Abstract
The monitoring regime for the Comprehensive
Nuclear-Test-Ban Treaty includes seismic technologies based on data from the
International Monitoring System (IMS), which is processed by the International
Data Centre (IDC). High standards for data quality and the processing are
mandatory to achieving the goals of the Treaty. The IDC bulletins and catalogues
include only event hypotheses matching the established levels of statistical
significance and reliability. The States Parties to the CTBT are flexible in
applying the own methods of monitoring, focusing on specific regions and source
types. The research community dealing with the scientific and technical issues
related to the monitoring regime proposes, develops, and tests various
techniques and methods to improve the
resolution and sensitivity of the IMS network and to enhance processing. The
waveform cross-correlation method (WCC) reduces the detection threshold and
improves the accuracy of the principal parameters estimation. When applied to seismic
activity at the Nevada Test Site, the WCC-based methods allow to find dozens of
events not detected by the IDC. The monitoring regime of the NTS can be
significantly improved by using the approach developed in this study.
Key words: CTBT, IMS, IDC, Nevada test site, waveform cross
correlation
Introduction
The seismic network of the International Monitoring
System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO)
will include 50 primary and 120 auxiliary stations [CTBT, 1996]. As the CTBT
has not yet entered into force, the seismic network has not been complete with a
few more stations to be deployed and/or certified. Many State Parties, including
the USA and China, have not yet ratified the CTBT, but they provide and process
data of all technologies used by the CTBTO. The early ratification of the CTBT
by Russia was revoked in order to return to equal position with the other two
countries having the largest nuclear arsenals. The Treaty cannot come into effect
without a few countries that have not signed it. Therefore, the Preliminary
Technical Secretariat (PTS) of the CTBTO runs all the IMS networks and data
processing in preparation mode. There is no obligation on any country to submit
data to the International Data Centre (IDC) located in Vienna, Austria, before
the CTBT comes into force. The same is applicable to onsite inspections - a
powerful procedure of the CTBT monitoring regime.
Distribution
of the IMS primary seismic stations over the globe was designed to provide a quasi-even
distribution of detection threshold without any specific place to be monitored
with a much higher sensitivity and resolution. By definition, seismic signals
at primary stations define the statistical significance of the created event
hypotheses with different inputs from arrays and three-component (3-C) stations
[Coyne et al., 2012]. All statistical
properties of a hypothesis are based on the measurements of travel time,
slowness and azimuth of the detected signals. The residuals of these three
parameters have to be within well calibrated tolerances that are specific to
stations and seismic phases. The IMS auxiliary stations provide valuable
information to improve the accuracy of the defining source parameters:
hypocenter, origin time, and magnitudes, but they do not affect the event
hypothesis statistics directly.
Larger
seismic events tell for themselves and are easy to detect and to interpret. The
smallest natural events and concentrated underground explosion has very
specific features shaping the IMS network [Evernden et al., 1986]. All small events are very similar in terms of source
function. An event with the body wave magnitude, mb, of, say, 2.85
would have the size of emitting source or elastic radius of tens of meters. A 1
kt explosion in hard rock like granite or anhydrite has an elastic radius of
approximately 100-120m, and the scaling law suggests that the radius is
proportional to the cube root of the explosion yield. The source size of 50 m makes
it effectively a point source as the length of generated P-waves observed at
regional stations is of approximately 1 km (e.g., wavelength of the Pn-wave
with apparent velocity of 8 km/s at 8 Hz). Moreover, the source duration is
also a few thousandths of a second as the propagation velocity of the shock
wave is more than 5 km/s and for the length of 50 m the propagation time is <0.01
s. The source function of any seismic event with magnitude of ~3.0 is a point
source with δ-function as an emitted signal. There is no method to distinguish
natural sources like earthquakes and underground explosions for such small
magnitudes. The IDC has a rule not to apply the event screening procedure to
the events with mb below 3.5 as the generations of seismologists
recommended [Coyne et al., 2012]. Any
responsible statement of the explosion relevant features for an mb
2.85 event has to be scientifically justified. An extensive statistics of
successful identification/discrimination/ screening based on such features is a
mandatory prerequisite for the monitoring community.
