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Site characterization using passive seismic techniques: A case of Suez city, Egypt
Journal of African Earth Sciences 156 (2019) 1–11
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Site characterization using passive seismic techniques: A case of Suez city, Egypt
T
Mostafa Tonia,∗, Toshiaki Yokoib, Medhat El Rayessc a
Geology Department, Faculty of Science, Helwan University, Cairo, Egypt International Institute of Seismology and Earthquake Engineering (IISEE), Building Research Institute (BRI), Tsukuba, Japan c National Research Institute of Astronomy and Geophysics (NRIAG), Helwan, Cairo, Egypt b
A R T I C LE I N FO
A B S T R A C T
Keywords: Microtremor Suez city SPAC CCA HVSR AVS30 Predominant frequency
This article introduces a site investigation study using quick and low-cost passive seismic techniques at Suez city which located in the northeastern part of Egypt. The Spatial Auto Correlation (SPAC) method is applied, as well as the newly developed Centerless Circular Array (CCA) method for estimating the shear wave velocity (Vs) structures of the subsurface layers using microtremor array data. The Horizontal/Vertical Spectral Ratio (HVSR) approach is employed in determination of predominant frequency (f0) of a site and its equivalent peak amplitude of ground motion (A0) using a single station microtremor measurements. In this study, microtremor array measurements have been carried out at five sites distributed in Suez city. In order to cover a wide frequency band, different array sizes are carried out at each observation site. Measurements are made using high performance accelerometers with a sampling rate 100 sample per second. In both SPAC and CCA methods, only the vertical component of microtremor data is considered in the analysis. The analysis includes two main stages, i.e., calculation of surface wave dispersion curves and inversion process to infer the Vs structure of the ground. The obtained dispersion curves cover frequency band (2.0–21.0 Hz) and show a good fitting between the observed and the calculated ones at all measured sites, proving the reliability of the inversion process performed in this work. In HVSR analysis, the E-W, N-S, and vertical components of microtremors are considered, and the ratio between the horizontal and the vertical components spectra is calculated, then the spectral ratio curves are produced. The predominant frequency (f0) and the peak amplitude (A0) of HVSR curve are reported for each site of observation. The inferred Vs profiles are used for calculating the average velocity value of shear wave up to 30 m depth (AVS30) which in turn employed in site classification at the investigated area. The results demonstrate that the parameter AVS30 varies between 248 m/s and 310 m/s in Suez city. The created site classification incorporates only one class (Class D), appearing no significant variation in the characteristics of the superficial and shallow soils in Suez city. The site predominant frequency (f0) ranges between 0.35 Hz and 5.0 Hz with relevant amplification (A0) between 1.6 and 4.2. These outputs represent a crucial site response model for future seismic hazard assessment and risk decrease studies in Suez area which is currently witnesses large investments and rapid land use planning.
1. Introduction Passive seismic techniques using microtremors (also known as ambient noises) gained in the last few decades an essential role in many seismological investigations. They are often employed in determination of Vs structure of the ground and estimate the parameter AVS30 which is used in building codes for seismic site classification. Also, microtremor techniques are widely used in determination of the site predominant frequency and its equivalent amplification of ground motion.
∗
Among the advantages of using passive techniques in site investigations is the possibility of using them in the urban environments without causing disturbance to inhabitants and neighboring buildings. Moreover the frequency content of microtremor covers a wider range which makes it possible to investigate deep structures in low cost and limited time and personnel requirements comparing with active techniques which are costly and offer a restricted investigation depths. In this work, three passive seismic techniques using microtremor data are used in determination of the dynamic properties of subsurface
Corresponding author. E-mail address: [email protected] (M. Toni).
https://doi.org/10.1016/j.jafrearsci.2019.05.004 Received 11 February 2019; Received in revised form 3 May 2019; Accepted 3 May 2019 Available online 06 May 2019 1464-343X/ © 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. Location map of the study area showing microtremor observation sites and locations of drilling data.
Aqaba where the transform fault system is the predominant tectonic force. Prime examples of earthquakes that had been reported from this source are the 3 August 1993 (Mb 5.8) earthquake, the largest earthquake (Mw 7.3) of 22 November 1995, and the 27 June 2015 (Mb 5.2) earthquake (Abd el-aal and Badreldin, 2016; Badreldin et al., 2019). The northern Red Sea where the triple junction of the relative motion between Arabian plate, African plate, and Sinai sub-plate occurs represents another seismic source that has a significant impact on Suez city. Moreover, Suez city is affected from the western side by the intraplate seismotectonic activity of Cairo-Suez district. The area under investigation is located on the Suez Canal region of in the western side of Suez Gulf. In view of the geological setting of Suez Canal region, it can be stated that this region occupies a semi-flat terrain with ripple marks extend from North to South. High topographic land (e.g., up to 234 m above sea level in G. Genifa (mountain) and 226 m above sea level in G. Shabraweet (mountain)) rises toward the west and the northwest of the study area (Said, 1962; El Shazly et al., 1975; Ramadan, 1984; Geriesh, 1999). Salem (1988) analyzed the structural features in the area under investigation and its environs to determine the style of deformation and stress directions that influence this region and reported that it mostly affected by normal faults and few diagonals with major dip-slip and minor strike-slip components. By focusing on the area where microtremor measurements have been conducted, it is covered by deposits that belong to Miocene-Pliocene and Quaternary ages. The Miocene-Pliocene deposits are composed of gravel, sand, clay, and limestone with sandstone and clay, while Quaternary deposits are composed of sandy clay, sabkhas (a type of marine deposit), gravels, gypsum, beach sand, wadi alluvium and sand dunes (Said, 1962; El Shazly et al., 1975; Geriesh, 1999; Hegazi et al., 2013). Shallow drilling data (up to 15 m depth) is available from four locations in the investigated area (Fig. 1) and used in description of subsurface soil (Fig. 2). As shown in the graphical description depicted in Fig. 2, there are no significant lateral variation in the subsurface soil within the investigated area, and the soil composed mainly of limy clayey shale and sand with different cohesion degrees. This study represents the first application of SPAC and CCA techniques in Suez city in combination with the HVSR method for site characterization. The expected model of the site dynamic characteristics represents a major input parameter for future seismic hazard assessment and risk reduction studies in the Suez area.
soil layers at Suez city, which located in the northeastern portion of Egypt (Fig. 1). For the first time the new developed CCA technique (Cho et al., 2006 a; b) is applied in Egypt in combination with the SPAC method (Aki, 1957) after its previous applications by Toni et al. (2016 a,c) and Maklad (2017). The most common HVSR method (Nakamura, 1989&1997) is also applied. Both SPAC and CCA are used to retrieve the shear wave velocity (Vs) structure of the subsurface soils, while the HVSR is used in determination of the site predominant frequency (f0) and its equivalent peak amplitude of ground motion (A0). The resulted Vs structural models are used in determination of AVS30, which in turn used in classification of the surface soil at the investigated area. The Suez city (i.e. the case of the present study) is a naval-port city in northeast Egypt, located on the north coast of the Gulf of Suez, at the southern gateway of Suez Canal (Fig. 1). The Suez city is the capital of a governorate that holds the same name, covering a surface area 250 km2, and populated with about 744,000 in 2018 (https://en.wikipedia.org/ wiki/Suez). The importance of Suez city comes from its location on the Suez Canal which is an artificial waterway connecting the Mediterranean Sea to the Red Sea with a total length of about 193 km. Moreover, the industrial section of the city includes many factories working mainly in the petroleum sector and a commercial port that is utilized for shipping merchandise between many countries around the Red Sea region. Currently, the region witnesses development of large strategic projects such as the digging of a new canal parallel to the present Suez Canal to increase its capacity by permit sailing in both directions simultaneously. Besides, new logistic and ship services centers are built along the Suez Canal, making the city a vital trading center globally. From a seismological view point, the city of Suez is surrounded by seismic sources of low to moderate activity. Among these sources is the Gulf of Suez where the Red Sea rifting system exists. In this zone, the largest earthquake (ML 6.7) in the recent history occurred in the gateway of the Suez Gulf on 31 March 1969 (McKenzie et al., 1970). Another earthquake was reported in the same area on 28 June 1972 with magnitude Mb 5.6 (Ben-Menahem et al., 1976). The most significant events that recorded from the Gulf of Suez in the past few years are: The 30 January 2012 earthquake with local magnitude ML 4.6 which occurred in the very south of the Gulf of Suez (Hosny et al., 2013), the 22 January 2013 (ML 4.1) and the 1 June 2013 (ML 5.1) earthquakes which occurred in the central Gulf of Suez with similar epicenter and different depths (Toni et al., 2016b; Toni, 2017). The area of Suez is also influenced by the earthquake activity from the Gulf of 2
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ρ (rAB, ω) =
1 2π
1 = 2π
2π
∫ 0 2π
Re{E [CA,B (ω)]} dθ E [CA, A (ω)]
∫ exp[ikrAB cos(θ −
∅)] dθ = J0 (krAB) (1)
0
where ρ(rAB,ω) is the SPAC coefficient from microtremors, rAB and θ are the distance and the azimuth respectively between two observation points xA and xB, ∅ is the azimuth along which the incidence of waves takes place, and k denotes the wavenumber. The CA,B(ω) denotes the cross spectra of the records obtained at the observation points xA and xB. Yokoi (2010) reported that the term (E[CA,A(ω)]E[CB,B(ω)])1/2 could be used instead of E[CA,A(ω)] to correct local ground amplification. The wavenumber k(ω) can be estimated by fitting J0(kr) with the observed SPAC coefficient. The phase velocity c(ω) = ω/k(ω) is calculated for each frequency using ω2πf; then c(ω) can be inverted to a layered ground structure of density and velocities (Vp and Vs) by using the inversion techniques; e.g., the Heuristic Search (e.g., Lomax and Snieder, 1994), the Simulated Annealing (e.g., Sen and Stoffa, 1991), and the Neighborhood Algorithm (e.g., Sambridge, 1999a,b). Alternatively, the direct search for underground structures that gives the best fit with SPAC coefficient can be used (e.g., Asten et al., 2004; Wathelet et al., 2005&, 2008). The analysis procedures of SPAC method are depicted in Fig. 3. For more details about SPAC method, the reader is referred (Okada, 2003; Wathelet et al., 2005; Tada et al., 2007; Yokoi, 2010; Foti et al., 2018). 2.2. CCA Another approach used in this study is the newly developed CCA technique (Cho et al., 2004 & 2006a) which is effective for analyzing microtremors of small size array (mini-array) based on a theory derived by generalizing SPAC method (Cho et al., 2006b). The CCA method uses vertical component of microtremors for determining the Rayleigh wave phase with wavelengths exceeding several ten times the array radius (Cho et al., 2004 & 2006 b,c). Cho et al. (2013) pointed that the CCA method could identify the phase velocities using a circular array with radius (r). Analysis limit of the shortest-wavelength in CCA equals 2r, while the longest-wavelength analysis limit is determined by the signalto-noise ratio (SNR). When the SNR becomes large, the resolving power of long wavelengths is higher in CCA method than in SPAC method (Cho et al., 2006a). The CCA coefficient is defined as follows (Cho et al., 2006a):
Fig. 2. Graphical description of the shallow subsurface soil beneath Suez city.
