions of each recording, one with a hammer strike (10 lb (4.5 kg)) on an aluminum plate that triggered the onset of the recording (combined “passive-active” (Park et al., 2005; Onnis et al., 2019)) and one with manual triggering (“passive” only) (e.g., Pang et al., 2019; Zhou et al., 2018). The hammer
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strike was located in line with the geophone array at the edge of the sea cliff, 10.7 m (35 ft)
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northeast of the first geophone, so as to have a wave propagation direction approximately equal
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to that of the breaking waves. Note that no hammer strike was used for the parallel array (BIH-
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2) since the wave propagation direction from a hammer strike would have been approximately 90° to that of the ocean wave energy arriving from the northeast-facing sea cliff and thus would
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have interfered with the design of the experiment (Fig. 1). These seismic data were recorded
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over a two-day period in July, 2015, during which time we observed strong wind and wave action arriving from the north and east, with high surf conditions. No appreciable ocean waves
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were observed arriving along the western boundary of the headland in Hapuu Bay, 135 m west of
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the western end of BIH-2 (Fig. 1).
As a check on the repeatability of our initial observations, we redeployed a recording array (BIH-4; Fig. 1) in August, 2017 with the same parameters as for BIH-3 (except 64 recording channels instead of 66, due to private property limitations). BIH-4 was shifted about 35 m east of BIH-3, keeping the distance from the sea cliff edge about constant. As can be seen from the location map (Fig. 1), the northeast end of BIH-4 is a little closer to breaking waves at the base of the cliff.
Journal Pre-proof RESULTS AND INTERPRETATION We display our results with seismic recordings (Fig. 3), frequency-wavenumber (f-k) spectra (Fig. 4), dispersion spectra (phase velocity as a function of frequency) (Figs. 5-7), as well as shear-wave modeling results for verification (Fig. 8). The recordings provide a general view of the raw data, the f-k spectra indicate directions of arriving seismic energy, and the dispersion
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spectra indicate the quality of the transformation from the time-offset distance domain to the
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phase velocity-frequency domain.
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Frequency-wavenumber (f-k) spectra. F-k spectra (Yilmaz, 2001) were computed for passive recordings, with and without a hammer strike, along geophone arrays parallel (BIH-2) and
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perpendicular (BIH-3) to the northeast-facing sea cliff (Fig. 1). Records for BIH-3 with a strike
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(combined passive-active source) have f-k spectra (Fig. 4a) with readily identifiable apparent velocity trends propagating along the array (increasing channel number is the positive signed
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direction). These include a high-apparent velocity trend and a low-apparent velocity trend (Fig.
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4a). Higher-apparent velocities correspond to body-wave arrivals (refractions, diving waves, and
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reflections) and/or higher-mode surface waves, whereas lower-apparent velocities correspond to the fundamental mode surface waves visible on the field records (Fig. 3a, b, c), as evidenced by their dispersive (i.e., “shingled” arrivals) character. A directional dependence in the positive direction is obvious on the f-k spectra (Fig. 4a). The BIH-3 records with a hammer strike (combined passive-active source) provide a baseline observation of what trends can be identified as active-source Rayleigh waves arriving perpendicular to the northeast-facing sea cliff. F-k spectra along the same BIH-3 recording array, but with no hammer strike (completely passive source), show a similar positive, but weaker, directional dependence (i.e., inland-
Journal Pre-proof directed), but with less amplitude and with no conspicuous high-apparent velocity trends (Fig. 4b). The difference between positive and negative apparent velocity directions for these records is obviously not as prominent as on the combined passive-active source records (Fig. 4a). Although it remains possible that arrivals with a negative apparent velocity could originate from the nearest main paved highway (Akoni Pule Highway), 1.6 km distant, we believe natural sound sources dominate the records due to the site location being much nearer the sea cliffs (or due to
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backscattered energy). Because the expression of the lower apparent-velocity trend on the
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passive-source spectra (Fig. 4b) is similar to that on the combined passive-active spectra
Since there was no hammer strike for these records, ocean waves
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mode surface waves.
