315
Indonesian Journal of Science & Technology 6 (2) (2021) 315-336

Indonesian Journal of Science & Technology
Journal homepage: http://ejournal.upi.edu/index.php/ijost/

Relationship between Shear Velocities Recorded by
Microtremor Observations and Seismic Cone Penetration
Test Results
Rusnardi Rahmat Putra1*, J. Kiyono2, Sai K. Vanapalli3, Y. Ono4
1

Faculty of Engineering, Universitas Negeri Padang, Jl Prof. Dr. Hamka, Padang, 25171, Indonesia
Graduate School of Engineering, Urban Management Department, Katsura Campus, Kyoto University
Nishikyo, Kyoto 615-8540, Japan
3
Faculty of Engineering, Department of Civil Engineering, University of Ottawa, 161 Louis-Pasteur St. Room
A015 (CBY) Ottawa ON K1N 6N5 Canada
4 Faculty of Engineering, Civil Engineering Department, Tottori University 4-101 Koyama Minami, Tottori city
680-8552, Japan
2

Correspondence: E-mail: rusnardi.rahmat@ft.unp.ac.id

ABSTRACT
This research proposes a relationship between two methods
such as a numerical approach by conducting a microtremor
array observation and field survey by using the seismic cone
penetration test unit (SCPTu). A database of shear-wave
velocity (Vs) measurements was established using the
microtremor array technique and seismic cone penetration
test unit (SCPTu) on high-quality samples of rock and soft soil
in Padang city, Indonesia. The study also demonstrates that
the Vs values obtained from the different methods are
consistent with the microtremor array technique. This
technique may thus be deemed a valuable tool, as it can be
used in engineering practice with confidence. Comparison of
the Vs for different soils at the first layer between the
microtremor array observation results and the SCPTu results
exhibited the microtremor array method is unable to
determine the Vs at the layer where its Vs changes
dramatically, such as at the same layer as station UNP at 2 to
3.5m deep.
© 2021 Tim Pengembang Jurnal UPI

ARTICLE INFO
Article History:
Submitted/Received 20 June 2020
First revised 19 March 2021
Accepted 14 May 2021
First available online 16 May 2021
Publication
date 01 Sep 2021
____________________
Keywords:
Microtremor Array,
Shear Velocity,
Soil Characteristics.

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 316

1. INTRODUCTION
The location of Padang city is on the west
coast of the island of Sumatra. The city is on
the western part of Indonesia. It is situated
nearby the Sumatran subduction zone and
on the fault line formed on the IndoAustralian plate beneath the Eurasian plate.
The plates' movement is about 50 to 70
mm/year. The plates activity is associated
with the seismicity in the area (Genrich et
al., 2000) and (Prawirodirdjo et al., 2000).
The most recent earthquake in the Padang
region occurred on 30 September 2009. The
epicenter of this earthquake was in the
ocean slab of the Eurasian plate of
Indonesia at a depth of 80 km, specifically
at -0.81°S, 99.65°E. It produced a ground
motion that contributed to a high degree of
shaking and tremors that were felt within a
radius of approximately 923 km from the
epicenter, including the Indonesian capital
Jakarta as well as the neighboring countries
of Malaysia and Singapore (Parker et al.,
2020).
According to seismicity records, the fault
line in the Sumatra island region
contributes to destructive earthquakes. The
earthquakes typically occur at shallow
depths of 10 km to 100 km (Figure 1). This
powerful earthquakes significantly affect
the infrastructure, economy, and society of
Padang (Putra et al., 2014). The average
seismic shear-wave velocity from the
surface to a depth of 30 meters (Vs30) is
used as the fundamental parameter to build
an earthquake-resistant building (Thein et
al., 2015; Putra et al., 2017; Sutrisno et al.,
2017). Seismic hazard and risk analyses for
Padang city were conducted in 2012 (Putra
et al., 2012; Putra et al., 2014), yielding data

regarding local soil properties, especially
the shear-wave velocity (Vs). The research
was
conducted
at
four
surface
accelerometer stations of the monitoring
network.
The subsurface soil in the Padang has
unconsolidated sediments as well as
heterogeneous composition and properties
(Lanin et al., 2019; Rosyidi et al., 2011).
Numerous different methods were applied
to obtain in situ Vs values to a target depth
of at least 30 m, or the maximum capacity
penetration of the cone: as much as 22
MPa for SCPTu. The techniques include
seismic cone penetration tests (SCPT) with
varying source offsets and microtremor
array observation on Rayleigh waves with
different processing approaches. SCPT
proved to be a powerful and cost-effective
approach in determining representative Vs
profiles at the selected soil type (McGann
et al., 2015; Pradono et al., 2019), such as
soft soil for two stations (UNP and FTB) and
a rock type for another (ADS).
The measured Vs profiles corresponded
closely with the modeled profiles and
significantly enhanced the ground motion
model’s derivation (Sofyan, 2016);
moreover, the level of similarity between
the theoretical transfer function from the
Vs profile and the observed amplification
from vertical array stations was excellent
(Noorlandt et al., 2018), opposite from
advantage, the used SPTu for this research
is heavy to carry. This paper describes how
this observation was conducted and how
the procedures to attain clear information
regarding the shear velocity (Vs), the
relationship between the microtremor
array results, and the seismic cone
penetration unit (SCPTu).