In
the paper devoted to the Lop Nor test site during the period around the 22nd of
June, 2020, we have processed the IMS data using waveform cross-correlation (WCC)
to assess regional seismicity [Kitov, 2026a]. The WCC-based methods have been
growing in number and capability since the early 2000s [Schaff, Richards, 2004;
Gibbons, Ringdal, 2004, 2006; Gibbons et
al., 2007, 2011]. At the IDC, WCC processing has been tested and introduced
into a prototype pipeline since 2010s [Bobrov et al., 2014]. It showed excellent results in finding low-magnitude
events missed in standard IDC processing. There were several exercises when
experienced IDC analysts reviewed the cross correlation bulletin (XSEL)
obtained for specific regions and time periods [Bobrov et al., 2014; Bobrov et al.,
2016a, 2017]. The events created in these interactive reviews fully matched the
IDC Event Definition Criteria [Coyne et
al., 2012]. Since the Reviewed Event Bulletin (REB), the IDC final internal
bulletin, cannot be changed after the interactive review is finished, these new
events were added to a different database account and are available for further
analysis. The share of these new REB-ready events was from 50% to 80% of that
in the REB. This means that the IDC misses around 100% of low-magnitude events most
relevant to the CTBT monitoring regime.
The
WCC-based methods are also very useful for the CTBT monitoring regime as they
allow for much more accurate location of explosions [Selby, 2010; Gibbons et al., 2017]. The smallest and weakest
aftershocks of the announced DPRK underground tests are found at near-regional
[Adushkin et al., 2017; Kitov,
Sanina, 2022], regional, and teleseismic distances [Adushkin et al., 2025b]. The most recent
improvements in the WCC capability to detect the weakest signals are based on
the extensive use of arrays (e.g. IMS stations and "Mikhnevo" array (MHVAR)
of the Institute of Geosphere Dynamics (IDG), Russian Academy of Sciences
[Kitov et al., 2025]) and noise
suppression by various techniques from mixing the processed waveforms with
regular signals [Kitov, Sanina, 2025a; Kitov 2026d] to adding stochastic noise in
order to induce destructive interference with the noise component coherent to
the sought signal [Adushkin et al.,
2025a; Kitov, 2026d]. Application of these new techniques to the IMS seismic data
allows for detailed study of the physical processes before and after
catastrophic earthquakes [Kitov, 2026b] and likely earthquake prediction [Schaff
et al., 2025; Kitov, 2026c]. One can
see the evolution of seismicity in time and space at the magnitude level not visible
to standard methods.
For historic
reasons, the NTS is characterized by the lowest detection threshold at the IDC with
three IMS primary seismic arrays NVAR, PDAR and TXAR and a few auxiliary 3-C (e.g., ELK, ANMO, NEW, YBH) stations at
regional distances. The detection threshold for the events within and close to
the NTS can be even further reduced at the IDC using the new data processing
techniques based on waveform cross correlation applied to IMS data [Bobrov et al., 2014, 2016ab, 2017; Adushkin et al., 2025a; Kitov et al., 2026; Kitov, 2026abc]. An
example of such an analysis was presented for the Lop Nor in [Kitov, 2026a].
It's interesting to apply the same procedure to the NTS using the same approach
to the IMS data for the same period as for Lop Nor. The low-magnitude seismic
events can be generated by natural sources or by underground explosions, and
not only by chemical ones.
Data and method
NTS seismicity, as per the IDC
The
NTS is not characterized by a large magnitude seismic activity with smaller
earthquakes detected by local, regional and global networks. There is a
seismically active zone to the west of the NTS as Figure 1 shows. The
approximate center of the NTS is presented by a red circle and has coordinates
37.15°N, 116.05°W. The size of the test site is of dozens of miles in each
direction from the center. The IDC bulletin includes 58 events located within
the rectangular area 114.0°W-117.2°W, 35.5°N-38.6°N and all of them are low-magnitude
with the largest mb(IDC) of 4.42 (Appendix 1). The number of
associated phases, Nass (see Appendix 1), includes regional phases (Pg,
Pn) at the same stations. Therefore, the number of associated
stations is not large for all NTS earthquakes. Figure 2 presents the number of
associated stations for all 389 events in Figure 1. At the closest stations
NVAR, ELK, and PDAR, Nass is larger than the number of REB events. The most
sensitive to the events within the NST are: near-regional (<4.5°) stations
NVAR and ELK, regional stations PDAR, ANMO, TXAR, YKA, ILAR, YBH, ULM, NEW,
teleseismic stations BVAR, KURK, and PETK. Array station PDYAR has been
operating since 2023 and it is likely to be one of the most sensitive
teleseismic stations to the NTS as associated with 20 from 23 REB events.