2. Methodology In this section we briefly describe the SPAC, CCA, and HVSR approaches which are employed in the analysis of microtremor data conducted in the current study.
π
s (r , ω) = 2.1. SPAC
PSD ∫−π Z (t , r , θ) dθ π −π
PSD ∫ Z (t , r , θ)exp(−iθ) dθ
=
J02 (rω/ c ) J12 (rω/ c )
(2)
where PSD is the power spectral density; Z(t,r,θ) is the microtremor vertical component observed at radius r, azimuth θ, and time t. The third part of equation (2) denotes the theoretical formula of the CCA coefficient, J1(rω/c), the first-order Bessel function of the first kind with the argument composed of the radius r, angular frequency ω, and phase velocity c. The numerator and denominator of the second part of equation (2) are the PSD of the zero and the first-order coefficients of the Fourier expansion over the azimuth, respectively, whereas the SPAC use its zero-order term alone (Cho et al., 2006b; Yokoi, 2010). The central station is used to determine the influence of the incoherent components of microtremors and to correct the results of analysis for those unwanted effects, however it is not indispensable in situations where incoherent noises are expected to be negligible (Yokoi, 2010). Among the advantages of CCA method is the possibility to cover a wide frequency range using only a small radius circular array. In contrast, the SPAC requires arrays of different sizes to be combined because only a narrow kr range is available for accurate determination of the phase velocity (Apostolidis et al., 2004; Tsuno and Kudo, 2004). This is because at small kr the resolution is low, whereas at large kr the SNR is
The SPAC method is an effective tool to estimate the Vs structure below a site of investigation by dispersion analysis of the propagating surface waves. It is based on the theory of stochastic process proposed by Aki (1957&1965). In recent years, the SPAC method has attracted attention in the community of earthquake engineering due to its easiness of application and its ability to investigate deep structures with reasonable cost (Morikawa et al., 2004; Wathelet et al., 2005; Asten, 2006; Okada, 2006; Köhler et al., 2007). Application of SPAC requires perfectly shaped arrays, typically it requires a single number of seismic stations distributed around a circle with equal azimuthal intervals plus a central station (Wathelet, 2005; Tada et al., 2007). Since the pioneering idea of Aki (1957&1965), the SPAC method underwent development by several researchers, from the most recent ones (e.g., Okada, 2003; Asten, 2006; Yokoi, 2010). The following general formula describes the principle underlying of SPAC:
3
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Fig. 3. The analysis procedures of SPAC method (Yokoi, 2017a).
Fig. 4. The analysis procedures of CCA method (Yokoi, 2017b).
low due to contamination by incoherent noises (Cho et al., 2008). Other notable advantages of CCA are: It implements mini-array which is easily available; the array observation is almost as easy as a single observation point to be carried out; furthermore, the site of installation requires a little effort because the installation can be deployed at small area such as a site at the roadside or in a little space in a parking parcel (Cho et al., 2013). All this makes the method very suitable for urban environments. The analysis procedures of CCA method are depicted in Fig. 4.
Fig. 5. Array configuration carried out in the present study. Four-point array with a triangular shape (left); four arrays with different sizes carried out at each observation site (right).
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Fig. 6. (Left): SPAC coefficient curves for small distance (distance between central station and any station on the triangle) and large distance (plane distance between any two adjacent stations on the circumference of a triangle) for each array size (48m, 24m, 12m, and 6m) of Array 3. (Right): Dispersion curve derived from SPAC analysis for Array 3, the frequency range between the first two green lines represents the reliable part, while the frequency range between the second green line and the third blue line represents the acceptable part of the dispersion curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 7. Power spectra of seismic stations (a); coherence curves between array's stations (b); CCA coefficient (c); and dispersion curve (d) derived from CCA analysis for the mini-array of site 3 as a representative example.
microtremor. This method was introduced by Nakamura (1989) based on the principles suggested by Nogoshi and Igarashi (1971), which in turn based on the initial studies of Kanai and Tanaka (1961). Due to the easiness of application in terms of data measurement and processing in addition to low expenses, the HVSR is vastly used in site effect studies and in a quick construction of microzonation maps mostly in urban settlements. A peak amplitude appears on the HVSR curve due to the dissimilarity between the uppermost sediments and the underlying rock at the site of observation. The peak frequency is considered to be the site fundamental frequency (f0), while the peak amplitude (A0) is directly related to velocity contrast, i.e. sharp velocity contrast yields large H/V peak amplitude, and vice versa (SESAME, 2004). The Fourier spectral ratio between the horizontal and vertical (H/V) components of microtremors can be expressed as follow:
Table 1 Site classification scheme of NEHRP (2004). Site class
Description
AVS30 (m/s)
A B C D E
Hard Rock Rock Very dense soil and soft rock Stiff soils Soft soils, profile with more than 10 ft (3 m) of soft clay Soils requiring site specific evaluations
> 1500 760–1500 360–760 180–360 < 180
F
–
2.3. HVSR The HVSR method is a simple and reliable technique to extract the site predominant frequency using three component measurements of 5
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using Fortran codes developed by one of the authors (Yokoi, 2017a,b) and GNUPLOT (http://www.gnuplot.info/) to plot the results. In both proposed techniques (SPAC and CCA), analysis of microtremor data focuses only on the record of vertical component where Rayleigh waves are supposed to be dominant. In general, the analysis includes two main stages: Determination of dispersion curves of surface wave, and inversion of the dispersion curve to derive the Vs structural profile of the ground. The procedures of data analysis include: data formatting, multiplexing, resampling, calculation of inter-station distances and azimuths, calculation of SPAC coefficient (in SPAC analysis) or CCA coefficient (in CCA analysis), and finally determination of dispersion curve (see Figs. 3 and 4). In the inversion stage, the Heuristic search of Vs structure was applied to retrieve the vertically 1D Vs profile (Yokoi, 2010). A representative example of the calculated SPAC coefficient and the equivalent dispersion curve obtained in the current analysis is shown in Fig. 6, while Fig. 7 shows an example of the power spectra calculated for seismic stations of the mini-array, the coherence curves between pairs of array's stations, the CCA coefficient, and dispersion curves obtained from CCA analysis. The inferred Vs profiles are here employed in the calculation of AVS30 (i.e. the average velocity value of shear waves in the top 30 m) at shear strain of 10−5 or less using the following relationship (Eurocode 8, 2003; CEN, 2004):
Fig. 8. Plot showing HVSR curves of all the measured sites in Suez city.