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

317 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

Figure 1. Seismicity details (a) Earthquake seismicity of Sumatra, Mw > 4 from 1779–
2020 (b) the September 2009 Padang earthquake (red circle is the epicenter).
2. METHODS AND SETUP
2.1 Overview
The research was conducted in Padang
City from 2009-2018. Padang is the capital
city of West Sumatra province, Indonesia.
The location of Padang city is at 100.38°E,
0.95°S. The main part of Padang city is
located on an alluvial plain between the
Indian Ocean (offshore) and the mountains.
Almost all the mountainous area is
composed of tertiary sedimentary rocks,
with outcrops of metamorphic rocks in
some places (ONO et al., 2012) and (Putra,
2020b). The alluvial plain spreads along the
base of the mountains and is roughly 10 km
wide in the east-west direction and 20 km
wide in the north-south direction (Figure 2).
The shallow subsurface in the Padang city
region is of heterogeneous composition as
a result of the microtremor array
observation from a previous study.
The location of this city is between the
the Indian Ocean, the Sunda Trench fault,

and the Sumatran fault. The two faults are
active. The slip rates of the faults are from
10 to 27 mm/year (natawidjaja & triyoso,
2007) and (Sieh & Natawidjaja, 2000).
Based on our records, there are 2,995
events occurred in this region with a
magnitude greater than four from AD 1779
to 2010 (Putra, R.R et al., 2014; Putra, R.R
2020). There were seven giant earthquakes
occured in this area. One of the earthquake
was in 2009 Padang. The earthquake was
located in the ocean slab of the IndoAustralian plate. It caused extensive
shaking and damage to houses and
buildings in Padang and Padang Pariaman,
due to the epicenter location (Juliafad et al.,
2021). Its epicentre was about 60 km
offshore from Padang (Figure 1.b).
Fortunately, the earthquake did not
generate a tsunami given that it was an
intra-slab earthquake. It was also at
intermediate depth with comparable
magnitude.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 318

Figure 2. Topography of Padang.
A database of shear-wave velocity (Vs)
measurements using the microtremor array
technique and the seismic cone penetration
test unit (SCPTu) on high-quality samples
for rock and soft soil in Padang region sites
has been established. Experimental
microtremor studies were also verified
using the analytical model proposed by
(Tavakoli et al., 2016), which provided
reasonably good comparison of Vs for the
subterraneous alluvium. The SCPTu results
proved to be a useful and cost-effective
approach in determining representative
values of Vs. The purpose of this study was
to evaluate the different methods of
measuring Vs, as well as to develop
guidelines and correlations to assist in
estimating the Vs profiles of clayey soils in
Padang and nearby regions in the absence

of site-specific data. Such relationships can
be used in first-order estimates of Vs values
from conventional soil properties. It was
found that reliable and reproducible
measurements of Vs can be obtained from
the microtremor array technique for use in
practical engineering applications.
The Vs values obtained from the
different methods are similar to the data
derived from the microtremor array
technique (Putra et al., 2014), such as from
field survey studies suggesting that the
SCPTu method is a convenient, fast and
fairly accurate method to derive Vs values
(Khazaei, Amiri & Khalilpour, 2017) and
(Thornley et al., 2019). A summary of the
survey setup for the two different shearwave methods is presented in Table 1.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

319 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

Table 1. Summary of survey setup for the two different shear-wave methods.
Sources
Receiver
Remark

Depth of investigation
Lateral average
Vertical resolution

SCPT
Steel beam and sledgehammer at
2.5m
Three
component
accelerometers in SCPT cone
Vertical sample interval, max 1.0
m, coinciding with stratigraphical
translation

4-18m
2.5 m
High, except shallow part

Microtremor array
Ambient noise
Three component acceleration sensors,
GPL-6A3P,
Recording of ambient noise at 1, 3, 7 and
30 m for one station. Sampling
frequency is 100 Hz and 200 Hz;
recording ground motion duration from
10 to 30 minutes.
Up to -102m and ~
Up to 30m
Medium decreasing with depth