There
were many underground explosions conducted within the NTS in the past. They are
recorded by the IMS legacy stations with some waveforms available from the
DARPA database. We do not use them in this study as the waveforms from smallest
earthquakes would not be much different from that of the same-size explosions.
For a point source with a δ-function as a signal shape, the solution does not
depend on the nature as it's the Green's function of the event-station
propagation path. The dependence of the signal amplitude on the azimuth for
low-magnitude events is less important than the ambient noise at seismic
stations. However, there is always a possibility to include historic records in
the WCC processing as templates for a number of stations.
Figure 1. Seismic events from the REB from January 18,
2001 to October 31, 2025 for the area within and around the NTS. The REB events
within the area confined by lines 114.0°W-117.2°W, 35.5°N-38.6°N are light blue
circles, master events: red circles - for routine WCC processing, violet
circles - for WCC processing with stochastic noise added.
Figure 2. Number
of associated phases (Pg, Pn) at IMS stations for 389 REB
events.
Master Events
Routine WCC processing is essentially the same as
introduced in [Bobrov et al., 2014]
for the first processing exercises followed by an interactive review conducted
by experienced IDC analysts. It is based on the events from the IDC database
called "master events" (ME) with their respective P-wave templates at
all associated stations. (For regional stations, the P-wave templates can
include the secondary phases.) Therefore, the MEs used in a given place are
subject to replacement if better REB events appear in the growing IDC database.
The ME selection process for various seismic regions depends on the
availability of REB sources. Within the areas with an intensive seismicity and
high REB event density, the best MEs have to detect the largest portion of the neighboring
REB events. Corresponding calculations are conducted for all new REB events and
the old MEs are replaced if the new ones are more efficient. For the areas with
low event density and low quality of templates as defined by their
signal-to-noise ratio (SNR), the best ME is selected by its weight equal to the
sum of probabilities of the associated stations to participate in events in the
area. For the places where only one of two events are available, they can be used
as the ME(s) by default. All new unique events, e.g. the DPRK underground
tests, are used as MEs when found and promoted to the REB. Finally, in the
areas where natural and man-made events are absent in the REB, semi-synthetic
and synthetic MEs are used [Bobrov et al.,
2016b].
Seismic
activity is high to the west of the studied NTS area. But these earthquakes are
not representative for the NTS and are not used as MEs. There are 58 REB events
more relevant to the task of NTS detailed monitoring shown in Figure 1. They
are split in three categories. Seven violet circles present the events closest
to the NTS centre and used as MEs for the WCC processing with stochastic noise.
Twenty events shown by red circles are used for routine WCC processing and are
at larger distances from the NTS central point. The other 31 REB events are
shown by light blue circles and can be used as MEs when needed. They are
located close to the events from the second category but have lower statistical
significance and number of associated phases. The dark blue circles are the REB
events not representing the NTS.
WCC detection
There are two approaches to WCC processing in this
study. For the 20 light blue MEs in Figure 1, routine processing is used with
the only enhancement by the "shaken, not stirred" technique applied
to the traces of the cross correlation coefficient (CC) at array stations. The CC
values can be shifted in the discrete time series relative to their real
positions in time. Random shifts of individual CC time series by one or two counts before averaging over all
channels. When applied a hundred times, the simultaneous shifts of all channels
can create a configuration closer to the actual one and increases the
signal-to-noise ratio (SNRcc) for the matched filter detector [Turin, 1960].
As an
enhancement to the routine processing, a newly developed technique for ambient
noise suppression using a stochastic time series [Adushkin et al., 2025a; Kitov et al.,
2026; Kitov, 2026d] is able to reduce the detection threshold by up to a factor
of 2 or more, depending on whether
there is a coherent component in the ambient noise that matches the template. This method is thoroughly used in many wave processes
to suppress noise. Its application to seismic data at array stations, which are
phased antennas, is especially effective when used before the WCC-based
detector is applied.