H / V (ω) = {[S2 (ω)NS + S2 (ω)EW]/ 2S2 (ω) V }1/2
(3)
AVS30 = 30 /
where [S(ω)NS and S(ω)EW] are the spectra of the two horizontal components north-south (NS) and east-west (EW) of microtremors, [S (ω)V] is the spectrum of vertical component (V), and ω is the angular frequency. Several studies (e.g., Field and Jacob, 1995; Bard, 2000; Parolai et al., 2001&2002; Mucciarelli and Gallipoli, 2004; SESAME, 2004; Turnbull, 2008; Gok and Polat, 2012; Gok et al., 2014) demonstrated that the HVSR method could adequately estimate the predominant frequency of a site, however the method still has some controversies regarding the estimation of site amplification factor. According to the European research project SESAME (2004), the HVSR method is useful in determination of the fundamental frequency of soil deposits, however, measurements and analysis require caution. On the other hand, the H/V peak amplitude represents an underestimate of the actual site amplification. The most recent study of Kawase et al. (2018), developed empirical corrections to Nakamura's method to evaluate directly the real site amplification from HVSR method. Application of the HVSR method is frequently used for site characterization at different localities in Egypt with reliable results (e.g., Mohamed and Fat-Helbary, 2010; El-Eraki et al., 2012; Mohamed et al., 2013&2015; Toni et al., 2016a; c; Abdel Hafiez and Toni, 2019).
∑ i = 1, N
hi vi
(4)
where hi and vi are the thickness (m) and the shear-wave velocity (m/s) respectively of the i-th layer, in a total of N, existing in the top 30 m of soil profile. As has been accepted in most international building codes i.e. National Earthquake Hazards Reduction Program (NEHRP, 2004) and Eurocode 8 (2003), the site is classified according to the AVS30 value. In this research the surface soil at Suez city is classified based on the estimated AVS30 values following the classification scheme of NEHRP (2004) which shown in Table (1). At each observation site in Suez city, microtremor record of one sensor has been chosen as a single station for HVSR analysis. Analysis was performed using the open access Geopsy software (http://www. geopsy.org) and focused on the frequency range (0.1–15 Hz). In such analysis, microtremor data relative to each ground motion component is split in the time domain into short time blocks (25–50 s) from the stable parts of the recorded signals, and to avoid transients from specific sources such as close traffics. Using the processing module of Geopsy software, microtremor data relative to each time block is transformed from time to frequency domain using the FFT, cosine tapered, and smoothed using Konno and Ohmachi's algorithm (Konno and Ohmachi, 1998). The two horizontal components (NS and EW) are merged with the quadratic mean to get the H component which in turn divided by the vertical component (V) to estimate the HVSR for each time block as follow:
3. Data set and analysis Microtremors have been conducted at Suez city in the western side of the Suez Canal. The date set includes microtremor recordings through an array of sensors at five observation sites distributed in Suez city (see Fig. 1). Each array comprises four seismic stations with a triangular shape (four-point array, three stations on the circumference of a circle and one at the center), which is a de-fact standard configuration for SPAC and CCA analysis (Fig. 5, left). In order to cover a wider range of frequencies, four arrays with sizes 48m, 24m, 12m, and 6m (Fig. 5, right) were carried out at each observation site (for SPAC analysis). Additionally, a mini-array with 2 m side length and radius (r = 1.16 m) has been carried out at each observation site (for CCA analysis). Measurements were made using high-performance accelerometer (McSEISMT NEO) from OYO Corporation. The signal was recorded in three components (North-South, East-West, and Vertical) with a sampling rate 100 sample per second and record duration 60 min (in small size arrays 2m, 6m, 12m) and 120 min (in larger size arrays 24m and 48m). In the present research, data processing (SPAC and CCA) is managed
HVSR (f ) =
NS (f ). EW (f ) V (f )
(5)
Finally, the spectral ratios relative to all time blocks are considered, then averaged to get the main spectral ratio curve (Fig. 8). The peak ground amlitude (A0) and its predominant frequency (f0) are defined for each spectral ratio curve corresponding to an observation site. Peaks from artificial sources such as machinery were treated with awareness, since they do not belong to the dynamic properties of the subsurface soil structure. 4. Results and discussions The Vs profiles resulted from SPAC and CCA analyses are plotted in Figs. 9 and 10 respectively. Both observed and calculated dispersion 6
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Fig. 9. Results of SPAC analysis: Observed and calculated dispersion curves (left); 1D Vs profile (right).
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Fig. 10. Results of CCA analysis: Observed and calculated dispersion curves (left); 1D Vs profile (right).
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Fig. 11. Comparison between dispersion curves derived from SPAC and CCA analyses (a), and Vs profiles inferred from SPAC (b) and from CCA (c) analyses of all the measured sites in Suez city.
Figs. 9 and 11b). The investigated depth in the Vs profiles show a good consistency with the minimum and maximum frequencies of the corresponding dispersion curves (Fig. 9). The results depicted in Fig. 10 show that the dispersion curves derived from CCA analysis of the mini-array cover frequency range between 4.0 Hz and 19.0 Hz and show a very good fitting between the observed and the calculated ones. The Vs profiles inferred from CCA analysis could investigate subsurface structures up to 37 m depth with high resolution, however arrays 1 and 5 investigated a very shallow depth (∼12m) because the dispersion curves of these arrays start at high frequency (over 9.0 Hz) as shown in Fig. 10 and in Fig. 11a,c. Comparing the dispersion curves derived from the two employed techniques (SPAC and CCA) reveals that the frequency bands of the dispersion curves derived from CCA analysis lay partially within the frequency range of those derived from SPAC analysis, and show in general lower amplitudes of phase velocities for CCA than SPAC curves (Fig. 11a). However, for Array 5 the dispersion curve derived from CCA analysis covers frequency band (11.2–19.0 Hz) and represents a high frequency extension of the dispersion curve derived from SPAC analysis (5.4–11.8 Hz) and shows higher amplitude of phase velocity than that obtained from SPAC (Fig. 11a).
Table 2 Results obtained in the investigated area. Site
Latitude
Longitude
AVS30 (m/s)
Site class
f0 (Hz)
A0
1 2 3 4 5
29.98544 29.99898 29.99453 29.96793 29.9545
32.55869 32.54071 32.51158 32.51951 32.56913
302.591 258.4 248.43 302.14 310.29
D D D D D
5.0 0.5 0.6 0.35 1.5
4.2 1.6 1.8 2.1 2.2
curves which were used in producing the Vs profiles through an inversion process are also shown in the same figures. The results demonstrate that the dispersion curves derived from SPAC analysis cover frequencies between 2.0 Hz and 21.0 Hz. The widest frequency band (2.0–20.4 Hz) is covered by Array 3, while the narrowest frequency band (5.3–11.8 Hz) is covered by Array 5 (Fig. 9). A good matching between the measured and the calculated dispersion curves is noticed for all arrays (Fig. 9), proving a reliability of the inversion process performed in the present study. The resulted VS profiles show shear wave velocity ranging from 130 m/s to 190 m/s at the surface layer and from 390 m/s to 585 m/s at the underlying rock (see 9
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In comparison with the previous work of Mohamed et al. (2016) in the western side of the Suez Canal area using a different technique (i.e. MASW method), the Vs profiles obtained in the current work demonstrate in general a good agreement with their results in terms of the frequency ranges covered by dispersion curves and the Vs value against investigated depths. Their results cover frequency range between 6.0 and 28.0 Hz with investigated depth up to 30m, however graphical comparison between our results and their results is not possible because the observation sites are not the same. Table (2) lists the values of AVS30 that have been estimated by averaging the shear wave velocities in shallow layers up to 30 m depth using equation (4). The classes of surface soils at the measured locations are also shown in Table (2) and reveal no considerable variance in the properties of the superficial and shallow soils in Suez city, since the whole investigated area has one site class (class D). The resulted HVSR curves are illustrated in Fig. 8. The site parameters extracted from these curves are the predominant frequency (f0) and its relevant amplification of ground motion (A0) at each site of observation. The results reveal that all the sites of observations at Suez city exhibit peak frequency value (0.35–5.0 Hz). Sites 3 and 5 exhibit more than one clear peak at HVSR curve (Fig. 8), which may be related to the presence of interfaces at different depths.