θ
r

Figure 3. A four-point array observation.
2.2 Microtremor Array Observations
We conducted microtremor array
investigations on 12 sites in several districts
in Padang (Figure 4). The sampling
frequency used was 100 Hz and 200 Hz,
with recording ground motion duration
from 10 to 30 minutes and an array radius
from 1m up to 1km for each observation.
Figure 3 provides a succinct summary of the
four-point array technique used in the

present study. The site coordinates are
0°54′46.7″S, 100°27′53.7E″, 0°55′45.3″S
100°21′26.5″E,
and
0°53′52.1″S,
100°20′56.2″E for ADS, FTB and UNP
respectively.
We followed the SPAC method to
calculate the dispersion curves to estimate
a velocity structure from the microtremor
recordings (Nakamura, 2000; Carniel,
Barazza & Pascolo, 2006). In this study, we
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 320

used the SPAC methods only. SPAC is a
method of calculating the phase velocity
from different frequencies of the Bessel
function by taking the average of the

normalized coherence function. It is
defined as the spectrum from a site pair on
the array.

Figure 4. SPAC method flow chart.

Figure 5. The 12 array observation sites; red circles are the compared observation
stations ADS (right), FTB and UNP (left).
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

321 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

The outline of the SPAC method for the
𝑅𝑒(𝑆𝑃𝐴𝐶(𝜔, 𝑟))
phase velocity calculation of Rayleigh
1 2𝜋
𝜔𝑟
=
∫
cos(𝑖
𝑐𝑜𝑠𝜑)𝑑𝜑
waves is as follows:
2𝜋 0
𝑐(𝜔)
∞
1
𝜔𝑟
𝐹(𝜔) =
∫ 𝑓(𝑡) ∙ 𝑒𝑥𝑝(−𝑖𝜔𝑡)
𝐽(
)
2𝜋 −∞
𝑐(𝜔)
(1)
1 2𝜋
𝜔𝑟
(11)
= 𝐴𝑓 (𝜔) ∙ 𝑒𝑥𝑝 (−𝑖∅𝑓 (𝜔))
=
∫
𝑒𝑥𝑝(
𝑐𝑜𝑠𝜑)𝑑𝜑
∞
2𝜋 0
𝑐(𝜔)
1
𝐺(𝜔) =
∫ 𝑔(𝑡) ∙ 𝑒𝑥𝑝(−𝑖𝜔𝑡) 𝑑𝑡
2𝜋 −∞
(2)
where Jo(x) is the zero-order Bessel
= 𝐴𝑔 (𝜔)𝑒𝑥𝑝 (−𝑖∅𝑔 (𝜔))
function of the first x, and c(ω) is the phase
(𝜔)，𝐴
(𝜔)
𝐴𝑓
and ∅𝒇 are differences velocity at ω frequency. The SPAC
𝑔
between the amplitude of ∅𝑔 (𝜔), coefficient ρ(r,ω) can be taken from the
𝐹(𝜔) 𝑎𝑛𝑑 𝐺(𝜔),respectively. Futher cross- frequency domain using the Fourier series
of
the
observed
correlation in the frequency region of the transformation
microtremors. From the SPAC coefficient
two waveforms will be as follows:
ρ(r,ω), the phase velocity is calculated for
̅̅̅̅̅̅̅
𝐶𝐶𝑓𝑔 = 𝐹(𝜔) ∙ 𝐺(𝜔)
(3) different frequencies from the Bessel
= 𝐴𝑓 (𝜔) ∙ 𝐴𝑔 (𝜔) ∙ 𝑒𝑥𝑝(𝑖∆∅(𝜔))
function. Equation 11 and the velocity
This shows the phase difference
model can be inverted. The layer thickness
of∆∅(𝜔)
and the average S-wave velocity at each
𝜔𝑟
∆∅(𝜔) =
(4) array site can be estimated. The average S
𝑐(𝜔)
𝑐(𝜔) is the phase velocity from the phase wave velocity model was obtained by taking
the average of the estimated ground
difference.
structure of the array site. It was calculated
𝜔𝑟
𝐶𝐶𝑓𝑔 = 𝐴𝑓 (𝜔) ∙ 𝐴𝑔 (𝜔) ∙ 𝑒𝑥𝑝 (𝑖
)
(5) by a weighted average using an S-wave
𝑐(𝜔)
The complex coherence of two velocity structure for a weighted layer
waveforms is defined by the following thickness.
equation:
𝐶𝐶𝑓𝑔 (𝜔)
𝐶𝑂𝐻𝑓𝑔 (𝜔) =
𝐴𝑓 (𝜔) ∙ 𝐴𝑔 (𝜔)
𝜔𝑟
= 𝑒𝑥 𝑝 (𝑖
)
𝑐(𝜔)
𝜔𝑟
𝑅𝑒 (𝐶𝑂𝐻𝑓𝑔 (𝜔)) = cos (𝑖
)
𝑐(𝜔)
𝑐(𝜔)
𝑐(𝜔, 𝜑) =
𝑐𝑜𝑠𝜑
𝑆𝑃𝐴𝐶(𝜔, 𝑟)
1 2𝜋
𝜔𝑟
=
∫ 𝑒𝑥𝑝(𝑖
𝑐𝑜𝑠𝜑)𝑑𝜑
2𝜋 0
𝑐(𝜔)