The
WCC detector uses the CC time series
calculated for the raw data filtered in five overlapping frequency bands
between 0.5 Hz and 8 Hz. As the sough signal length above the noise is not
known in advance, the WCC window width can vary from the shortest teleseismic
signals of 3 s to 4 s to the longest near-regional signals of 120 s or more,
which include all regional phases from Pg to Rg. Such
wide windows make the CC estimates to
be very sensitive to the difference in the apparent velocities of individual
regular phases. The change in the sought event-station distance relative to
that of the ME-station value effectively destroys the similarity of shapes as
the secondary phases arrive earlier or later. For array stations, the change in
event-station azimuth for even identical signals also destroys signal coherency
resulting in lower CC values and
non-detection.
For
an array station, the individual CC
time series are averaged over all channels without any time shift since the
sought signal has to arrive at all sensors at the same relative times as in the
multichannel template. The averaged CC
time series is similar to the averaged trace created in the beamforming
[Schweitzer et al., 2012]. The same
ratio of short-term-average (STA) and long-term-average (LTA) can be used for
detection. For an array beam, a detection is declared when the STA/LTA ratio
reaches the predefined threshold. The maximum SNR of the detected signal and
its peak amplitude are sought in a relatively short interval after the
detection time. When the threshold in reached, the LTA is "frozen"
not to allow the signal energy to affect the STA/LTA estimates.
The
WCC detection is different as the sought and template signals have to be fully
synchronized for the SNRcc has to reach its peak. The CC may start to rise when the tail of the template enters the
initial part of the sough signal, however. These signals might be coherent throughout
the whole length of the template. For the 120-second-long template and sought
signals, the CC and thus SNRcc may
start to grow tens of seconds before the signals finally coincide. At the same
time, the detection threshold defined for the SNRcc has to be lower than the
peak SNRcc value not to allow the increasing CC to be used in the LTA estimation. As a result, the detection
window has to be at least as long as the template. The time of the peak SNRcc
is considered as the arrival time. This is important station NVAR is at a
distance of 3° to 4° from the NTS and has to detect long signals consisting of
secondary seismic phases. For teleseismic distances, the sought signals are
very short for low-magnitude events and the peak SNRcc is close to the first
point where it reaches the detection threshold. The peak SNRcc value for a
given time count is selected from the full set of filters and template lengths
similar to the procedure in the beamforming
detection [Coyne et al., 2012].
The
detection thresholds have to be tuned to the expected signals and variations in
the noise conditions. Station tuning is a mandatory task for the IMS/IDC optimal
performance [Saragiotis, Kitov, 2020]. By varying the SNRcc threshold, one can
obtain the desired rate of detections. Figure 3 presents pdf distributions of the SNRcc values for 6 hours on June 21, 2020,
at three stations: NVAR - near regional, PDAR - regional, YKA - teleseismic.
Two MEs (one for YKA) are shown for comparison of their performance. The
detection threshold is set at two levels - low and high. For the high level no
detection is possible since the SNRcc value for low-amplitude signals can never
reach SNRcc=100. The low level is used for routine WCC processing and is tuned
to generate from 30 to 80 detections per hour. The detection rate of approximately
1 per minute is an important constraint for the following phase association
process with the travel time tolerance of 2 seconds. The difference between the
low and high case is the presence of detections with SNRcc above 3.1-3.5 in the
low detection threshold curves. These are the detections likely related to the
sought signals from the NTS. For the high threshold case, there is a weak kink
in the curves around 3.5. The absence of detections does not mean the absence
of relevant signals, but the effect of long precursor in the CC trace described above suppresses the
peak SNRcc values. At stations NVAR and YKA there are wide SNRcc peaks between
3.2 and 4.0. A part of sought signals from these peaks then associated with the
event hypotheses. There is no such a peak at PDAR, but the pdf starts to deviate from the exponential trend approximately at
SNRcc of 3.0-3.2 producing potentially valid signals.
The
curves in Figure 3 demonstrate the features not observed in similar curves for
standard SNR at the same stations. The SNRcc curves include only signals from
the target area around the corresponding ME. For a fully quiet day in this
target zone, the curves should have no signals and follow exponential trend.