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European Committee for Standardization, Brussels. Cho, I., Tada, T., Shinozaki, Y., 2004. A new method to determine phase velocities of Rayleigh waves from microseisms. Geophysics 69, 1535–1551. Cho, I., Tada, T., Shinozaki, Y., 2006a. Centerless circular array method. inferring phase velocities of Rayleigh waves in broad wavelength ranges using microtremor records. J. Geophys. Res. 111, B09315. https://doi.org/10.1029/2005JB004235. Cho, I., Tada, T., Shinozaki, Y., 2006b. A generic formulation for microtremor exploration methods using three-component records from a circular array. Geophys. J. Int. 165, 236–258. Cho, I., Tada, T., Shinozaki, Y., 2006c. New methods of microtremor exploration. the centerless circular array method and the two-radius method. Third International Symposium on the Effects of Surface Geology on Seismic Motion, vol 1. Laboratoire Central des Ponts et Chaussées, Paris, pp. 335–344. Cho, I., Tada, T., Shinozaki, Y., 2008. Assessing the applicability of the spatial autocorrelation method. A theoretical approach. J. Geophys. Res. Sol. Earth 113 (B6). Cho, I., Senna, S., Fujiwara, H., 2013. Miniature array analysis of microtremors. Geophysics 78 (1), KS13–KS23. El-Eraki, M., Mohamed, A.A., El-Kenawy, A.A., Toni, M.S., Imam, S.M., 2012. Engineering seismological studies in and around Zagazig city, Sharkia, Egypt. NRIAG J. Astro. Geophys. 12/2012 (2), 141–151. https://doi.org/10.1016/j.nrjag.2012.12.009. 1. El Shazly, E., Abdel Hady, M., Salman, A., Morsy, M., El Rakaiby, M., El Assy, I., Kamel, A., Meshref, W., Ammar, A., Meleik, M., 1975. Geological Investigations of theSuez Canal Zone, vol 1975. Academy of Scientific Research and Technology, Cairo, pp. 54. Eurocode 8, 2003. Design of Structures for Earthquake Resistance - Part 1. General Rules, Seismic Actions and Rules for Buildings. English Version, Ref. No. (prEN 1998-1. 2003 E). Management Centre. rue de Stassart, Brussels, pp. 36 B-1050. Field, E.H., Jacob, K., 1995. A comparison and test of various site response estimation techniques, including three that are non reference-site dependent. Bull. Seismol. Soc. Am. 85, 1127–1143. Foti, S., Hollender, F., Garofalo, F., Albarello, D., Asten, M., Bard, P.Y., Comina, C., Cornou, C., Cox, B., Di Giulio, G., Forbriger, T., Hayashi, K., Lunedei, E., Martin, A., Mercerat, D., Ohrnberger, M., Poggi, V., Renalier, F., Sicilia, D., Socco, V., 2018. Guidelines for the good practice of surface wave analysis. a product of the InterPACIFIC project. Bull. Earthq. Eng. 16 (6), 2367–2420. https://doi.org/10. 1007/s10518-017-0206-7. Geriesh, H., 1999. Improvement of drinking water quality in the new villages, east of Suez canal navigation route, Sinai Peninsula, Egypt. Using artificial ground WaterRecharge techniques. Al-Azhar Bull. Sci. 15, 37–54. Gok, E., Polat, O., 2012. In: d'Amico, Sebastiano (Ed.), Microtremor HVSR Study of Site Effects in Bursa City (Northern Marmara Region, Turkey) in the Book of "Earthquake Research and Analysis - New Frontiers in Seismology. INTECH Publications, University Campus, Rijeka - Croatia, 978-953-307-840-3, pp. 380. 225-236. https:// www. intechopen.com/books/earthquake-research-and-analysis-new-frontiers-inseismology. Gok, E., Chavez-Garcia, F.J., Polat, O., 2014. Effect of soil conditions on predicted ground motion. case study from Western Anatolia, Turkey. Phys. Earth Planet. In. 229, 88–97. https://www.sciencedirect.com/science/article/pii/S00319201140 00120. Hegazi, A.M., Seleem, T.A., Aboulela, H.A., 2013. The spatial and genetic relation between seismicity and tectonic trends, the Bitter lakes area, north-east Egypt. Geoinf. Geostatistics Overv 1. 2. of, 7, 2. https://www.dx.doi.org/10.4172/2327-4581. 1000106. Hosny, A., Omar, K., Ali, S.M., 2013. The Gulf of Suez earthquake, 30 January 2012, northeast of Egypt. Rend. Fis. Acc. Lincei, 2013 24, 377–386. https://doi.org/10. 1007/s12210-013-0244-2. Kanai, K., Tanaka, T., 1961. On Microtremors VIII, vol 39. Bull Earthq Res Inst, Tokyo University, pp. 97–114. Kawase, H., Nagashima, F., Nakano, K., Mori, Y., 2018. Direct evaluation of S-wave amplification factors from microtremor H/V ratios. Double empirical corrections to “Nakamura” method. Soil Dynam. Earthq. Eng. https://www.doi.org/10.1016/j.
5. Conclusions This study aims to illuminate the site characteristics in Suez city which located on the Suez Canal in the northeastern portion of Egypt. Three passive seismic techniques (SPAC, CCA, and HVSR) using microtremor measurements have been employed to achieve the objectives of this study. The gained results allow making the following conclusions: 1 The parameter AVS30 varies between 248 m/s and 310 m/s, showing only one site category (Class D), which means that there are no considerable differences in the characteristics of the superficial and the shallow soils in Suez city. 2 The estimated site predominant frequency (f0) using microtremor HVSR method is reliable, while the estimated peak ground amplitude (A0) represent the lower threshold of the real site amplification (SESAME, 2004). 3 The employed techniques (SPAC, CCA, and HVSR) could successfully investigate reliable shear wave velocity structures and site response parameters in reasonable cost and without causing disturbance to inhabitants and buildings in Suez city. 4 The output of this study may represent a good model of the site dynamic parameters which is necessary for seismic hazard and risk reduction studies in Suez city which witnesses large investments and rapid land use planning, however intensive measurements are recommended for reliable seismic microzonation. Acknowledgments This study is funded by the Science and Technology Development Fund (STDF), Egyptian Ministry of Higher Education and Scientific Research through STF project (ID 25397). The authors are very grateful to the Department of Seismology, National Research Institute of Astronomy and Geophysics (NRIAG), Cairo, Egypt for kind support in microtremor data measurement. The authors are also very grateful to the International Institute of Seismology and Earthquake Engineering (IISEE), Building Research Institute (BRI), Tsukuba, Japan for hosting the project's PI and providing him with all scientific facilities to perform this study. References Abd el-aal, A.k., Badreldin, H., 2016. Seismological aspects of the 27 June 2015 Gulf of
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sediments, and resonance frequency calculated by the H/V ratio of seismic noise for Cologne Area (Germany). Bull. Seismol. Soc. Am. 92, 2521–2527. Ramadan, F., 1984. Sedimentological Studies on the Bottom Sediments of the Suez Canal. M.Sc Thesis. Faculty of Science, Zagazig University, Egypt. Said, R., 1962. The Geology of Egypt. Elsevier Pub Co., Amsterdam, pp. 377. Salem, A.S., 1988. Geological and Hydrogeological Studies on the Area between Gebel Ataqa and Northern Galala Plateau, Egypt. PhD Thesis. Faculty of Science, Zagazig University, Egypt. Sambridge, M., 1999a. Geophysical inversion with a neighborhood algorithm. Part 1 — searching a parameter space. Geophys. J. Int. 138, 479–494. Sambridge, M., 1999b. Geophysical inversion with a neighborhood algorithm. Part 2 — appraising the ensemble. Geophys. J. Int. 138, 727–746. Sen, M.K., Stoffa, P.L., 1991. Nonlinear one-dimensional seismic waveform inversion using simulated annealing. Geophysics 56, 1624–1638. SESAME, 2004. Site Effects Assessment Using Ambient Excitations. Guidelines for the implementation of the H/V spectral ratio technique on ambient vibrations measurements, processing and interpretation. European research project. WP12 – Deliverable D23.12, December 2004 1–62. Tada, T., Cho, I., Shinozaki, Y., 2007. Beyond the SPAC method. Exploiting the wealth of circular-array methods for microtremor exploration. Bull. Seismol. Soc. Am. 97 (6), 2080–2095. Toni, M., Abd el-aal, A.K., Mohamed, G.A., 2016a. Ambient noise for determination of site dynamic properties at Hurghada and Safaga cities, Red Sea, Egypt. Acta Geodyn. Geomater. 13 (3), 227–240. https://doi.org/10.13168/AGG.2016.0004. 2016. Toni, M., Barth, A., Ali, S.M., Wenzel, F., 2016b. Analysis of the similar epicenter earthquakes on 22 January 2013 and 01 June 2013, central Gulf of Suez, Egypt. J. Afr. Earth Sci. 121, 274–285. 10.1016/j.jafrearsci.2016.06.013. Toni, M., Mohamed, G.A., Abd el-aal, A.K., 2016c. Microtremor for evaluating the effect of shallow sediments on earthquake ground motion at Quseir city, Red Sea, Egypt. In: Near Surface Geoscience 2016 - 22nd European Meeting of Environmental and Engineering Geophysics, 4-8 September 2016, Barcelona, Spain. Toni, M., 2017. Simulation of strong ground motion parameters of the 1 June 2013 Gulf of Suez earthquake, Egypt. NRIAG J. Astro. Geophys. 6 (1), 30–40. https://doi.org/ 10.1016/j.nrjag.2016.12.002. Tsuno, S., Kudo, K., 2004. On the efficiency and precision of analysis of microtremors by SPAC method in practical engineering site. In: Proceedings of the 13thWorld Conference on Earthquake Engineering, Paper 345. Turnbull, M.L., 2008. Relative seismic shaking vulnerability microzonation using an adaptation of the Nakamura horizontal to vertical spectral ratio method. J. Earth Syst. Sci. 117 (S2), 879–895. Wathelet, M., 2005. Array Recordings of Ambient Vibrations. Surface-Wave Inversion. PhD Thesis. Université de Liège, Belgium. Wathelet, M., Jongmans, D., Ohrnberger, M., 2005. Direct inversion of spatial autocorrelation curves with the Neighborhood algorithm. Bull. Seismol. Soc. Am. 95, 1787–1800. https://www.doi.org/10.1785/0120040220. Wathelet, M., Jongmans, D., Ohrnberger, M., Bonnefoy-Claudet, S., 2008. Array performances for ambient vibrations on a shallow structure and consequences over vs inversion. J. Seismol. 12, 1–19. Yokoi, T., 2017a. SPAC2017 Ubuntu. https://www.iisee.kenken.go.jp/net/SPAC_FREE_ PROGRAM/SPAC2017_Ubuntu_open4public/SPAC_PROGRAM_DOWNLOAD.html. Yokoi, T., 2017b. CCA2017 Ubuntu. https://www.iisee.kenken.go.jp/net/CCA_FREE_ PROGRAM/CCA2017_Ubuntu_open4public/CCA_FREE_PROGRAM.html. Yokoi, T., 2010. New formulas derived from seismic interferometry to simulate phase velocity estimates from correlation methods using microtremor. Geophysics 75 (4), SA71–SA83. https://doi.org/10.1190/1.3454210.