𝜔𝑟

𝑅𝑒(𝑆𝑃𝐴𝐶(𝜔, 𝑟)) = 𝐽 (𝑐(𝜔))

(12)

From the SPAC coefficient ρ(r,ω), the
phase velocity is calculated for every
frequency from the Bessel function
(6)
argument of equation 12, and the velocity
model can be inverted. The layer thickness
and the average S-wave velocity for each
(7)
array site were determined. The average Swave velocity model, obtained by
(8)
averaging the estimated ground structure
of the array site. It was calculated by a
weighted average using an S-wave velocity
structure estimated as a weighted layer
(9)
thickness. Figure 7 shows an example of the
dispersion curve obtained using the array
(10) observations.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 322

Figure 6. Phase velocity from SPAC and CCA method at several sites in Padang, (a) Station
FTB, (b) Station UNP and (c) ADS.

Figure 7. Dispersion curve at several sites in Padang; (a) Rock at station ADS, (b) Soft
type at station FTB, (c) Soft type at station UNP.
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

323 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

By conducting an inversion analysis
using the particle swarm optimization
(PSO) algorithm on the above dispersion
curves, the subsurface structure beneath
the site can be estimated. The PSO is a
solution method for a non-linear
optimization problem (Chopard &
Tomassini, 2018). We estimated the
subsurface structure of the model by
minimizing the difference between the
observed and theoretical phase velocity
curves. We estimated the subsurface
structure of the model by solving a
nonlinear minimization problem with the
fitness function below.

explained by the estimated subsurface soil
structure. In this study, we used the two
distinct peaks in the observed H/V spectra
and Vs structure obtained by array
observation. The technique used was the
1/4 wavelength principle, which can
approximately be extended to multilayered media.

2.3 Determination of Layer Thickness

𝑇𝑝 ∑𝑛𝑖=1 𝑉𝑆𝑖 ∙ 𝐻𝑖
𝐻 =
(15)
∑𝑛𝑖=1 𝐻𝑖
4
where H is a thickness of a layer. Here we
divided the ground into three layers: the
upper two layers and a base semi-infinite
layer. The range of the shear wave velocity
for the first, second and third layers was
assumed: (I) Vs ≦ 300 m/s; (II) 300 < Vs <
300 m/s; (III) Vs ≧ 3000 m/s.
The target area is shown in Figure 8(a),
in which the rapidly varying area of the
subsurface
condition
and
dense
observation area are enclosed. The ground
model was constructed as follows: the
rectangular area (about 10 km x10 km) in
Figure 8(a) was divided into100*100
meshes (100 m square). According to the
Kriging technique, the values of
predominant periods Ts and T at the centre
of each mesh are interpolated by using the
finite number of peak periods read from
the observed H/V spectrum.
In Figure 9 (a) at station ADS shows the
Vs from 0-4m depth is average 308.8m/s
corresponds to relatively rock type and (b)
at station FTB from the Vs from 0- 18 m
(green line) is average 169.3m/s and at
station UNP from the Vs from 0- 16 m
(yellow line) is average 169m/s correspond
to relatively soft type at the first layer.
Three of the 12 observation sites were
considered for evaluating the relationship,
one each for rock at station ADS (Vs >
300m/s) and two for soft soil at FTB and
UNP (Vs < 200m/s) (Figure. 5).

The peaks in the short and long periods
of the observed H/V spectrum could be

3. Seismic Cone Penetration Test unit
(SCPTu)

𝑡+1
𝑡
𝑡
𝑡 )
𝑡
𝑡
𝑣𝑖𝑑
= 𝜔 𝑣𝑖𝑑
+ 𝑐1 𝑟1 (𝑝𝑖𝑑
− 𝑥𝑖𝑑
+ 𝑐2 𝑟2 (𝑝𝑔𝑑
− 𝑥𝑔𝑑
)(13)

𝑡+1
𝑡
𝑡+1
𝑥𝑖𝑑
= 𝑥𝑖𝑑
+ 𝑣𝑖𝑑

(14)