The SNR curves always have all sorts of local, regional and teleseismic signals
from a multitude of physical sources. There are no really quiet days for a
standard energy detector. This is one of the reasons why the SNRcc thresholds
are lower than the SNR ones. The detection rate cannot be too high in order not
to create to many false event hypotheses with randomly associated phases.
Figure 3. pdf distributions of SNRcc values at three stations: NVAR - near regional, PDAR - regional, YKA - teleseismic.
The
matched filter is the optimal detector maximizing the SNRcc when the noise is
stochastic and additive. For seismology, the ambient noise is almost always
additive if to neglect resonance, liquefaction, and strong motions. But the ambient noise is almost never stochastic, because it consists of
elastic signals generated by physical sources that are similar to the sources
of the signals we are looking for. Then computer generated stochastic noise time
series is added to the filtered waveforms before the WCC detector is applied,
the noise component coherent to the template is suppressed more than the sough
signal and the CC values decrease for
the noise more than for the sought signal. The SNRcc increases respectively,
with some values above the detection threshold. This is the mechanism at work
and the first results fully support this approach for aftershocks of the
Kamchatka July 29, 2025 earthquake [Kitov et
al., 2026].
There are various ways to
add time series to filtered data. The stochastic noise amplitude has to be
tuned to the amplitude of the noise component to destroy. The target noise
component is the one most coherent with the template. Constructive interference
of this noise component mixed with the sought signal suppresses the WCC
performance. The case when the ambient noise is almost fully coherent to the
sought signals is the aftershocks right after a catastrophic earthquake. The
sought signals are the same as noise and all detection methods fail to find
even bigger aftershocks right after the mainshock. The addition of stochastic
noise reduces the detection threshold
even in such inferior conditions.
Since the amplitude of the
target ambient noise component is not known, a set of stochastic noise
amplitudes has to be used. The original random noise sequence obtained in the
range [-1.0,+1.0] is scaled by the factor StochN
before being mixed with real data. The simplest way is to globally scale to the
peak amplitude of the real trace in the processed time interval. It is also
possible to scale locally using the noise amplitude estimates like the STA and
LTA. The best scaling method has to be evaluated before applied to the WCC
processing of the data set under study. The STA occurred to be the choice for
the NTS data. The factor StochN varies between 0 and 20 with 1.0
step. The calculation time increases by a factor of 21 as the CC has to be calculated for each StochN value separately and then the
highest SNRcc is taken for a given time count. This is especially challenging
for station NVAR where the template length varies from 10 s to 120 s. The CC computation for a given time count is
done once for 120 s and the shorter windows are cut from the 120 s segment.
Local phase association and
conflict resolution
After the WCC-based detection has
been completed, individual lists of arrivals for the MEs are available for
further processing. Each arrival is characterized by its principal parameters:
arrival time, CC, SNRcc, standard
SNR, and relative amplitude. The latter is the ratio of the RMS amplitudes of
the sought signal and template in the detection configuration of the band-pass
filter and the width of WCC window. The logarithm of this ratio is the relative
magnitude of the sought signal with the known magnitude of the ME of the
template. All these parameters are used in the following phase association.
For a
ME, the event hypotheses have a very specific feature compared to the global
association at the IDC or any other seismological agency. All hypotheses created
by the detections for one ME must be close in space to it. Instead of using the
global travel time curves, one can calculate the station-event hypotheses
empirical travel time with a very high accuracy. This is a correction to the
ME-station empirical travel time estimated from the hypotheses location
relative to the ME and the empirical or theoretical slowness. Therefore, a grid
search is an effective technique for the relative location of the event
hypotheses within a small footprint of the ME. The relative location is the
basis of local association (LA) of seismic phases with event hypotheses. The
final set of hypotheses has to maximize the weights of events, i.e. the sum of probabilities of
the stations to be associates with the events in the studied area. In addition
to the quality requirements of the WCC-based processing [Kitov, 2026c], the
quality of the created hypotheses has to match the Event Definition Criteria of
the IDC. The most important IDC rule is that there have to be at least three
IMS stations with P-wave arrivals. For all calculations in this study, the
travel time residual for valid association is set to 2 s. All associated
stations have to have origin times (the arrival time less the empirical travel
time) within ±2 s of the averaged value defining the event origin time. The
stations magnitude tolerance for standard WCC processing is 1.2. The magnitude
estimates in this study are prone to large errors related to the low amplitude
of the sought signals at the level of
noise or even below it. The relative magnitudes of the event hypotheses can be biased
significantly to larger values and cannot be used for further
interpretation.