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identifiable as Rayleigh waves (Fig. 4a), we interpret this trend as originating from fundamental
impinging the cliff face are interpreted to be the sole energy source. We note that on both the
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passive-only and combined passive-active records for BIH-3, low-apparent velocity inland-
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propagating arrivals (i.e., positive wavenumber) predominate (Fig. 3), which is consistent with
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the interpretation of ocean waves as the energy source. Along the passive recording array, oriented parallel to the northeast-facing sea cliff (BIH-2,
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Fig. 1), there is also a positive directional dependence on the f-k spectra (Fig. 4c), propagating from east to west; however, the dependence of the amplitude on direction is less prominent, compared to the passive recording on the array perpendicular to the cliff (BIH-3, Fig. 4b). Ocean wave energy propagating from the east-facing sea cliff must travel a relatively significant distance (~360 m) in order to be recorded in-line along the array. Thus, we do not expect in-linedirected wave energy to be as strong as that received along array BIH-3, from the northeastfacing cliff. This is consistent with the observation from the BIH-2 field records of a mix of
Journal Pre-proof positive (in-line, “dipping” down the BIH-2 array) arrivals and negative (up-line) arrivals (Fig. 3c), but with the former dominating. In summary, the f-k spectra indicate that the passive seismic records are affected by energy directed in a manner consistent with ocean waves breaking on nearby headlands, but somewhat more strongly on those records from the perpendicular array, closest to sea cliffs. The ability to
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detect directed ocean wave energy on the passive records, with a preference for orientation of the array with respect to the trend of sea cliff, implies a directional sensitivity for computation of
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dispersion relationships for surface wave energy and the ability to extract shear-wave velocity
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information. In view of the focus of this study on linear arrays to detect a directional dependence
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for the energy source (in this case, ocean waves breaking along a sea cliff), the assumption that a
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linear array of receivers can accurately sample arriving surface waves, whose source is not well known, remains somewhat controversial (e.g., for the ReMi method (Louie, 2001)). This topic
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of "offline-slant-angle" propagation of surface waves being included in the conventional linear For example, one of the fundamental
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array is well discussed in Park and Miller (2008).
assumptions of the ReMi method that has been under scrutiny relates to the omnidirectional
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distribution of surface-wave sources. However, our study is not related to this aspect of the source, but related to the optimum orientation of a linear array recording a unidirectional surface wave source. Phase velocity vs. frequency (dispersion) spectra. Dispersion spectra, depicting phase velocity as a function of frequency (Park et al., 2004; Park, 2008), were computed for both combined passive-active and passive source records, parallel (BIH-2) and perpendicular (BIH-3) to the northeast-facing sea cliff (Fig. 1). The spectra show a well-defined dispersion relationship within the frequency range of 5 to 20 Hz, interpreted to express fundamental-mode Rayleigh
Journal Pre-proof waves (Fig. 5). The spectra indicate the effect of the orientation of the recording array with respect to the trend of the northeast-facing sea cliff. Spectra from the parallel array (BIH-2) show a response up to almost 10 Hz, but with poor continuity in the dispersion relation down to lower frequencies (Fig. 5b). On the other hand, spectra from the perpendicular array (BIH-3) provide a broader and more continuous dispersion relation, with a frequency response extending to 14 Hz (Fig. 5d). The definition of the spectra for frequencies less than about 9 Hz is also
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improved for the perpendicular array (cf. Figs. 5a, b and 5 c, d).
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As a check on the repeatability of the purely passive 60-s dispersion curves, we also
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computed dispersion spectra for the 30-s passive records (2 ms instead of 4 ms sample rate)
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(Figs. 5a and 5c). One might possibly expect some difference between a 30-s and a 60-s record
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due to the integration of more diverse wave energy with increasing listening time. For BIH-2 and BIH-3 passive arrays, there was little difference in the spectra above 6 Hz between different
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record lengths or sample rates (Fig. 5). For example, the start and end points of the fundamental-
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mode dispersion curves interpreted from both images in Figures 6a and 6b are almost identical to 6 Hz and 17 Hz, respectively. On the other hand, comparing the 30-s to the 60-s spectra for the
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passive-active recordings (Figs. 6a and 6b, respectively), the latter are easier interpret between 5 and 10 Hz (clearer dominant dispersion peak). This is also confirmed by comparing the 30-s and 60-s versions for the passive-only spectra (Fig. 5). Spectra for the combined passive-active data from BIH-3 (perpendicular array, Fig. 6) display an extension of the dispersion curve, from 14 Hz up to 18 Hz relative to the passive records (Figs. 5c and 5d).
This demonstrates the repeatability of the passive dispersion
relationships, in that the spectra for each are very similar except for the extension of the higher-
Journal Pre-proof frequency fundamental mode component (Fig. 6). Note that a stronger higher mode appears in the BIH-3 passive-active spectra (Fig. 6), relative to the purely passive versions (Fig. 5). Lastly, since BIH-2 was recorded with 72 channels and BIH-3 was recorded with only 66 channels, we re-computed BIH-2 with only 66 channels in order to afford a more robust comparison and found no appreciable difference in the spectra.