𝑡
where 𝑣𝑖𝑑
is the particle velocity of the 𝑖 𝑡ℎ
component in dimension d in the
𝑡
interaction, 𝑥𝑖𝑑
is the particle position of
𝑡ℎ
the 𝑖 component in dimension d in the
interaction, 𝑐1 and 𝑐2 are constant weight
factors, 𝑝𝑖 is the best position achieved by
particle 𝑖, 𝑝 𝑔 is the best position found by
the neighbour of particle 𝑖, 𝑟1and 𝑟2 are
random factors in the [0,1] interval and 𝜔 is
the inertia weight. Before performing the
inversion analysis, the subsurface structure
was assumed to consist of horizontal layers
of elastic and homogeneous media above a
semi-infinite elastic body. The shear wave
velocity and thickness of each layer are the
parameters determined by the inversion
analysis. The results enabled us to
determine the condition of shallow
subsurface structures (Kiyono et al., 2011).
The outline of the SPAC method for the
phase velocity calculation of the Rayleigh
waves is shown in Figure 3 and 4.

∗

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 324

Seismic cone penetration tests (SCPTu)
consist of a normal CPT with an
accelerometer contained in the cone. The
cone penetrates into the soils until it
reaches defined depth intervals for a Vs
measurement.
Shear
waves
were
generated at the surface by striking a 10 kg
sledgehammer on opposite sides of 2.5 m
hardwood beams. The cone penetration is
typically stopped every 1.0 m and the
source is located ~ 1 m from the entry point
at the surface (Noguchi et al., 2010) (Figure
7). The seismic cone penetration test unit
(SCPTu) used for seismic data acquisition
was the BCE SC1-DACtm 2013. The field
conducted survey method as shown in
Figure 10.

(a)

Three stations were compared based on
the soil type result from the microtremor
testing: soft type (Vs<200m/s) for the FTB,
UNP station and rock type (Vs>200) for the
ADS station. The considered depth of the
surface structure for each site was 4 m for
ADS, 18 m for FTB and 16 m for UNP
because the cone could not penetrate
further having reached the maximum
capacity of as much as 22 MPa. At every 1
m increment, a ground motion wave form
was obtained and the recorded data were
converted to the frequency domain using
the fast Fourier transform (FFT) method
(Figure 11).

(b)

H/V spectra(035)

H/V ratio

100

10

Td

Ts

1

0.1
0.1

1

10

period(s)

(c)

(d)

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

325 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

depth[m]

0

35

5

30

10

25

15

20

20

15

25

10

30

5

35

0

-0.88
-0.9
-0.92
latitude[deg]

-0.94
-0.96
-0.98 100.34

100.36

100.42
100.4
100.38
longitude[deg]

100.44

(e)
Figure 8. Three dimensional shape of the estimated subsurface structure: (a) target area
for the analaysis of three layered model, (b) Observation sites for microtremor single
observation, (c) sample of H/V spectrum, and (d) H/V distribution for whole Padang city
and (e) boundary depth for one layer.

Figure 9. Microtremor array results for three stations in Padang: (a) results for station
ADS (rock type) and (b) FTB and UNP stations (soft type).

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 326

Figure 10. Illustration: (a) SCPTu observation mechanism, (b) setting up the SCTPu
device.

Figure 11. Flow chart to highlight the procedure followed in order to estimate Vs from
SCPTu.
Table 2 shows the comparison of Vs
results. The Vs was determined from the
SCPTu for every 1 m increment depth using
Equation (16) (Wang et al., 2018) by
following a single layer model according to
a simplified single degree of freedom
system. The considered layer is the first
layer only, where Hi = 1 m increment,
ρ_i=1.7 ton/m3 and T_i is estimated from

the FFT of recorded ground motion at every
1 metre increment result as shown in
Figure 13-17.
𝑛
ℎ𝑖
T = π∑
(16)
𝑉𝑖
=1

where T is the frequency obtained from FFT
from the recorded acceleration for each
depth 1 m, and H is the depth from the
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

327 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

surface. Figures 13-17 summaries the
results of various soil properties from the
data generated from SCPTu.

Figure 12. Single shear velocity model.

Figure 13. CPT data for station ADS: (a) CPT sounding of SCPT at ADS with cone resistance.
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 328

(a)

(b)
Figure 14. SCPT data for station ADS: (a) acceleration at 1 m depth and (b) frequency at 1
m depth (from FFT).

Legend

Figure 15. CPT data for station FTB: (a) CPT sounding of SCPTu with cone resistance.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

329 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

(a)

(b)
Figure 16. SCPT data for station FTB: (a) acceleration at 1 m depth and (b) frequency at 1 m
depth (from FFT).