The
MEs are closer to each other than the radius of their virtual location grid in
order to cover the whole area without gaps. The adjacent MEs may create hypotheses
for the same physical event with slightly different arrivals obtained by
different templates at the same station. To resolve potential conflict between
two of more hypotheses for the same physical source, the events' weights are
used. If they are equal, the number of associated phases is compared. When both
parameters are equal, the conflict resolution process is using the RMS travel
time residual.
The
final list of generated events hypotheses, XSEL, contains the events with
associated stations. This is an automatic bulletin. Hence, it contains valid hypotheses
ready to be promoted to the REB, valid hypotheses not promoted to the REB
because of analysts experience with visible signal, and false hypotheses. The
not promoted valid hypotheses are those with low SNR values and high SNRcc
values. The signals are real but they are close to the noise level. Such
detections are not allowed in IDC automatic processing since the energy
detectors would generate enormous number of arrivals [Saragiotis, Kitov, 2020].
Results
The set of 20 MEs in Figure 1 was used to process data
between June 18 and June 24, 2020. The detection lists for the MEs were
processed by the LA program using two different settings corresponding to
strict and weak requirements for the event hypotheses. The crucial difference
is in the sum of the SNRcc values for the hypotheses with 3 to 5 associated
stations. According to Figure 3, the probability of a detection falls almost
exponentially as a function of SNRcc. An increase in SNRcc by 1.0 for each of
the associated detections results in a dramatic spike in the statistical
significance of the created hypothesis because the probability of the random
association falls respectively. The statistical power of the created hypotheses
is related to the capability of the XSEL to match the REB or the bulletin
created by the IDC analysis from the XSEL. This exercises have demonstrated the
extraordinary statistical power of the WCC-based bulletins [Kitov, Sanina, 2025b].
Another difference is the search area with the strict setting having the radius
of 45 km while that for the weak one is 60 km. The third difference in the
minimum event weight: 2.5 and 2.2 for the strict and weak setting respectively.
The largest weight of 1.0 has station NVAR. Stations PDAR and ELK have the
weight of 0.9, TXAR 0.85, and the other stations have weights of 0.8 and lower.
This approach is similar to the weight calculation at the IDC based on the
quality of stations and associated phases [Coyne et al., 2012].
Figure
4 presents the result of the WCC processing for the strict case. There were 31 event
hypotheses created with the most of them concentrated near the high seismic
activity area shown in Figure 1. Such distribution of the reliable XSEL hypotheses
does not contradict the observed seismicity. The REB has not reported any event
within this area. There are three XSEL events in different locations but they
are also in the known seismic zones.
Figure 4. XSEL events for the strict LA setting
The strict LA setting may have too
high thresholds for the defining parameters if to consider the detection rate
at the involved IMS stations listed in Table 1. The total number of detections
in the third column of Table 1 at a given station depends on the number of MEs
associated with it and the processed period.
Only NVAR has all 20 MEs associated and this is the reason for it 1.0
weight in the event hypotheses. The WCC processing is conducted at a daily
basis, but the day length is 25 hours in order to allow arrivals from some
events with origin time close to 00:00 in the next day. The hourly detection
rates vary from 15 at USRK to 60 at KURK. The most sensitive station NVAR has
detection rate of 39 per hour. These values are very low for the possibility of
random association of 3 to 5 stations with an event hypothesis considering the
origin time tolerance of 2 s.
The
strict setting can reject some valid hypotheses and the weak setting may help to
find some of them without a visible increase in the number of false hypotheses.
Figure 5 depicts the distribution of 207 XSEL events obtained for the weak setting for the same 7
days as for the strict setting. The XSEL events concentrate in the same
north-western zone, but many of them are found to the south and east of the NTS
center. Appendix 2 lists the XSEL
catalog for these events. The number of associated stations for a majority of
events is 5. This number is important for the statistical significance of the
hypotheses. There are several 3-station events consisting of the best stations
and one 8-station event (#7 on June 23) with the weight 6.6. This XSEL can be
compared to a local bulletin if the latter is available. The performance of 3-C
stations of standard local/regional network can be less effective, however, than
that of arrays. For a 16-instrument array, the detection threshold is by a
factor of 4 lower on average than for the collocated 3-C station. The amplitude
distance curve at near-regional distances decreases by a power law [Veith,
Clawson, 1972] and the factor of 4 is converted into the lower detectable
magnitude at the same distance or into a larger distance for the same magnitude
threshold.
