Figure 1. (a) Tectonic setting of the SCB. The different
colours in the background indicate the different periods of rock
outcrops distributed throughout the SCB. The thick solid lines represent
the convergence boundary and deep faults between blocks: GHF:
Gaoyao–Huilai fault; ZDF: Zhenghe–Dapu fault; ALF: Anhua–Luocheng
fault; CNF: Changle–Nanao fault; JSF: Jiangshao-Shaoxing fault. The
thick dashed lines are the inferred boundaries between blocks. The thin
black lines are major faults in mainland China, while the blue circles
denote Mw ≥ 3.0 earthquakes that occurred from 1980 to 2021 downloaded
from the Incorporated Research Institutions for Seismology (IRIS)
website (http://ds.iris.edu/ieb/). The gold triangles represent the node
geophones deployed along the Zhuhai–Lianzhou profile. (b) Tectonic
setting of Southeast Asia. The equilateral blue rectangle denotes the
main research area in panel (a). NCB: North China block; SCB: South
China block; ECS: East China Sea; SCS: South China Sea; TP: Tibetan
Plateau; IB: Indochina block. (c) Teleseismic events recorded by the
node geophones. The dark red triangle indicates the location of the
dense array in Guangdong Province, China. The circles of different sizes
are the teleseismic events recorded by the dense seismic array with
epicentral distances within 30~90° and Mw ≥ 5.0. The Mw
7.3 Banda Sea earthquake (black arrow) occurred on 24 June 2019 at
02:53:39 (Coordinated Universal Time, UTC) at an epicentral distance of
212.0 km (33.57°).
1.2 The dense short-period seismic array
The detection of fine subsurface structures in modern seismology always
requires a good sampling frequency in the spatial domain, which may be
beyond the ability of most permanent seismic stations with a large
spacing of 20~100 km (Shen et al., 2019). Meanwhile,
these permanent stations can be supplemented by deploying portable
broadband stations with a small spacing of 1~20 km (Wang
et al., 2018; Ye et al., 2017; Yuan et al., 1997; Zhu, 2000). However,
broadband stations are expensive and thus are sparsely adopted, while
the resolution depending on the spacing between two stations is limited.
In recent years, with the development of dense short-period seismic
arrays with intervals ranging approximately from 100 m to 2 km, fine
crustal structures have been discovered in increasingly observations.
In the early studies, Yuan et al. (1997) proposed the moveout correction
methods based on the INDEPTH short-period seismic array, and Zhu (2000)
developed the common conversion point (CCP) migration method based on
the LARSE short-period seismic array. More recently, based on 473
seismometers, Shen et al. (2020) suggested that a pure shear shortening
model beneath the Qilian Mountains can explain the lateral growth of the
northern front of the Tibetan Plateau. Moreover, based on a dense array
of 340 seismometers, Tian et al. (2021) found that the lateral growth of
the northeastern front of the Tibetan Plateau can be represented with a
model incorporating upper crustal overthrusting and lower crustal
underthrusting beneath the Liupan Shan area. However, none of these
features have been reported by previous portable or permanent broadband
seismic studies.
In the following, one type of seismometer named the node geophone from
the petroleum industry, which was introduced to the passive source
seismic studies, has gradually become the most advantageous option for
local exploration surveys. The deployments of large-N experiments within
small areas using the node geophones (~100 m) became
highly convenient for the 3D detection of shallow crustal structures
(Dougherty et al., 2019; Lin et al., 2013). Some laboratory and outdoor
experiments even show that node geophones can also be adopted to
effectively record teleseismic signals; however, the shortcomings,
namely, that they are biased toward relatively high frequencies and are
susceptible to local noise and ambient temperatures, limit their use in
teleseismic studies (Ringler et al., 2018). Despite this, these
geophones have been introduced for traditional teleseismic receiver
function analysis (Ward & Lin, 2017), and the results confirm that the
recording of nodes can provide good constrains of shallow basin and
fault structures (G. Liu et al., 2018; Ward et al., 2018).
Simultaneously, node geophones are also used for monitoring traffic,
weather, thunder, and blasts in urban seismology (Johnson et al., 2019;
Lythgoe et al., 2021).
In this research, we carried out a geophysical survey with a dense
linear array of short-period node geophones. This array was oriented
north-south connecting the cities of Zhuhai and Lianzhou in Guangdong
Province, China (Fig 1 a). From the recording of teleseismic events, we
obtained an unprecedentedly detailed stacking profile using the
teleseismic receiver function method. With these high-resolution
results, we can provide certain evidence for the existence of remnants
from the amalgamation of the East and West Cathaysia blocks.
2 Data and Methods
Using 527 short-period, 3-channel node geophones (Fairfield Zland GEN2
5Hz), we obtained 5.75 TB of seismic waveform data over 37 days from 25
May to 2 July 2019 and a total of 41 Mw ≥ 5.5 teleseismic events were
recorded (Fig 1 c). Although short-period node geophones are convenient,
the quality of the recorded waveforms is greatly affected by the
deployment conditions. To ensure that the seismometers are coupled with
the earth, node geophones each need to be buried within a 30 cm deep
hole and at least 10 cm from the surface, in this way, persistent noise
signals at approximately 20~40 Hz can be suppressed
(Farrell et al., 2018).
In the early stage, the Python-based seismic tool Obspy was used to
process the raw data (Beyreuther et al., 2010). To better constrain the
performance of the geophones, we specifically analyzed the filtering
parameters by using a series of two-pass, four-pole butterworth filters.
Finally, a relatively narrow and low frequency band of 0.02–1 Hz was
adopted to avoid the sensitivity of the instrument to high frequencies
and prevent the contamination of the teleseismic signals with ambient
noise. Upon rotating the three-component waveforms into
radial-transverse-vertical (RTZ) coordinates, the direct primary
(P-wave) arrival could be clearly distinguished from the continuous
waveforms. After applying time-domain iterative deconvolution (Ligorría
& Ammon, 1999) and manual checking, a total of 991 teleseismic receiver
functions were selected. During the deconvolution process, low-pass
Gaussian filters with different Gaussian factors of 2.0, 5.0 and 10.0
were adopted, and the corner frequencies were 1.0, 2.4 and 4.8 Hz,
respectively. To avoid the influence of decreasing slowness with
increasing conversion depth on the converted waves, the moveout
correction method proposed by Yuan et al. (1997) was used to correct
each curve to the 65° theoretical curve calculated by the iasp91
velocity model (Kennett & Engdahl, 1991). In the following, according
to the piercing points of the Moho-converted phase, hereafter referred
to as the Pms phase, the receiver functions with a Gaussian factor of
5.0 were aligned along the profile (Fig 2 a, b). Stacking of receiver
functions with Gaussian factors of 2.0 and 10.0 are shown in the
Supplementary Materials (Fig S2). In addition, we also binned the
receiver functions in each 0.08° grid interval to strength the arrival
of the Pms phases. The theoretical Pms arrival times were calculated by
the TauP Toolkit (Crotwell et al., 1999) at a depth of 35 km under the
iasp91 velocity model. Moreover, to intuitively enhance the signals from
multiple waves, we also carried out PmpPms and PmpSms moveout
corrections, and the stacking results are shown in Figure 3. During
stacking, a smoothing factor was employed to smooth the receiver
functions between adjacent grids, while the factor was determined by
dividing the amplitude by the square of the distance between two grids.
The amplitude and time errors during picking are indicated by the mean
value and standard deviation with 100 resamplings according to the
1-dimensional