soildyn.2018.01.049 (in press). Konno, K., Ohmachi, T., 1998. Ground motion characteristics estimated from spectral ratio between horizontal and vertical components of microtremor. Bull. Seismol. Soc. Am. 88 (1), 228–241. Köhler, A., Ohrnberger, M., Scherbaum, F., Wathelet, M., Cornou, C., 2007. Assessing the reliability of the modified three-component spatial autocorrelation technique. Geophys. J. Int. 168, 779–796. Lomax, A., Snieder, R., 1994. Finding sets of acceptable solutions with a genetic algorithm with application to surface wave group dispersion in Europe. Geophys. Res. Lett. 21, 2617–2620. Maklad, M., 2017. Estimation of Shear Wave Velocity Profiles Using Microtremor Array Explorations in Ismailia City, Egypt. M.Sc. thesis,. Disaster Management Policy Program, National Graduate Institute for Policy Studies (GRIPS), Tokyo, Japan & International Institute of Seismology and Earthquake Engineering (IISEE), Building Research Institute (BRI), Tsukuba, Japan. McKenzie, D., Davies, D., Molnar, P., 1970. Plate tectonics of the Red Sea and east Africa. Nature 226, 243–248. Mohamed, A., Fat-Helbary, R., 2010. Microtremors measurements for site effect investigation at Aswan New City, Egypt. In: Proceedings of the 14th European Conference of Earthquake Engineering (14ECEE), Macedonia, 30 August-03 September 2010. Mohamed, A., Fat-Helbary, R., Basheer, A.A., Dojcinovski, Dragi, 2013. In: “Using Ambient Vibrations for Site Characterization at the New Aswan University Site, Southern Egypt” SE50EEE International Conference on Earthquake Engineering, Macedonia, 29-31 May 2013. Mohamed, A., Lindholm, C., Girgis, M., 2015. Site characterization and seismic site response study of the Sahary area, South Egypt. Acta Geodyn. Geomater. 12 (180), 427–436. https://doi.org/10.13168/AGG.2015.0032. No. 4. Mohamed, E.K., Shokry, M.M.F., Hassoup, A., Helal, A.M.A., 2016. Evaluation of local site effect in the western side of the Suez Canal area by applying H/V and MASW techniques. J. Afr. Earth Sci. 123, 403–419. 10.1016/j. jafrearsci.2016.07.004. Morikawa, H., Sawada, S., Akamatsu, J., 2004. A method to estimate phase velocities of Rayleigh waves using microseisms simultaneously observed at two sites. Bull. Seismol. Soc. Am. 94, 961–976. Mucciarelli, M., Gallipoli, M.R., 2004. The HVSR technique from microtremor to strong motion. empirical and statistical considerations. In: Proc. Of 13th World Conference of Earthquake Engineering, Vancouver, B.C., Canada, Paper No. 45. Nakamura, Y., 1989. A method for dynamic characteristics estimations of subsurface using microtremors on the ground surface. Q. Rep., RTRI, Japan 30, 25–33. Nakamura, Y., 1997. Seismic Vulnerability Indices for Ground and Structures Using Microtremor. World Congress on Railway Research, Florence, Nov 1997. NEHRP, 2004. For Seismic Regulations for New Buildings and Other Structures (FEMA450) 2003 Edition, Prt 1. Provisions, Building Safety Council for the Federal Emergency Management Agency, National Institute of Building Sciences, Washington DC. Nogoshi, M., Igarashi, T., 1971. On the amplitude characteristics of microtremors. J. Seismol. Soc. Jpn. 24, 24–40. Okada, H., 2003. The Microtremor Survey Method. Geophysical Monograph Series, Series 12. Society of exploration geophysics. Okada, H., 2006. Theory of efficient array observations of microtremors with special reference to the SPAC method. Explor. Geophys. 37, 73–85. Parolai, S., Bormann, P., Milkereit, C., 2001. Assessment of the natural frequency of the sedimentary cover in the Cologne area (Germany) using noise measurements. J. Earthq. Eng. 5, 541–564. Parolai, S., Bormann, P., Milkereit, C., 2002. New relationships between Vs, thickness of
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Journal of African Earth Sciences journal homepage: www.elsevier.com/locate/jafrearsci
Site characterization using passive seismic techniques: A case of Suez city, Egypt
T
Mostafa Tonia,∗, Toshiaki Yokoib, Medhat El Rayessc a
Geology Department, Faculty of Science, Helwan University, Cairo, Egypt International Institute of Seismology and Earthquake Engineering (IISEE), Building Research Institute (BRI), Tsukuba, Japan c National Research Institute of Astronomy and Geophysics (NRIAG), Helwan, Cairo, Egypt b
A R T I C LE I N FO
A B S T R A C T
Keywords: Microtremor Suez city SPAC CCA HVSR AVS30 Predominant frequency
This article introduces a site investigation study using quick and low-cost passive seismic techniques at Suez city which located in the northeastern part of Egypt. The Spatial Auto Correlation (SPAC) method is applied, as well as the newly developed Centerless Circular Array (CCA) method for estimating the shear wave velocity (Vs) structures of the subsurface layers using microtremor array data. The Horizontal/Vertical Spectral Ratio (HVSR) approach is employed in determination of predominant frequency (f0) of a site and its equivalent peak amplitude of ground motion (A0) using a single station microtremor measurements. In this study, microtremor array measurements have been carried out at five sites distributed in Suez city. In order to cover a wide frequency band, different array sizes are carried out at each observation site. Measurements are made using high performance accelerometers with a sampling rate 100 sample per second. In both SPAC and CCA methods, only the vertical component of microtremor data is considered in the analysis. The analysis includes two main stages, i.e., calculation of surface wave dispersion curves and inversion process to infer the Vs structure of the ground. The obtained dispersion curves cover frequency band (2.0–21.0 Hz) and show a good fitting between the observed and the calculated ones at all measured sites, proving the reliability of the inversion process performed in this work. In HVSR analysis, the E-W, N-S, and vertical components of microtremors are considered, and the ratio between the horizontal and the vertical components spectra is calculated, then the spectral ratio curves are produced. The predominant frequency (f0) and the peak amplitude (A0) of HVSR curve are reported for each site of observation. The inferred Vs profiles are used for calculating the average velocity value of shear wave up to 30 m depth (AVS30) which in turn employed in site classification at the investigated area. The results demonstrate that the parameter AVS30 varies between 248 m/s and 310 m/s in Suez city. The created site classification incorporates only one class (Class D), appearing no significant variation in the characteristics of the superficial and shallow soils in Suez city. The site predominant frequency (f0) ranges between 0.35 Hz and 5.0 Hz with relevant amplification (A0) between 1.6 and 4.2. These outputs represent a crucial site response model for future seismic hazard assessment and risk decrease studies in Suez area which is currently witnesses large investments and rapid land use planning.
1. Introduction Passive seismic techniques using microtremors (also known as ambient noises) gained in the last few decades an essential role in many seismological investigations. They are often employed in determination of Vs structure of the ground and estimate the parameter AVS30 which is used in building codes for seismic site classification. Also, microtremor techniques are widely used in determination of the site predominant frequency and its equivalent amplification of ground motion.
∗
Among the advantages of using passive techniques in site investigations is the possibility of using them in the urban environments without causing disturbance to inhabitants and neighboring buildings. Moreover the frequency content of microtremor covers a wider range which makes it possible to investigate deep structures in low cost and limited time and personnel requirements comparing with active techniques which are costly and offer a restricted investigation depths. In this work, three passive seismic techniques using microtremor data are used in determination of the dynamic properties of subsurface
Corresponding author. E-mail address: [email protected] (M. Toni).
https://doi.org/10.1016/j.jafrearsci.2019.05.004 Received 11 February 2019; Received in revised form 3 May 2019; Accepted 3 May 2019 Available online 06 May 2019 1464-343X/ © 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. Location map of the study area showing microtremor observation sites and locations of drilling data.