Table 1. June
18, 2020. Station detection rate for the routine WCC processing of 20 MEs
|
Station |
Associated MEs |
Total detections |
Detections per ME |
Detections per ME per hour |
|
ANMO |
11 |
10645 |
967 |
39 |
|
ARCES |
3 |
2492 |
830 |
33 |
|
BVAR |
4 |
3035 |
758 |
30 |
|
ELK |
13 |
11006 |
846 |
34 |
|
FINES |
6 |
3651 |
608 |
24 |
|
ILAR |
14 |
7180 |
512 |
20 |
|
KURK |
2 |
3007 |
1503 |
60 |
|
NVAR |
20 |
19316 |
966 |
39 |
|
PDAR |
19 |
12334 |
649 |
26 |
|
PETK |
4 |
2868 |
717 |
29 |
|
TXAR |
15 |
17199 |
1146 |
46 |
|
ULM |
13 |
13883 |
1067 |
43 |
|
USRK |
5 |
1874 |
374 |
15 |
|
YBH |
8 |
6579 |
822 |
33 |
|
YKA |
11 |
14542 |
1322 |
53 |
|
ZALV |
6 |
7348 |
1224 |
49 |
The
central part of the NTS lacks XSEL events as there are no MEs close to the
central point in the 20 MEs set. There are seven ME closer to the NTS center.
They are weaker than the MEs used for the routine WCC processing and have less
associated IMS station - only those within the North America and station BVAR
in Kazakhstan, which is characterized by very low-amplitude seismic noise and
high sensitivity to the events within the NTS. In order to reduce the detection
threshold for the central part of the NTS the stochastic noise component was
added to the data before the WCC detection.
Table 2 presents the average detection rates for the 22 June, 2020. The
rates at stations TXAR and YKA increased dramatically - by a factor of 3. At the same time, all 3-C
stations demonstrate the rates around 1 per hour. Station NVAR near the edge of
the acceptable zone with 83 detections per hour for an average ME. The
detection thresholds at YKA and TXAR should be tuned to the level of 80 if the
elevated rates distort the LA process and generate too many event hypotheses.
Table 2. June
18, 2020. Station detection rate for WCC processing with stochastic noise
|
Station |
ME |
Total detections |
Detections per ME |
Detections per ME per hour |
|
NVAR |
7 |
7522 |
1074 |
83 |
|
BVAR |
1 |
1064 |
1064 |
43 |
|
TXAR |
6 |
10559 |
1759 |
135 |
|
PDAR |
7 |
6248 |
892 |
69 |
|
ILAR |
2 |
1357 |
678 |
52 |
|
YKA |
5 |
9950 |
1990 |
153 |
|
ELK |
3 |
100 |
33 |
3 |
|
ANMO |
3 |
28 |
9 |
1 |
|
ULM |
1 |
5 |
5 |
1 |
|
YBH |
1 |
4 |
4 |
1 |
Figure 5. XSEL
events for the weak LA setting.
Figure 6. Master events and 31 event hypotheses for the period between June 18 and June 24, 2020.
The
results of the LA process for the 7 MEs, with StochN varying from 0 to 20, are presented in Figure 6 with the
original data listed in Appendices 3 (XSEL catalog) and 4 (XSEL bulletin).
There are 31 XSEL event hypotheses distributed near the MEs. The radius of
virtual location grid is also 60 km and several XSEL events are tens of
kilometers far from the corresponding MEs. There also hypotheses very close to
the MEs. All XSEL hypotheses have 5 to 6 associated stations and the event
weight above 40 as the evidence of their high statistical significance. The
XSEL bulletin shows that stations YKA and TXAR have no extraordinary
association rate due to the abundance of detections. Moreover, the low
detection rate at 3-C stations does not prevent them to be an important
contributor to the XSEL. This observation means that stations ANMO and ELK
provide a larger share of valid detections.
