## 1 Introduction  
The measurement of the shear wave velocities (V\({}_{\text{s}}\)) of soils is an important aspect in the application of geotechnical and earthquake engineering. This geophysical parameter is related to the shear modulus (G) through the elastic theory, in the equation G = \(\rho\)V\({}_{\text{s}}\)\({}^{2}\), where \(\rho\) is the density of material. The stress-strain behavior of materials is then dictated by the shear modulus, as the strain is directly affected by this parameter [1]. This relationship is also important in ground response analysis, as it is used to evaluate the dynamic response of soils during earthquakes. The seismic shear wave velocity of the upper 30-m soil layer (V\({}_{\text{s}}\)30) largely influences the ground motion amplification and is therefore considered an important parameter in earthquake engineering [2]. Additionally, the shear wave velocity of geomaterials is also used in studies on soil stratigraphy, liquefaction analysis, and site-specific subsurface modeling [3, 4, 5]. Shear wave velocities can be measured or estimated using a variety of laboratory or field tests. Bender element and resonant columns are some of the laboratory techniques that measure V\({}_{\text{s}}\). The accuracy of these techniques is greatly dependent on the degree of disturbance of the soil samples [6]. In situ field measurements include invasive methods such as down-hole, cross-hole, and up-hole tests. These techniques require the drilling of boreholes to a particular depth and, thus, may not be economically feasible in all situations. On the other hand, non-invasive geophysical methods, such as spectral analysis of surface waves (SASW), multichannel analysis of surface waves (MASW), refraction microtremor(ReMi), among others, can also estimate \(V_{s}\) on site. These techniques do not require drilling equipment and only use acoustic sensors to determine the subsurface shear wave velocities. There have been attempts to correlate this geophysical parameter to other physically measured soil properties. These empirical correlations between the geotechnical parameters of soil and \(V_{s}\) were established in order to aid in soil behavior estimation and seismic demand analysis (e.g., [PERSON] et al., 2015 [7]; [PERSON], 2017 [2]). However, these relationships are only accepted in localized data. In Japan, many works regarding this area were done in the 1970s, utilizing datasets from different regions (i.e., [PERSON] and [PERSON], 1970 [8]; [PERSON] and [PERSON], 1970 [9]; [PERSON], 1970 [10]; [PERSON] et al., 1972 [11]; [PERSON], 1972 [12]; [PERSON] and [PERSON], 1973 [13]; [PERSON], 1977 [14]). These works mainly evaluated the dynamic response of soils (e.g., liquefaction) due to earthquakes. This continued into the 1980s, as [PERSON] and [PERSON] (1982) [15] proposed a correlation with the most data points (\(n=1654\)) based on the relative density of the subsurface soil (N-value), soil type, and geologic age. The work of [PERSON] and [PERSON] (1982) also indicated that clayey layers have higher \(V_{s}\) values in comparison to sandy soils. In the United States, a similar correlation was proposed by [PERSON] and [PERSON] (1981) [16], to determine liquefaction susceptibility of alluvium and marine sands. Their correlation utilizes corrected SPT parameters such as the N\({}_{60}\) and (N\({}_{1}\))\({}_{60}\). This proposal is similar with the works by [PERSON] et al., (1985) [17]; [PERSON] and [PERSON] (1983) [18], [PERSON] et al. (1998) [19], and [PERSON] et al., (2010) [20]. Other countries have developed similar empirical correlations. Over the past decades, works by [PERSON] et al. (1992) [21], [PERSON] et al. (1999) [22], [PERSON] (1995) [23], [PERSON] et al. (1995) [24], [PERSON] and [PERSON] (2011) [25] have been completed in Greece. From Turkey, works by [PERSON] (1996) [26], [PERSON] (1996) [27], [PERSON] and [PERSON] (2007) [28], [PERSON] and [PERSON] (2008) [29], [PERSON] (2009) [30], and [PERSON] et al.