Aqaba where the transform fault system is the predominant tectonic force. Prime examples of earthquakes that had been reported from this source are the 3 August 1993 (Mb 5.8) earthquake, the largest earthquake (Mw 7.3) of 22 November 1995, and the 27 June 2015 (Mb 5.2) earthquake (Abd el-aal and Badreldin, 2016; Badreldin et al., 2019). The northern Red Sea where the triple junction of the relative motion between Arabian plate, African plate, and Sinai sub-plate occurs represents another seismic source that has a significant impact on Suez city. Moreover, Suez city is affected from the western side by the intraplate seismotectonic activity of Cairo-Suez district. The area under investigation is located on the Suez Canal region of in the western side of Suez Gulf. In view of the geological setting of Suez Canal region, it can be stated that this region occupies a semi-flat terrain with ripple marks extend from North to South. High topographic land (e.g., up to 234 m above sea level in G. Genifa (mountain) and 226 m above sea level in G. Shabraweet (mountain)) rises toward the west and the northwest of the study area (Said, 1962; El Shazly et al., 1975; Ramadan, 1984; Geriesh, 1999). Salem (1988) analyzed the structural features in the area under investigation and its environs to determine the style of deformation and stress directions that influence this region and reported that it mostly affected by normal faults and few diagonals with major dip-slip and minor strike-slip components. By focusing on the area where microtremor measurements have been conducted, it is covered by deposits that belong to Miocene-Pliocene and Quaternary ages. The Miocene-Pliocene deposits are composed of gravel, sand, clay, and limestone with sandstone and clay, while Quaternary deposits are composed of sandy clay, sabkhas (a type of marine deposit), gravels, gypsum, beach sand, wadi alluvium and sand dunes (Said, 1962; El Shazly et al., 1975; Geriesh, 1999; Hegazi et al., 2013). Shallow drilling data (up to 15 m depth) is available from four locations in the investigated area (Fig. 1) and used in description of subsurface soil (Fig. 2). As shown in the graphical description depicted in Fig. 2, there are no significant lateral variation in the subsurface soil within the investigated area, and the soil composed mainly of limy clayey shale and sand with different cohesion degrees. This study represents the first application of SPAC and CCA techniques in Suez city in combination with the HVSR method for site characterization. The expected model of the site dynamic characteristics represents a major input parameter for future seismic hazard assessment and risk reduction studies in the Suez area.
soil layers at Suez city, which located in the northeastern portion of Egypt (Fig. 1). For the first time the new developed CCA technique (Cho et al., 2006 a; b) is applied in Egypt in combination with the SPAC method (Aki, 1957) after its previous applications by Toni et al. (2016 a,c) and Maklad (2017). The most common HVSR method (Nakamura, 1989&1997) is also applied. Both SPAC and CCA are used to retrieve the shear wave velocity (Vs) structure of the subsurface soils, while the HVSR is used in determination of the site predominant frequency (f0) and its equivalent peak amplitude of ground motion (A0). The resulted Vs structural models are used in determination of AVS30, which in turn used in classification of the surface soil at the investigated area. The Suez city (i.e. the case of the present study) is a naval-port city in northeast Egypt, located on the north coast of the Gulf of Suez, at the southern gateway of Suez Canal (Fig. 1). The Suez city is the capital of a governorate that holds the same name, covering a surface area 250 km2, and populated with about 744,000 in 2018 (https://en.wikipedia.org/ wiki/Suez). The importance of Suez city comes from its location on the Suez Canal which is an artificial waterway connecting the Mediterranean Sea to the Red Sea with a total length of about 193 km. Moreover, the industrial section of the city includes many factories working mainly in the petroleum sector and a commercial port that is utilized for shipping merchandise between many countries around the Red Sea region. Currently, the region witnesses development of large strategic projects such as the digging of a new canal parallel to the present Suez Canal to increase its capacity by permit sailing in both directions simultaneously. Besides, new logistic and ship services centers are built along the Suez Canal, making the city a vital trading center globally. From a seismological view point, the city of Suez is surrounded by seismic sources of low to moderate activity. Among these sources is the Gulf of Suez where the Red Sea rifting system exists. In this zone, the largest earthquake (ML 6.7) in the recent history occurred in the gateway of the Suez Gulf on 31 March 1969 (McKenzie et al., 1970). Another earthquake was reported in the same area on 28 June 1972 with magnitude Mb 5.6 (Ben-Menahem et al., 1976). The most significant events that recorded from the Gulf of Suez in the past few years are: The 30 January 2012 earthquake with local magnitude ML 4.6 which occurred in the very south of the Gulf of Suez (Hosny et al., 2013), the 22 January 2013 (ML 4.1) and the 1 June 2013 (ML 5.1) earthquakes which occurred in the central Gulf of Suez with similar epicenter and different depths (Toni et al., 2016b; Toni, 2017). The area of Suez is also influenced by the earthquake activity from the Gulf of 2
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ρ (rAB, ω) =
1 2π
1 = 2π
2π
∫ 0 2π
Re{E [CA,B (ω)]} dθ E [CA, A (ω)]
∫ exp[ikrAB cos(θ −
∅)] dθ = J0 (krAB) (1)
0
where ρ(rAB,ω) is the SPAC coefficient from microtremors, rAB and θ are the distance and the azimuth respectively between two observation points xA and xB, ∅ is the azimuth along which the incidence of waves takes place, and k denotes the wavenumber. The CA,B(ω) denotes the cross spectra of the records obtained at the observation points xA and xB. Yokoi (2010) reported that the term (E[CA,A(ω)]E[CB,B(ω)])1/2 could be used instead of E[CA,A(ω)] to correct local ground amplification. The wavenumber k(ω) can be estimated by fitting J0(kr) with the observed SPAC coefficient. The phase velocity c(ω) = ω/k(ω) is calculated for each frequency using ω2πf; then c(ω) can be inverted to a layered ground structure of density and velocities (Vp and Vs) by using the inversion techniques; e.g., the Heuristic Search (e.g., Lomax and Snieder, 1994), the Simulated Annealing (e.g., Sen and Stoffa, 1991), and the Neighborhood Algorithm (e.g., Sambridge, 1999a,b). Alternatively, the direct search for underground structures that gives the best fit with SPAC coefficient can be used (e.g., Asten et al., 2004; Wathelet et al., 2005&, 2008). The analysis procedures of SPAC method are depicted in Fig. 3. For more details about SPAC method, the reader is referred (Okada, 2003; Wathelet et al., 2005; Tada et al., 2007; Yokoi, 2010; Foti et al., 2018). 2.2. CCA Another approach used in this study is the newly developed CCA technique (Cho et al., 2004 & 2006a) which is effective for analyzing microtremors of small size array (mini-array) based on a theory derived by generalizing SPAC method (Cho et al., 2006b). The CCA method uses vertical component of microtremors for determining the Rayleigh wave phase with wavelengths exceeding several ten times the array radius (Cho et al., 2004 & 2006 b,c). Cho et al. (2013) pointed that the CCA method could identify the phase velocities using a circular array with radius (r). Analysis limit of the shortest-wavelength in CCA equals 2r, while the longest-wavelength analysis limit is determined by the signalto-noise ratio (SNR). When the SNR becomes large, the resolving power of long wavelengths is higher in CCA method than in SPAC method (Cho et al., 2006a). The CCA coefficient is defined as follows (Cho et al., 2006a):
Fig. 2. Graphical description of the shallow subsurface soil beneath Suez city.
2. Methodology In this section we briefly describe the SPAC, CCA, and HVSR approaches which are employed in the analysis of microtremor data conducted in the current study.
π
s (r , ω) = 2.1. SPAC
PSD ∫−π Z (t , r , θ) dθ π −π
PSD ∫ Z (t , r , θ)exp(−iθ) dθ
=
J02 (rω/ c ) J12 (rω/ c )
(2)
where PSD is the power spectral density; Z(t,r,θ) is the microtremor vertical component observed at radius r, azimuth θ, and time t. The third part of equation (2) denotes the theoretical formula of the CCA coefficient, J1(rω/c), the first-order Bessel function of the first kind with the argument composed of the radius r, angular frequency ω, and phase velocity c. The numerator and denominator of the second part of equation (2) are the PSD of the zero and the first-order coefficients of the Fourier expansion over the azimuth, respectively, whereas the SPAC use its zero-order term alone (Cho et al., 2006b; Yokoi, 2010). The central station is used to determine the influence of the incoherent components of microtremors and to correct the results of analysis for those unwanted effects, however it is not indispensable in situations where incoherent noises are expected to be negligible (Yokoi, 2010). Among the advantages of CCA method is the possibility to cover a wide frequency range using only a small radius circular array. In contrast, the SPAC requires arrays of different sizes to be combined because only a narrow kr range is available for accurate determination of the phase velocity (Apostolidis et al., 2004; Tsuno and Kudo, 2004). This is because at small kr the resolution is low, whereas at large kr the SNR is
The SPAC method is an effective tool to estimate the Vs structure below a site of investigation by dispersion analysis of the propagating surface waves. It is based on the theory of stochastic process proposed by Aki (1957&1965). In recent years, the SPAC method has attracted attention in the community of earthquake engineering due to its easiness of application and its ability to investigate deep structures with reasonable cost (Morikawa et al., 2004; Wathelet et al., 2005; Asten, 2006; Okada, 2006; Köhler et al., 2007). Application of SPAC requires perfectly shaped arrays, typically it requires a single number of seismic stations distributed around a circle with equal azimuthal intervals plus a central station (Wathelet, 2005; Tada et al., 2007). Since the pioneering idea of Aki (1957&1965), the SPAC method underwent development by several researchers, from the most recent ones (e.g., Okada, 2003; Asten, 2006; Yokoi, 2010). The following general formula describes the principle underlying of SPAC:
3
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Fig. 3. The analysis procedures of SPAC method (Yokoi, 2017a).
