This document discusses using Love waves in active Multichannel Analysis of Surface Waves (MASW) surveys to improve data quality. It proposes recording both left and right polarized Love waves in addition to Rayleigh waves. The polarization of Love waves could help quality control data collection. Stacking the polarized Love waves in the phase velocity domain may enhance the dispersion image compared to using Rayleigh waves alone. The paper aims to test this approach on a field site and compare the shear wave velocity profiles obtained from inverting Love wave and Rayleigh wave dispersion data. References are provided on research related to improving MASW surveys through better handling of higher surface wave modes.

1. Near surface geophysics: polarity of Love waves and its use in refining data in active
Multichannel Analysis of Surface Waves (MASW) surveys by Benjamin N Seive 04/05/2014
Near surface geophysical seismic techniques have been efficient tools for more than 75 years to better understand
the properties of the subsurface (Steeples, 2005). Modern techniques are fast and non-intrusive and commonly
used for geotechnical investigations prior construction, environmental remediation issues and resources
exploration. One of the most recent developments is the Multi-Channel Analysis of Surface Waves (MASW) (Park
et al., 1997 and 1999) which can generate shear wave velocity profiles of the subsurface. Because the shear wave
velocity is directly related to the geotechnical parameter shear modulus at small strain of the soils/rocks, MASW
can be used as a site characterization tool for earth quake engineering and seismic dynamic design requirements
(Foti, 2012). Moreover, the shear wave velocity is better at characterizing rock or soil types in comparison to other
body waves (P-waves) seismic surveys (Crice, 2005). Due to these advantages, active MASW surveys can be used to
map bedrock depths, location of faults, buried tunnels and cavities (Tokimatsu, 1995; Xia et al., 2004; Stokoe et al.,
2004) in a fast, cost effective and general accurate way.
The active MASW data collection method involves recording an artificially generated wave field at different
locations along a line of geophones as it travels through the earth. The aim of the MASW data collection is to
extract the surface wave component of this wave field (Park et al., 1999). Surface waves can develop in two types
of waves: Rayleigh wave or Love wave (Sheriff and Geldart, 1995). The wave field is generally produced at a certain
offset distance from the first geophone by a vertically falling mass; in general a simple sledge hammer is used.
Because of the vertical deformation imposed to the ground, the surface wave component of the wave field is
predominantly in the form of Rayleigh waves. That is the reason why active MASW survey currently uses Rayleigh
waves in their algorithm of analysis of surface waves. In contrast very few researches have been made to use Love
waves.
MASW surveys make use of two properties of the surface waves recorded: their high energy content and their
dispersive properties which are at the basis of the different data inversion methods that have been developed to
characterize the subsurface using MASW survey (Foti, 2005; Socco and Strobbia, 2004). In the seismic record the
surface waves are easily detectable because they contain 2/3 of the total seismic energy of the wave field recorded
(Richart et al., 1970; Heisey et al., 1982). Most importantly, surface waves traveling in an inhomogeneous media
are dispersive (Park et al., 1999). This means that different wavelengths have different penetration depths and
therefore propagate at different velocities. In a geological media the shorter wavelengths propagate in shallower
ground, which is usually made of slower velocity materials and the longer wavelengths propagate in deeper
ground, made of higher velocity materials (Neducza, 2007). On the recorded wave field, the dispersion property of
the surface waves is extracted as the curve of the highest energy values of a phase velocity-frequency domain
obtained by mathematical transforms. The dispersion curve is subsequently used in forward modelling schemes
and least square approach to produce a shear wave velocity model of the subsurface in which the dispersion
properties are similar (best fit approach) with the site recorded data (Lai et al., 2002; Xia et al., 1999).
The current inversion processes are mainly based on the correct identification of the fundamental mode of the
surface wave in the phase velocity – frequency domain (Zhang et al., 2003). However, in many instances it has
been reported that several higher modes are present in the surface wave dataset and that if an incorrect
identification of the fundamental is made, erroneous and ambiguous inverted model can be produced (Dal More
et al., 2011). Higher modes of surface waves commonly appears in the energy dispersion image (i.e. the phase
velocity – frequency domain) when sharp variation in stiffness of the subsurface layering is present such as a very
stiff layer close to the surface or a softer layer between harder layer (O’Neill and Matsuoka, 2005). Major “jump”

2. in energy between fundamental modes to higher modes can occur, especially at higher frequencies, creating data
gap in the fundamental mode on the dispersion image. Even more subtle issues arises arise when the several
modes, if present, are co-located in the energy dispersion image (i.e. not separated) and create an apparent
effective phase velocity instead of a fundamental mode phase velocity (Chai et al., 2012). Inverted model with
effective phase velocity have been shown to produce wrong model when trying to resolve thin layers with low
velocities (Zhang et al., 2003).
Due to the very likely higher modes generation in the recorded surface wave dataset, most of the research effort is
made to improve the contrast of the fundamental mode in the dispersion image; improve the separation of the
higher modes in the dispersion image; or using the higher modes in the inversion process to better constrain the
inverted model. For instance, developments are made toward using different spread configuration with non-
equidistant geophones spacing and determining the best active source offset location to better resolve and
separate the different modes of the surface waves (Dikmen et al., 2010). Also, new techniques to stack the data
have been proven to enhance the multimode dispersion curve which allows easier identification of the
fundamental mode in the dispersion image (Neducza, 2007). Improvement on the quality control of the dataset
collected has been made to check the data uncertainty (i.e. likely higher mode generation), near field effect, and
lateral discontinuity (Strobbia and Foti, 2006) that would directly affect the quality of the dispersion curve and
therefore the inverted model. On the topic of dispersion image, more accurate mathematical transform have been
developed to create better phase velocity – frequency domain to allow more accurate identification of the
fundamental mode and higher modes energy pattern with high resolution linear radon transform (Luo et al., 2008).
Finally, new algorithms have been developed to take into account higher modes into in the inversion process
(Ivanov et al., 2010; Xia et al., 2003) but they are not yet readily available and can still suffer from issues of non-
uniqueness of the produced shear wave model.
In contrast, few researches have been made on using Love waves instead of Rayleigh wave to create the dispersion
image. Authors like Dal Moro and Ferigo (2011) have shown the usefulness of using Love waves in active MASW
survey. Love waves are in general much less affected by higher mode generations compare to Rayleigh Waves
(Safani et al., 2005) and therefore can produced much more easily interpretable dispersion image. To the author
knowledge, no research has been made yet to use the polarizable property of the Love waves in order to keep
improving the method.
This research paper aims at reducing this gap by testing an active MASW survey where left and right polarizable
Love waves are recorded. Rayleigh waves are recorded as well as a comparison tool. The dispersion image for the
waves are created and compared to see if Love waves generate better dispersion image. The polarizable property
of the Love waves is first used as a quality control tool of the collected data. Then the two polarities of the Love
waves are stacked in the phase velocity domain to further enhance the quality of the dispersion image compare to
a survey with Rayleigh wave only.
The paper is organized as follows. The site data collection methodology is presented first. Then the collected data
are transform in the phase velocity- frequency domain and inverted to produce shear wave velocity profiles with
the SurfSeis© software form KGS. Finally, comparison of the results is made and recommendations are developed.

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