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Repeatability of dispersion spectral observations. The purely passive and combined passive-
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active results from the BIH-4 array (parallel to and offset from BIH-3 by 35 m; Fig. 7) show
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spectra similar to those for the 60-s passive and passive-active records for BIH-3 (cf. Figs. 5 and
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6 with Fig. 7).
Inversion of dispersion curve for shear-wave velocity modeling. In order to evaluate the surface-
Shear-wave velocity is a standard inversion target for modeling surface-wave
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inversion.
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wave results, we chose subsurface shear-wave velocity as the target parameter of geophysical
dispersion (Xia et al., 1999; Xia et al., 2012; Dal Moro, G., 2015; Dumont et al., 2017;
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Karabulut, 2018; Bajaj and Anbazhagan, 2019) and thus provides a useful parameter for
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evaluation. One-dimensional (1D) inversion was performed using the results derived in this study compared with previously published two-dimensional (2D) inversion from the same area. Data processing and inverse modeling were performed using ParkSEIS (Park, 2019). The optimization algorithms and necessary equations, upon which the inversion procedure is based, can be found in Park et al. (1999), Xia et al. (1999), Ryden and Park (2006), Park (2011), and Olafsdottir et al. (2018). Specifically, the inversion algorithm is based on the most common surface-wave inversion scheme, which optimizes each layer velocity based on examination of the Jacobian matrix as exemplified in Xia et al. (1999).
Journal Pre-proof We began our comparison by extracting a dispersion curve from the version of the BIH-3 spectra with the most complete frequency range (60-s, passive-active, Fig. 6; Fig. 8a), then inverting to derive a one-dimensional (1D) shear-wave velocity model (Park, 2003; Park, 2013) (Fig. 8b). Results from the model were then compared with the saprolite thickness observed in the sea-cliff geological outcrop (Fig. 2) and with previous conventional 2D roll-along MASW results (Fig. 8b) (Sowards et al., 2018). The initial 1D velocity profile was obtained through the
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normal automatic inversion method based on the optimization algorithm given in Xia et al.
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(1999). The velocity of each layer was then iteratively adjusted to obtain an improved match
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between the modeled and measured dispersion curves. The resulting 1D velocity model (Fig. 8b)
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depicts a depth-trend and range of values typical for weathered basaltic lavas (e.g., on Oahu, Yaede et al. (2015)). The function shows a low-velocity zone (175-210 m/s) just beneath the
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ground surface, underlain by a 2.5-m thick high velocity zone (~775 m/s) that approximately
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matches the observed stiff, gibbsite layer in outcrop (Sowards et al., 2018), which is then underlain by a second, thick low-velocity zone (~325 m/s). The base of this latter zone is
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defined by a jump back up to about 650 m/s, below which velocities then gradually increase
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down to the base of the model in a manner typical for unweathered Hawaiian and other tholeiitic basalts (Wong et al., 2011; Yaede et al., 2015). Yaede et al. (2015) derived a typical value of 500 m/s for the onset of unweathered basalt beneath a zone of (weathered) saprolite. This was based on correlating MASW-derived 2D shear-wave velocity models to the thickness of mechanically weak saprolite over basalt observed from logged drill holes and outcrops. Applying this relationship to our results (Fig. 8b), we conclude that the onset of unweathered basalt is at about 17 m, which is within the 15-20-m thickness range of the weathered zone at the sea cliff outcrop (Fig. 2). The velocity model also is
Journal Pre-proof qualitatively consistent with the higher-resolution 2D roll-along MASW results (Fig. 8b) obtained along the line of the BIH-2 array (Sowards et al., 2018), including the shallow velocity inversion and the depth to the base of the weathered zone, marked by the onset of increasing shear-wave velocity beginning at 500 m/s. The pattern of the velocity variation is similar between the two methods, including the depth to the onset of velocities higher than 500 m/s, although the maximum velocity values for the passive 1D experiment are somewhat higher than
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those for the 2D MASW results. In particular, the higher resolution (but shallower investigation)
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2D and the lower-resolution (but deeper investigation) 1D results (Fig. 8b) show a similar
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arrangement of high and low velocity layers, but with somewhat varying thicknesses and
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velocities. The variation in the velocity models could express either differing levels of resolution between the two methods or geological variation within what are otherwise laterally continuous
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layers in the saprolite, considering that the two models are not exactly co-located (Fig. 1).