Fig. 4. The analysis procedures of CCA method (Yokoi, 2017b).
low due to contamination by incoherent noises (Cho et al., 2008). Other notable advantages of CCA are: It implements mini-array which is easily available; the array observation is almost as easy as a single observation point to be carried out; furthermore, the site of installation requires a little effort because the installation can be deployed at small area such as a site at the roadside or in a little space in a parking parcel (Cho et al., 2013). All this makes the method very suitable for urban environments. The analysis procedures of CCA method are depicted in Fig. 4.
Fig. 5. Array configuration carried out in the present study. Four-point array with a triangular shape (left); four arrays with different sizes carried out at each observation site (right).
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Fig. 6. (Left): SPAC coefficient curves for small distance (distance between central station and any station on the triangle) and large distance (plane distance between any two adjacent stations on the circumference of a triangle) for each array size (48m, 24m, 12m, and 6m) of Array 3. (Right): Dispersion curve derived from SPAC analysis for Array 3, the frequency range between the first two green lines represents the reliable part, while the frequency range between the second green line and the third blue line represents the acceptable part of the dispersion curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 7. Power spectra of seismic stations (a); coherence curves between array's stations (b); CCA coefficient (c); and dispersion curve (d) derived from CCA analysis for the mini-array of site 3 as a representative example.
microtremor. This method was introduced by Nakamura (1989) based on the principles suggested by Nogoshi and Igarashi (1971), which in turn based on the initial studies of Kanai and Tanaka (1961). Due to the easiness of application in terms of data measurement and processing in addition to low expenses, the HVSR is vastly used in site effect studies and in a quick construction of microzonation maps mostly in urban settlements. A peak amplitude appears on the HVSR curve due to the dissimilarity between the uppermost sediments and the underlying rock at the site of observation. The peak frequency is considered to be the site fundamental frequency (f0), while the peak amplitude (A0) is directly related to velocity contrast, i.e. sharp velocity contrast yields large H/V peak amplitude, and vice versa (SESAME, 2004). The Fourier spectral ratio between the horizontal and vertical (H/V) components of microtremors can be expressed as follow:
Table 1 Site classification scheme of NEHRP (2004). Site class
Description
AVS30 (m/s)
A B C D E
Hard Rock Rock Very dense soil and soft rock Stiff soils Soft soils, profile with more than 10 ft (3 m) of soft clay Soils requiring site specific evaluations
> 1500 760–1500 360–760 180–360 < 180
F
–
2.3. HVSR The HVSR method is a simple and reliable technique to extract the site predominant frequency using three component measurements of 5
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using Fortran codes developed by one of the authors (Yokoi, 2017a,b) and GNUPLOT (http://www.gnuplot.info/) to plot the results. In both proposed techniques (SPAC and CCA), analysis of microtremor data focuses only on the record of vertical component where Rayleigh waves are supposed to be dominant. In general, the analysis includes two main stages: Determination of dispersion curves of surface wave, and inversion of the dispersion curve to derive the Vs structural profile of the ground. The procedures of data analysis include: data formatting, multiplexing, resampling, calculation of inter-station distances and azimuths, calculation of SPAC coefficient (in SPAC analysis) or CCA coefficient (in CCA analysis), and finally determination of dispersion curve (see Figs. 3 and 4). In the inversion stage, the Heuristic search of Vs structure was applied to retrieve the vertically 1D Vs profile (Yokoi, 2010). A representative example of the calculated SPAC coefficient and the equivalent dispersion curve obtained in the current analysis is shown in Fig. 6, while Fig. 7 shows an example of the power spectra calculated for seismic stations of the mini-array, the coherence curves between pairs of array's stations, the CCA coefficient, and dispersion curves obtained from CCA analysis. The inferred Vs profiles are here employed in the calculation of AVS30 (i.e. the average velocity value of shear waves in the top 30 m) at shear strain of 10−5 or less using the following relationship (Eurocode 8, 2003; CEN, 2004):
Fig. 8. Plot showing HVSR curves of all the measured sites in Suez city.
H / V (ω) = {[S2 (ω)NS + S2 (ω)EW]/ 2S2 (ω) V }1/2
(3)
AVS30 = 30 /
where [S(ω)NS and S(ω)EW] are the spectra of the two horizontal components north-south (NS) and east-west (EW) of microtremors, [S (ω)V] is the spectrum of vertical component (V), and ω is the angular frequency. Several studies (e.g., Field and Jacob, 1995; Bard, 2000; Parolai et al., 2001&2002; Mucciarelli and Gallipoli, 2004; SESAME, 2004; Turnbull, 2008; Gok and Polat, 2012; Gok et al., 2014) demonstrated that the HVSR method could adequately estimate the predominant frequency of a site, however the method still has some controversies regarding the estimation of site amplification factor. According to the European research project SESAME (2004), the HVSR method is useful in determination of the fundamental frequency of soil deposits, however, measurements and analysis require caution. On the other hand, the H/V peak amplitude represents an underestimate of the actual site amplification. The most recent study of Kawase et al. (2018), developed empirical corrections to Nakamura's method to evaluate directly the real site amplification from HVSR method. Application of the HVSR method is frequently used for site characterization at different localities in Egypt with reliable results (e.g., Mohamed and Fat-Helbary, 2010; El-Eraki et al., 2012; Mohamed et al., 2013&2015; Toni et al., 2016a; c; Abdel Hafiez and Toni, 2019).
∑ i = 1, N
hi vi
(4)
where hi and vi are the thickness (m) and the shear-wave velocity (m/s) respectively of the i-th layer, in a total of N, existing in the top 30 m of soil profile. As has been accepted in most international building codes i.e. National Earthquake Hazards Reduction Program (NEHRP, 2004) and Eurocode 8 (2003), the site is classified according to the AVS30 value. In this research the surface soil at Suez city is classified based on the estimated AVS30 values following the classification scheme of NEHRP (2004) which shown in Table (1). At each observation site in Suez city, microtremor record of one sensor has been chosen as a single station for HVSR analysis. Analysis was performed using the open access Geopsy software (http://www. geopsy.org) and focused on the frequency range (0.1–15 Hz). In such analysis, microtremor data relative to each ground motion component is split in the time domain into short time blocks (25–50 s) from the stable parts of the recorded signals, and to avoid transients from specific sources such as close traffics. Using the processing module of Geopsy software, microtremor data relative to each time block is transformed from time to frequency domain using the FFT, cosine tapered, and smoothed using Konno and Ohmachi's algorithm (Konno and Ohmachi, 1998). The two horizontal components (NS and EW) are merged with the quadratic mean to get the H component which in turn divided by the vertical component (V) to estimate the HVSR for each time block as follow:
3. Data set and analysis Microtremors have been conducted at Suez city in the western side of the Suez Canal. The date set includes microtremor recordings through an array of sensors at five observation sites distributed in Suez city (see Fig. 1). Each array comprises four seismic stations with a triangular shape (four-point array, three stations on the circumference of a circle and one at the center), which is a de-fact standard configuration for SPAC and CCA analysis (Fig. 5, left). In order to cover a wider range of frequencies, four arrays with sizes 48m, 24m, 12m, and 6m (Fig. 5, right) were carried out at each observation site (for SPAC analysis). Additionally, a mini-array with 2 m side length and radius (r = 1.16 m) has been carried out at each observation site (for CCA analysis). Measurements were made using high-performance accelerometer (McSEISMT NEO) from OYO Corporation. The signal was recorded in three components (North-South, East-West, and Vertical) with a sampling rate 100 sample per second and record duration 60 min (in small size arrays 2m, 6m, 12m) and 120 min (in larger size arrays 24m and 48m). In the present research, data processing (SPAC and CCA) is managed
HVSR (f ) =
NS (f ). EW (f ) V (f )
(5)
Finally, the spectral ratios relative to all time blocks are considered, then averaged to get the main spectral ratio curve (Fig. 8). The peak ground amlitude (A0) and its predominant frequency (f0) are defined for each spectral ratio curve corresponding to an observation site. Peaks from artificial sources such as machinery were treated with awareness, since they do not belong to the dynamic properties of the subsurface soil structure. 4. Results and discussions The Vs profiles resulted from SPAC and CCA analyses are plotted in Figs. 9 and 10 respectively. Both observed and calculated dispersion 6
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Fig. 9. Results of SPAC analysis: Observed and calculated dispersion curves (left); 1D Vs profile (right).
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Fig. 10. Results of CCA analysis: Observed and calculated dispersion curves (left); 1D Vs profile (right).
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Fig. 11. Comparison between dispersion curves derived from SPAC and CCA analyses (a), and Vs profiles inferred from SPAC (b) and from CCA (c) analyses of all the measured sites in Suez city.