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 330

Legend

(b)
(a)
Figure 17. SCPT data for station UNP, (a) CPT sounding of SCPTu with cone resistance.

(a)

(b)

Figure 18. Microtremor array results: (a) Vs and depth; (b) dispersion curve for site UNP.

DOI:https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

331 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

(a)

(b)
Figure 19. Comparison of Vs (a) for soft soil from station FTB and UNP, (b) for the rock
soil type from station ADS.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 332

Table 2. The comparison of Vs results.
Depth (m)

0-2

SCPTu
ADS (m/s) FTB (m/s)
UNP(m/s)
145
152
163

2 -4

145

160

4–6
6–8
8 – 12

-

145
143
148

4. RESULTS AND DISCUSSION
4.1 Results
Figure 14 (a) and (b) presents
acceleration data at 1 m depth and the
FFT of acceleration, the predominant
period of acceleration was 0.26s. By
following the same procedure, each
predominant period was determined at
every 1 m increment for station ADS (rock
type). Figure 16 (a) and (b) presents
acceleration data at 1 m depth and the
FFT of acceleration. From FFT the
predominant period of acceleration was
found to be 0.26s. The predominant
period was determined for every 1 m
increment at station FTB by following the
same procedure for station UNP at
station UNP, as shown in Figure 17, the
Vs ranges from 0 to 15m. The Vs changed
rapidly from 2m to 3.5m (sand to gravel,
whereas the Vs of gravel was >300m/s)
and the cone resistant value ranged from
7 MPa to 13 MPa. Figure 19 (a) indicates
that the microtremor array result is
unable to determine dramatic changes of
Vs at the same layer as station UNP at 2
to 3.5m deep. The various soil properties
at every depth (m) can be seen in Figure
17 (b).
The Vs profiles result obtained
difference methods; from microtremor
array and SCPTu on 3 site with difference
soil types, The Vs profiles are not

Microtremor array
ADS (m/s) FTB (m/s) UNP(m/s)
308

165

163.5

350

308

165

163.5

175
170
130

308
308
308

165
165
165

163.5
163.5
163.5

comparable due to their difference in
resolution. While the SCPTu is able at
every 1m depth up to cone’s maximum
penetration resistance, the microtremor
array is more suitable for deeper
measurement but with lower resolution.
By considering constrain the inversion
process, it can improve the resolution for
Vs from microtremor array method. Our
conclusions are based on comparing Vs
between the microtremor array and
SCPTu results with a limited number of
observation sites (three in total: two for
soft soil types and one for the rock type).
4.2. Discussion
The various techniques used to
determine Vs (Tavakoli et al., 2016),
(Fatehnia et al., 2015) in the field
generally
performed
well.
The
comparison
obtained
Vs
from
microtremor and Borehole shows phase
velocities with the dispersion curve
calculated from the velocity structure
was found that observations agree with
borehole results to better than 11%
except when the wavelength is greater
than 2 times the array aperture (Hsi-Ping
Liu, 2020).
These result show the conducted
survey by SCPTu for three sites are The Vs
profiles are not comparable due to their
difference in resolution. While the SCPTu
is able at every 1m depth up to cone’s
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

333 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

maximum penetration resistance, the
microtremor array is more suitable for
deeper measurement but with lower
resolution. The depth of penetration of
SCPT was up to 18 m because the cone
could not penetrate further upon
reaching the maximum capacity of 22
MPa (McGann et al., 2015). In some
cases, this maximum was not achieved
owing to a combination of high friction
due to stiff clay, high tip resistance, or
high friction in the Pleistocene sands.
The other result shows the
microtremor array result is not suitable
for shallow measurement compare with
SPTu. The clearest case was station UNP,
where the top 2 to 3.5m was hard
material (Vs >300m/s), while the
opposite result was found for shear
velocity from the microtremor array
technique, leading to generalized Vs=
163.6m/s from 0-30.9 depth (no change
at 30m depth, called layer 1). In this
location, the dispersion could be
determined down to approximately 1 Hz,
but the modelling indicated that it only
obtained information from the top 15 m
(Figure 16).
Microtremor array is more suitable for
deeper measurement with lower
resolution (Sant et al., 2018). By
considering constrain the inversion
process, it can improve the resolution for
Vs from microtremor array method
(Yoshida & Uebayashi, 2021).
5. CONCLUSION
The shear velocity results from the
microtremor studies were used to
classify Padang soils into soft soils,
medium soils and rock. The seismic cone
penetration test unit (SCPTu) was used
up to a depth of 18 m for the soft soil type
and 4 m for the rock type. Comparison of
the Vs for different soils type at the first
layer between the microtremor array