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We remark that the spectra for the combined passive-active records from the BIH-3 array
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show a prominent mode (Fig. 6), relative to the passive-only spectra (Fig. 5). Further inverse modeling could be performed to jointly derive a velocity model using both fundamental and
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higher mode surface waves (Luo et al., 2007). Using a multi-mode inversion could improve the accuracy of the model results for deeper layers (Luo et al., 2007). SUMMARY AND CONCLUSIONS We demonstrate the ability of ocean waves impinging a headland to produce surface-wave dispersion curves that can be inverted for shear-wave velocity models. Ocean waves are well known for their low-frequency contribution to ambient noise. This study illustrates their value down into the traditional microtremor range (≥1 Hz). Our sea cliff site provides an ideal natural
Journal Pre-proof laboratory for testing the correspondence of the shear-wave modeling results with known lithologic and mechanical strength properties of the shallow subsurface (i.e., the soft saprolite over hard basalt bedrock from which the former is derived). F-k analysis helps to constrain the interpretation of the influence and directionality of ocean wave energy. As expected, there can be a strong dependence of the array orientation with respect to the shoreline on the completeness of the dispersion spectra. The recording array oriented perpendicular to the sea cliff furnished
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the best spectra, with a higher frequency response and an improved definition for the lower Adding an active source to the passive recordings further extended the Spectra quality was unaffected by record lengths or sample rates for
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frequency response.
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frequency range.
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frequencies higher than about 10 Hz; however, spectra for the 60-s passive records had improved
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definition between 5 and 10 Hz.
In general, inclusion of an active source in any type of surface-wave survey is advantageous.
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Using only a passive survey may not be adequate for a broad enough depth coverage--this being
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especially true where no ambient noise (e.g., wind, vehicle traffic, etc.) is present. Nevertheless, an active survey usually generates surface waves in frequencies higher than 10 Hz that sample
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relatively shallow depths (e.g., ≤ 20 m), while a passive survey can provide the lower frequencies for greater depths. Thus, a mix of active and strong passive (e.g., ocean waves) sources is optimal. We verified the quality of the spectra by modeling dispersion curves extracted from them and comparing the results with outcrop in the adjacent sea cliff, which extends all the way down to stiff and unweathered basalt lava bedrock, and with previous 2D modeling. When combined with an active triggering source and an array oriented perpendicular to the shore, passive sources provide an easy and unobtrusive way to obtain the thickness of a saprolite overburden, developed
Journal Pre-proof from chemical weathering of basalt. Our analysis does not reveal any specific features of an ocean-wave source that makes it an improvement over traditional vehicle traffic noise, except that the frequency of wave impacts along a cliff face compares favorably with a light-duty road with infrequent traffic (e.g., one vehicle per 5 minutes). An ocean-wave source can be utilized to good effect when vehicle traffic is light, sporadic, or too far distant.
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Acknowledgments This research was supported in part by funding from the College of Physical and
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Mathematical Sciences at Brigham Young University. The displays of records and the f-k
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analysis were made possible by a generous software grant from the Landmark (Halliburton)
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University Grant Program. Inverse modeling was performed using ParkSEIS software. The final
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version of the paper was greatly improved by comments and recommendations from three
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journal reviewers.
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Xia, J., Miller, R. D., Park, C. B., Hunter, J. A., and Harris, J. B., 2012, Comparing Shear-Wave Velocity Profiles from MASW with Borehole Measurements in Unconsolidated Sediments, Fraser River Delta, B.C., Canada, Journal of Environmental and Engineering Geophysics, v. 5, p. 1-13. Yilmaz, O., 2001, Seismic Data Analysis. Society of Exploration Geophysicists, Tulsa, U.S.A. Yong, A., Martin, A., Stokoe, K., and Diehl, J., 2013, ARRA-funded VS30 measurements using multi-technique approach at strong-motion stations in California and central-eastern United States: U.S. Geological Survey Open-File Report 2013–1102, 59 p. and data files, pubs.usgs.gov/of/2013/1102/. Zhou, C., Xi, C., Pang, J., and Liu, Y., 2018, Ambient noise data selection based on the asymmetry of crosscorrelation functions for near surface applications, Journal of Applied Geophysics, v. 159, 803–813, doi.org/10.1016/j.jappgeo.2018.09.033.
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FIGURES
Figure 1. Location maps of study site, Kohala Peninsula, Big Island of Hawaiʻi. Map on the bottom shows close-up of study site with three recording arrays (BIH-2, 3, 4), along with beginning and ending channel numbers for each. The usual direction of trade winds (blue arrow) is from Stopa et al. (2011).