Figs. 9 and 11b). The investigated depth in the Vs profiles show a good consistency with the minimum and maximum frequencies of the corresponding dispersion curves (Fig. 9). The results depicted in Fig. 10 show that the dispersion curves derived from CCA analysis of the mini-array cover frequency range between 4.0 Hz and 19.0 Hz and show a very good fitting between the observed and the calculated ones. The Vs profiles inferred from CCA analysis could investigate subsurface structures up to 37 m depth with high resolution, however arrays 1 and 5 investigated a very shallow depth (∼12m) because the dispersion curves of these arrays start at high frequency (over 9.0 Hz) as shown in Fig. 10 and in Fig. 11a,c. Comparing the dispersion curves derived from the two employed techniques (SPAC and CCA) reveals that the frequency bands of the dispersion curves derived from CCA analysis lay partially within the frequency range of those derived from SPAC analysis, and show in general lower amplitudes of phase velocities for CCA than SPAC curves (Fig. 11a). However, for Array 5 the dispersion curve derived from CCA analysis covers frequency band (11.2–19.0 Hz) and represents a high frequency extension of the dispersion curve derived from SPAC analysis (5.4–11.8 Hz) and shows higher amplitude of phase velocity than that obtained from SPAC (Fig. 11a).
Table 2 Results obtained in the investigated area. Site
Latitude
Longitude
AVS30 (m/s)
Site class
f0 (Hz)
A0
1 2 3 4 5
29.98544 29.99898 29.99453 29.96793 29.9545
32.55869 32.54071 32.51158 32.51951 32.56913
302.591 258.4 248.43 302.14 310.29
D D D D D
5.0 0.5 0.6 0.35 1.5
4.2 1.6 1.8 2.1 2.2
curves which were used in producing the Vs profiles through an inversion process are also shown in the same figures. The results demonstrate that the dispersion curves derived from SPAC analysis cover frequencies between 2.0 Hz and 21.0 Hz. The widest frequency band (2.0–20.4 Hz) is covered by Array 3, while the narrowest frequency band (5.3–11.8 Hz) is covered by Array 5 (Fig. 9). A good matching between the measured and the calculated dispersion curves is noticed for all arrays (Fig. 9), proving a reliability of the inversion process performed in the present study. The resulted VS profiles show shear wave velocity ranging from 130 m/s to 190 m/s at the surface layer and from 390 m/s to 585 m/s at the underlying rock (see 9
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In comparison with the previous work of Mohamed et al. (2016) in the western side of the Suez Canal area using a different technique (i.e. MASW method), the Vs profiles obtained in the current work demonstrate in general a good agreement with their results in terms of the frequency ranges covered by dispersion curves and the Vs value against investigated depths. Their results cover frequency range between 6.0 and 28.0 Hz with investigated depth up to 30m, however graphical comparison between our results and their results is not possible because the observation sites are not the same. Table (2) lists the values of AVS30 that have been estimated by averaging the shear wave velocities in shallow layers up to 30 m depth using equation (4). The classes of surface soils at the measured locations are also shown in Table (2) and reveal no considerable variance in the properties of the superficial and shallow soils in Suez city, since the whole investigated area has one site class (class D). The resulted HVSR curves are illustrated in Fig. 8. The site parameters extracted from these curves are the predominant frequency (f0) and its relevant amplification of ground motion (A0) at each site of observation. The results reveal that all the sites of observations at Suez city exhibit peak frequency value (0.35–5.0 Hz). Sites 3 and 5 exhibit more than one clear peak at HVSR curve (Fig. 8), which may be related to the presence of interfaces at different depths.
Aqaba earthquake and its sequence of aftershocks. J. Seismol. 20 (3), 935–952. https://doi.org/10.1007/s10950-016-9572-x. Abdel Hafiez, H.E., Toni, M., 2019. Ambient noise level and site characterization in northern Egypt. Pure Appl. Geophys. 1–18. https://www.doi.org/10.1007/s00024019-02112-8. Aki, K., 1957. Space and time spectra of stationary stochastic waves, with special reference to microtremors. Bull. Earthq. Res. Inst. Univ. Tokyo 35, 415–457. Aki, K., 1965. A note on the use of microseisms in determining the shallow structures of the earth's crust. Geophysics 29, 665–666. Apostolidis, P., Raptakis, D., Roumelioti, Z., Pitilakis, K., 2004. Determination of S-wave velocity structure using microtremors and SPAC method applied in Thessaloniki (Greece). Soil Dynam. Earthq. Eng. 24, 49–67. Asten, M., Dhu, T., Lam, N., 2004. Optimized array design for microtremor array studies applied to site classification; comparison of results with SCPTlogs. In: Proceedings of the 13thWorld Conference on Earthquake Engineering, Paper No. 2903. Asten, M.W., 2006. On bias and noise in passive seismic data from finite circular array data processed using SPAC methods. Geophysics 71, V153–V162. Badreldin, H., Abd el-aal, A.K., Toni, M., El-Faragawy, K., 2019. Moment tensor inversion of small-to-moderate size local earthquakes in Egypt. J. Afr. Earth Sci. 151 (2019), 153–172. https://doi.org/10.1016/j.jafrearsci.2018.12.004. Bard, P.-Y., 2000. Lecture Notes on ‘Seismology, Seismic Hazard Assessment and Risk Mitigation’. International Training Course, Potsdam, pp. 160. Ben-Menahem, A., Nur, A., Vered, M., 1976. Tectonica, seismicity and structure of the Afro-Eurasian junction—the breaking of an incoherent plate. Phys. Earth Planet. In. 12, 1–50. CEN, 2004. Eurocode 8—design of Structures for Earthquake Resistance. Part 1. General Rules, Seismic Actions and Rules for Buildings. European Standard EN 1998-1, December 2004. European Committee for Standardization, Brussels. Cho, I., Tada, T., Shinozaki, Y., 2004. A new method to determine phase velocities of Rayleigh waves from microseisms. Geophysics 69, 1535–1551. Cho, I., Tada, T., Shinozaki, Y., 2006a. Centerless circular array method. inferring phase velocities of Rayleigh waves in broad wavelength ranges using microtremor records. J. Geophys. Res. 111, B09315. https://doi.org/10.1029/2005JB004235. Cho, I., Tada, T., Shinozaki, Y., 2006b. A generic formulation for microtremor exploration methods using three-component records from a circular array. Geophys. J. Int. 165, 236–258. Cho, I., Tada, T., Shinozaki, Y., 2006c. New methods of microtremor exploration. the centerless circular array method and the two-radius method. Third International Symposium on the Effects of Surface Geology on Seismic Motion, vol 1. Laboratoire Central des Ponts et Chaussées, Paris, pp. 335–344. Cho, I., Tada, T., Shinozaki, Y., 2008. Assessing the applicability of the spatial autocorrelation method. A theoretical approach. J. Geophys. Res. Sol. Earth 113 (B6). Cho, I., Senna, S., Fujiwara, H., 2013. Miniature array analysis of microtremors. Geophysics 78 (1), KS13–KS23. El-Eraki, M., Mohamed, A.A., El-Kenawy, A.A., Toni, M.S., Imam, S.M., 2012. Engineering seismological studies in and around Zagazig city, Sharkia, Egypt. NRIAG J. Astro. Geophys. 12/2012 (2), 141–151. https://doi.org/10.1016/j.nrjag.2012.12.009. 1. El Shazly, E., Abdel Hady, M., Salman, A., Morsy, M., El Rakaiby, M., El Assy, I., Kamel, A., Meshref, W., Ammar, A., Meleik, M., 1975. Geological Investigations of theSuez Canal Zone, vol 1975. Academy of Scientific Research and Technology, Cairo, pp. 54. Eurocode 8, 2003. Design of Structures for Earthquake Resistance - Part 1. General Rules, Seismic Actions and Rules for Buildings. English Version, Ref. No. (prEN 1998-1. 2003 E). Management Centre. rue de Stassart, Brussels, pp. 36 B-1050. 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5. Conclusions This study aims to illuminate the site characteristics in Suez city which located on the Suez Canal in the northeastern portion of Egypt. Three passive seismic techniques (SPAC, CCA, and HVSR) using microtremor measurements have been employed to achieve the objectives of this study. The gained results allow making the following conclusions: 1 The parameter AVS30 varies between 248 m/s and 310 m/s, showing only one site category (Class D), which means that there are no considerable differences in the characteristics of the superficial and the shallow soils in Suez city. 2 The estimated site predominant frequency (f0) using microtremor HVSR method is reliable, while the estimated peak ground amplitude (A0) represent the lower threshold of the real site amplification (SESAME, 2004). 3 The employed techniques (SPAC, CCA, and HVSR) could successfully investigate reliable shear wave velocity structures and site response parameters in reasonable cost and without causing disturbance to inhabitants and buildings in Suez city. 4 The output of this study may represent a good model of the site dynamic parameters which is necessary for seismic hazard and risk reduction studies in Suez city which witnesses large investments and rapid land use planning, however intensive measurements are recommended for reliable seismic microzonation. Acknowledgments This study is funded by the Science and Technology Development Fund (STDF), Egyptian Ministry of Higher Education and Scientific Research through STF project (ID 25397). The authors are very grateful to the Department of Seismology, National Research Institute of Astronomy and Geophysics (NRIAG), Cairo, Egypt for kind support in microtremor data measurement. The authors are also very grateful to the International Institute of Seismology and Earthquake Engineering (IISEE), Building Research Institute (BRI), Tsukuba, Japan for hosting the project's PI and providing him with all scientific facilities to perform this study. References Abd el-aal, A.k., Badreldin, H., 2016. Seismological aspects of the 27 June 2015 Gulf of
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