On 21
June, 2020, there were three XSEL events and five on June 22, 2020. These
events are weak and were not found neither by standard IDC processing (no REB
events) nor by routine WCC processing. The WCC processing with stochastic noise
allowed to create 31 XSEL event hypotheses with high statistical significance.
Therefore, the NTS monitoring can be enhanced in the future.
Discussion
The IMS includes many legacy seismic stations
historically focused on former nuclear test sites such as Nevada (NTS),
Semipalatinsk (STS), Novaya Zemlya of Russia, Lop Nor of China, etc. Therefore,
the final configuration of the IMS primary stations has some targets with lower
detection threshold and some places with higher thresholds. By design, the
number of primary stations located within continents have to be appropriate to
provide the best detection capability of low-magnitude events. The focus on the
known test sites makes the other territories to suffer higher detection
thresholds.
This
fact is even more negative to the CTBT monitoring regime when the possibility
of various evasion scenarios are considered. The most efficient method to
reduce the share of seismic energy emitted by an underground test is to conduct
it in a large underground cavity [Latter et
al., 1961]. This method is called cavity decoupling and is based on a
physical phenomenon of much faster shock wave attenuation in air or vacuum than
in solid rock. The shock wave energy is converted into heat in air, and into
solid rock kinetic energy for tamped explosions. For a 1 kt explosion, radius
of a spherical cavity in salt should be around 20 m to provide full or maximum
possible seismic decoupling [Adushkin et
al., 1993]. The radius increasing beyond that for the full decoupling does
not affect the high-frequency wave generation and thus does not harm detection
by IMS stations. The decoupling factor, i.e. the reduction in the seismic wave
amplitude relative to the fully tamped explosion in the identical conditions,
depends on rock type and cavity shape. However, the shape does not play a
critical role and an elongated tunnel provides a decoupling factor close to the
most efficient spherical case [Murphy et
al., 1997].
The
best places to construct a cavity for seismic decoupling as an evasion scenario
are those where the products of detonation cannot reach the atmosphere. Salt
deposits are perfect places for decoupling and they are usually far from the
test site [Sykes, 1996]. For example, the Salmon/Sterling cavity decoupling
experiment was conducted in Mississippi [Springer et al., 1968; Healy et al.,
1971]. In the Soviet Union, a similar experiment was conducted in the
pre-Caspian salt deposits [Adushkin et al.,
1993]. This makes the station distribution around test sites not optimal as the
focus is on the places where the efficient evasion methods are not applicable.
The
CTBT monitoring regime has the seismic technology as the first source of
information on the potential violation since the compression elastic waves in
the earth are propagating at velocities above
8 km/s and arrive at IMS seismic stations within a few minutes after any
event elsewhere. Prompt processing of
the data from the IMS by the IDC allows
quick assessment of the event potential importance for the Treaty. The IDC issues
various internal and official products such as seismic bulletins and catalogues.
The quality of these products matches the highest standard of statistical
significance and reliability. This makes the products prone to potential
incompleteness in the population of weak sources, which are difficult to find,
assess their quality and interpret nature.
The
States Parties to the CTBT are flexible in applying the own methods of
monitoring, focusing on specific regions and source types. They can also
announce their concern related to the potential violation of the Treaty by
other Member State(s). The independent research
community have conducted a lot of studies since the start of nuclear testing to
provide the best methods for the Treaty monitoring. There was a invaluable scientific support for
the understanding of the magnitude dependence on rock type when the violation
of the Threshold Test Ban Treaty was
discussed. The usage of NTS yield-magnitude curve for Semipalatinsk Test
Site was a later admitted mistake. Seismic efficiency of explosions in dry
alluvium and tuff is by almost an order of magnitude lower than that for the
explosions in hard anhydrite.
The
research community continue to develop and test various techniques and methods
to improve the resolution and
sensitivity of the IMS network and to enhance processing. The waveform
cross-correlation method (WCC) reduces the detection threshold and improves the
accuracy of the principal parameters estimation. When applied to seismic activity
at the Nevada Test Site, the WCC-based methods allow to find dozens of events
not detected by the IDC. The monitoring regime of the NTS can be significantly
improved by using the approach developed in this study. The IMS data has to be
used for further investigation of the local/regional seismicity in the areas of
interest in order to be ready for potential changes in the testing policy.
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