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Figure 2. Photo of sea cliff at the study site showing the thick saprolite layer (double arrow) over relatively unweathered basalt lava platform at sea level. Note that the thickness of the weathered zone is variable, but ranges between 15 and 20 m. View is looking southeast, taken down and to the northwest from the beginning of BIH-3 (Fig. 1). Photo by J. H. McBride.
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Figure 3. (a) Excerpt of field record for BIH-3 combined passive-active source array. The interpreted parts of wave field are noted. Seismic data displayed as variable density (grayscale) (top row) and as variable area wiggle trace (bottom row). Amplitude scale is referenced to the last trace on each individual record. Recording time is 60 s. (b) Same as in (a), but for the passive-only source array. Arrows indicate examples of ocean-wave impact arrivals. (c) Same as in (b), but for BIH-2 array, showing interpreted mixed ocean-wave arrivals (arrows indicate examples) from approximately 360 m to the east (as inclined events) and from approximately 100 m to the north (as flatter events). See Figure 1 for location. Note that increasing channel number, from northeast to southwest, is the positive signed direction for BIH-3 and from southeast to northwest for BIH-2.
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Figure 4. (a) Frequency-wavenumber (f-k) spectrum for a typical field record from the combined passive-active BIH-3 array (60-s record). Hot colors are high amplitude, cold colors are low amplitude (a color relative amplitude scale is shown). The regions of low-apparent velocity (dominated by surface waves from the hammer strike) and high-apparent velocity (dominated by body waves from the hammer strike) are noted. Examples of two apparent velocities are shown for reference. (b) Same as in (a), but for passive only BIH-3 array. Spectrum is dominated by ocean waves arriving mainly from the northeast, along the nearest shoreline. (c) Same as in (b), but from the BIH-2 passive array. High-amplitude response is dominated by distant ocean-wave arrivals from the southeast (lower apparent velocities) and approximately broadside from the northeast (higher apparent velocities). Note that backscattered events occur in the passive spectra (negative wavenumbers).
Figure 5. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for purely passive 30-s record (sample rate, 2 ms) from BIH-2. (b) Same as in (a), but for 60-s record (sample rate, 4 ms). (c) Same as in (a), but for BIH-3 array. (d) Same as in (b), for BIH-3 array. See Figure 1 for location of arrays.
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Figure 6. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for combined passive-active records from the BIH-3 array for 30-s record length (sample rate, 2 ms). Note the stronger higher mode, relative to the purely passive versions (Fig. 5). (b) Same as in (a), but for 60-s record length (sample rate, 4 ms) (compare with purely passive spectra for BIH-3 in Figures 5c, d).
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Figure 7. (a) Phase velocity plotted as a function of frequency (dispersion spectra) for passive record from the BIH-4 array (parallel to and offset from BIH-3 by 35 m) with a 60-s record length (sample rate, 4 ms) (compare with spectra for BIH-3 in Figure 5d). (b) Same as in (a), but for combined passive-active record (compare with spectra for BIH-3 in Figure 6b).
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Figure 8. (a) Dispersion curve extracted from BIH-3 passive-active recording (Fig. 6a) along with the signal-to-noise-ratio (S/N). The S/N curve indicates the amplitude ratio for each particular frequency in comparison to all other possible modes. For example, S/N=1.0 at 10 Hz means the fundamental mode accounts for 100% of measured seismic waves. On the other hand, S/N=0.5 at 10 Hz means the measured fundamental mode surface wave at 10 Hz takes up 50% of the total seismic amplitude at 10 Hz—the remaining amplitude (i.e., another 50%) can be either noise or other modes (e.g., higher modes or body waves).
Figure 8 (b) Extracted and final modeled dispersion curves from BIH-3 passive-active recording (Fig. 6a). Compare with Figure 8a.
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Figure 8 (c) Left, Excerpt of two-dimensional (2D) shear-wave velocity model obtained by Sowards et al. (2018) near middle of BIH-2 (Fig. 1) based on a moving-source roll-along technique. See Sowards et al. (2018) for details of seismic data acquisition and modeling. Right, One-dimensional shear-wave velocity-depth function, based on modeling the dispersion spectrum from the BIH-3, 60-s combined passive-active record (Fig. 8b). The onset of increasing velocity with depth, beginning at 500 m/s, is at a depth of about 17 m, which is just above the depth to rigid basalt bedrock as exposed in the face of the nearby sea cliff (Fig. 2) and derived independently in the 2D velocity model shown.
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Highlights We demonstrate how ocean waves can be used as a passive seismic source Directionality of the recording array affects quality of dispersion function Example results are tested against geologic outcrop and previous velocity modeling