observation results and the SCPTu results
indicated The compared the Vs profile
within the first ~20m, as obtained from
the microtremor array and the SCPTu.
However, the accuracy of the Vs profile
from the microtremor array is highly
ambiguous. It is a known fact that
microtremor techniques are not reliable
in the near-surface due to the lack of high
frequency data. Consequently, it is not
surprising that the Vs profiles have poor
resolution, in particularly at shallow
depths, the microtremor array is more
suitable for deeper measurement but
with lower resolution. The resolution
could have been improved by
constraining the inversion process. On
the hand, the SCPTu Vs profile returns a
far better resolution because it is
considered as an intrusive active seismic
test and the signals were acquired at a
depth interval of 1m.
6. ACKNOWLEDGEMENT
The authors would like to send high
appreciate and thanks to DIKTI for
financial support during conducting
research in Padang and Ottawa
University, Canada, Contract number
1248/E4.2/PP/2015. Thanks addressed
to Dr. Totoh Andayono, Mr. Adit, Mr. Ari
and Mr. Jamil for their contribution
during conducting field survey. finally,
High appreciate and thanks to
Universitas Negeri Padang for final
support through International research
collaboration and penelitian dasar
schemes PNBP with contract number
1012/UN35.13/LT/2021
and
904/UN35.13/LT/2021.
7. AUTHORS’ NOTE
Authors declare that there is no
conflict of interest regarding the
publication of this article. Authors
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 334

confirmed that the paper was free of
plagiarism.
8. REFERENCES
Carniel, R., Barazza, F., and Pascolo, P. (2006). Improvement of Nakamura technique by
singular spectrum analysis. Soil Dynamics and Earthquake Engineering, 26(1), 55-63.
Kennedy, J., and Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95international conference on neural networks, 4(1995), 1942-1948.
Fatehnia, M., Hayden, M., and Landschoot, M. (2015). Correlation between shear wave
velocity and SPT-N values for North Florida soils. Electronic Journal of Geotechnical
Engineering, 20(22), 12421-12430.
Lanin, D., Hermon, D., Fatimah, S., and Putra, A. (2019, August). A dynamics condition of
coastal environment in Padang City-Indonesia. In IOP Conference Series: Earth and
Environmental Science, 314(1), 012006. IOP Publishing.
Genrich, J. F., Bock, Y., McCaffrey, R., Prawirodirdjo, L., Stevens, C. W., Puntodewo, S. S.
O., and Wdowinski, S. (2000). Distribution of slip at the northern Sumatran fault
system. Journal of Geophysical Research: Solid Earth, 105(B12), 28327-28341.
Juliafad, E., Gokon., Putra, Rusnardi Rahmat., (2021). Defect study on single storey
reinforced concrete building in West Sumatra: Before and after 2009 west.
International Journal of GEOMATE, 20(77), 205–212.
Khazaei, J., Amiri, A., and Khalilpour, M. (2017). Seismic evaluation of soil-foundationstructure interaction: Direct and Cone model. Earthquakes and Structures, 12(2), 251262.
McGann, C. R., Bradley, B. A., Taylor, M. L., Wotherspoon, L. M., and Cubrinovski, M.
(2015). Development of an empirical correlation for predicting shear wave velocity of
Christchurch soils from cone penetration test data. Soil Dynamics and Earthquake
Engineering, 75, 66-75.
Nakamura, Y. (2000, January). Clear identification of fundamental idea of Nakamura’s
technique and its applications. In Proceedings of the 12th world conference on
earthquake engineering, 24, 25-30. New Zealand: Auckland.
Natawidjaja, D. H., and Triyoso, W. (2007). The Sumatran fault zone—From source to
hazard. Journal of Earthquake and Tsunami, 1(01), 21-47.
Noguchi, T., Ono, Y., Kiyono, J., Horio, T., Kubo, M., Ikeda, T., and Putra, R. R. (2010).
Determination of the subsurface structure of Padang City, Indonesia using microtremor
exploration. Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering
and Earthquake Engineering (SE/EE)), 66(1), 30-39.
Noorlandt, R., Kruiver, P. P., de Kleine, M. P., Karaoulis, M., de Lange, G., Di Matteo, A.,
and Doornhof, D. (2018). Characterisation of ground motion recording stations in the
Groningen gas field. Journal of seismology, 22(3), 605-623.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

335 | Indonesian Journal of Science & Technology, Volume 6 Issue 2, Sept 2021 Hal 315-336

Ono, Y., Noguchi, T., Rahmat Putra, R., Uemura, S., Ikeda, T., and Kiyono, J. (2012).
Estimating subsurface shear wave velocity structure and site amplificatin characteristics
of Padang, Indonesia. Journal of Japan Society of Civil Engineers, Ser. A1 (Structural
Engineering and Earthquake Engineering (SE/EE)), 68(4), I_227-I_235.
Parker, G. A., Baltay, A. S., Rekoske, J., and Thompson, E. M. (2020). Repeatable source,
path, and site effects from the 2019 M 7.1 Ridgecrest earthquake sequence. Bulletin of
the Seismological Society of America, 110(4), 1530-1548.
Pradono, M. H. (2014). Kajian kerentanan gempabumi gedung bertingkat dengan bentuk
beaturan dan tidak beraturan. Jurnal Sains dan Teknologi Indonesia, 16(3), 20-25.
Prawirodirdjo, L., Bock, Y., Genrich, J. F., Puntodewo, S. S. O., Rais, J., Subarya, C., and
Sutisna, D. S. (2000). One century of tectonic deformation along the Sumatran fault
from triangulation and Global Positioning System surveys. Journal of Geophysical
Research: Solid Earth, 105(B12), 28343-28361.
Putra, R. R. (2017). Estimation of Vs30 based on soil investigation by using microtremor
observation in Padang, Indonesia. International Journal of Geomate, 13(38), 135-140.
Putra, R. R. (2020). Damage investigation and re-analysis of damaged building affected by
the ground motion of the 2009 padang earthquake. International Journal, 18(66), 163170.
Putra, R. R. (2020). Relationship between obtained ultimate bearing capacity results based
on n-spt results and static load tests. International Journal, 19(74), 153-160.
Putra, R. R., Kiyono, J., Ono, Y., and Parajuli, H. R. (2012). Seismic hazard analysis for
Indonesia. Journal of Natural Disaster Science, 33(2), 59-70.
Putra, R. R., Kiyono, J., and Furukawa, A. (2014). Vulnerability assessment of non
engineered houses based on damage data of the 2009 Padang earthquake in Padang
city Indonesia. International Journal of GEOMATE, 7(2), 1076-1083.
Rosyidi, A. P., Jamaluddin, T. A., Sian, L. C., and Taha, M. R. (2011). Earthquake impacts of
the Mw 7.6, Padang, Indonesia, 30 September 2009. Sains Malaysiana, 40(12), 13931405.
Sant, D. A., Parvez, I. A., Rangarajan, G., Patel, S. J., Salam, T. S., and Bhatt, M. N. (2018).
Subsurface imaging of brown coal bearing Tertiary sedimentaries-Deccan Trap interface
using microtremor method. Journal of Applied Geophysics, 159, 362-373.
Sieh, K., and Natawidjaja, D. (2000). Neotectonics of the Sumatran fault, Indonesia. Journal
of Geophysical Research: Solid Earth, 105(B12), 28295-28326.
Sofyan, Y. (2016). Project for offshore Horizontal Directional Drilling (HDD) for pipeline
crossing in Bukit Tua, Indonesia. Indonesian Journal of Science and Technology, 1(2),
185-202.
Sutrisno, Putra, R. R., and Ganefri. (2017). A comparative study on structure in building
using different partition receiving expense earthquake. International Journal of
Geomate, 13(37), 34-39.
DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045

Putra et al., Relationship between Shear Velocities Recorded by Microtremor… | 336

Tavakoli, H. R., Amiri, M. T., Abdollahzade, G., and Janalizade, A. (2016). Site effect
microzonation of Babol, Iran. Geomechanics and Engineering, 11(6), 821-845.
Thein, P. S., Pramumijoyo, S., Brotopuspito, K. S., Wilopo, W., Kiyono, J., Setianto, A., and
Putra, R. R. (2015, April). Designed microtremor array based actual measurement and
analysis of strong ground motion at Palu city, Indonesia. In AIP Conference Proceedings,
1658(1), 040007
Thornley, J., Dutta, U., Fahringer, P., and Yang, Z. (2019). In situ shear-wave velocity
measurements at the Delaney Park downhole array, Anchorage, Alaska. Seismological
Research Letters, 90(1), 395-400.
Wang, S. Y., Shi, Y., Jiang, W. P., Yao, E. L., and Miao, Y. (2018). Estimating Site Fundamental
Period from Shear-Wave Velocity ProfileEstimating Site Fundamental Period from
Shear-Wave Velocity Profile. Bulletin of the Seismological Society of America, 108(6),
3431-3445.
Yoshida, K., and Uebayashi, H. (2021). Love-Wave Phase-Velocity Estimation from ArrayBased Rotational Motion Microtremor. Bulletin of the Seismological Society of
America, 111(1), 121-128.

DOI: https://doi.org/10.17509/ijost.v6i2.34191
p- ISSN 2528-1410 e- ISSN 2527-8045