IS42 was certified on December 2010 and is one of the infrasound stations of the International Monitoring System (IMS) of the Preparatory Commission of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The station is installed on Graciosa Island (Azores archipelago, Portugal), in the North Atlantic Ocean. The layout of eight array components together with its geographical...
In explosion monitoring, seismic arrays offer significant signal to noise improvements and enhanced ability to detect and locate important events. This advantage can be significantly degraded, however, in the presence of noise on the array components. For automated processing methods, this may result in a failure to identify an important signal, since many methods use thresholds. For a chronic...
Seismic signal detection and phase arrival picking had been initially carried out manually by qualified analysts. Currently, the introduction of large digital seismic monitoring networks has led to the necessity of automatic detection and picking tasks. The latter are extremely important, not only because an earthquake or a nuclear explosion must be detected and located automatically, but also...
Array processing is routinely used to measure apparent velocity and back-azimuth of seismic arrivals at the International Data Centre and many National Data Centres. Both quantities are measured under the plane wave assumption and are used to classify the phase type and to determine the direction towards the event epicentre. However, structural inhomogeneities can lead to deviations from the...
The International Data Centre (IDC) estimates several types of seismic magnitudes. Two of them are: the body wave magnitude mb, and the surface wave magnitude Ms. Both measures are significant to the CTBT verification regime as an input for discrimination methods between earthquakes and explosions, while mb is used for yield estimation for a presumed explosion. The IDC, like other institutes,...
This paper summarizes the advances in the application of machine learning to seismic monitoring data processing. Then it focuses on our work including local events detection based on multi-task Convolutional neural network (CNN), Generative Adversarial Network - Long Short-Term Memory(GAN-LSTM) joint network applied to seismic noise signal recognition, the seismic phase sequence detection...
All States Parties have convenient access to all International Monitoring System (IMS) data, International Data Center (IDC) products and all applications and scientific studies programmes used in the IDC of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). We took advantage of this as the Iraqi National Data Center. in this study most of the research and studies related to the...
The Sliding Information Distance (SLID) metric is a compression based metric that can identify signal arrivals in seismic data. SLID has advantages over existing algorithms that are used for detecting arrival times because it can be used to calculate the certainty of each automated detection and to denote multiple possible arrival times in cases where the detections have low certainty. This...
In this continuously globalized world with its vulnerability in the event of deployment of nuclear weapons in conflicts, testing of nuclear device appears to have assumed a redefined aim far beyond the traditional conceptualization. This new function can be seen in the context of recent nuclear device tests by Democratic People Republic of Korea (DPRK). Nuclear device test scholarship has been...
We present results from our use and analysis of the most recent release of NIAB, which contains the NET-VISA associator integrated into SeisComp3 (SC3). This version allows for the configuration of non-International Monitoring System (IMS) stations using both the International Data Centre (IDC) DFX detector and NET-VISA. Non-IMS stations from the Australian network and from other regions of...
PhaseNet and EQTransformer are two deep learning methods most commonly used for automatic earthquake detection and phase-picking. This work presents the performance of these algorithms using two weeks of data retrieved from the Botswana Seismological Network stations. Additional data used is obtained from the International Monitoring System network within a distance of 250 km from Botswana...
The infrasound array in Hungary at Piszkés-tető (PSZI) has been collecting data since 2017. For signal processing, the Progressive Multichannel Cross-Correlation (PMCC) method is used, which resulted in about a million detections so far. Among these detections there are about 10 000 categorized, hand labelled events from quarry blasts, storms and power plant noise that constitute the dataset...
Seismic waves are emitted by events such as earthquakes, explosions, or other movements of materials within the Earth. The International Monitoring System comprises of a global network of seismic stations intended to identify and locate such events. The accurate estimation of the back-azimuth, or the angle of arrival, of these seismic signals remains a key challenge. Over the last decades,...
Seismic events are produced by different types of sources (e.g. local earthquakes, distant earthquakes, quarry blasts, nuclear explosions, volcano activity, etc.). These events are detected by seismic network stations and stored. The first important task in seismic signal processing is to identify the source of each detected event. This task should be performed automatically due to the large...
Seismic waveform data are generally contaminated by noise from various sources, which interfere with the signals of interest. In this study, we implemented and applied several noise suppression methods. The denoising methods, consisting of approaches based on nonlinear thresholding of continuous wavelet transforms (CWTs), convolutional neural network (CNN) denoising and frequency filtering,...
Indonesia’s active involvement in nuclear politics can be traced back to the preparation committee for the establishment of the International Atomic Energy Agency (IAEA). During its first decade of Independence, the Government of Indonesia (GoI) elaborated its international politics of non-block by becoming a member of IAEA notwithstanding the high cost effect of the membership. Supporting...
Discriminating the event type with seismic waveforms is a vital part of the verification work. In this research, 500 seismic events with a magnitude below 3.0 ML around Beijing were collected in the categories of: natural earthquake, blasting and mining collapse. More than 25 features and their ratio parameters were applied to characterize the seismic waveforms, which were extracted from P ...
An effective response to the threats and challenges of the 21st century can only be achieved through the coordinated efforts of the international community, through the UN and international law. Although the role and significance of the CTBT cannot be overestimated, this role has been hampered due to the inability of the CTBT to enter into force, because ratification by eight Annex 2 states is...
The CTBTO releases the Standard Events Lists (SELs) with information about the location, magnitude, time and depth of events identified from the automatic analysis of waveform data (seismic, hydroacoustic and infrasound). This automatic generated list of events could be evaluated using machine learning methods. Machine learning models work in two phases; training and testing. The training...
Seismic noise from a variety of nuisance sources frequently contaminates signals of interest. Effectively suppressing this noise is a crucial step in the processing pipeline. In a previous work, Tibi et al. (2021) developed a seismic signal denoising approach that uses a deep convolutional neural network (CNN) model to decompose an input waveform into a signal of interest and noise. While...
This work expands on a new method, called event-based training (EBT) which is primarily a tool to leverage large datasets with little or no ground truth, to build event discrimination models across the continental United States. We include data from the transportable array and other regional catalogs as well as including a null criteria to enable a model to abstain from decision making in the...
The International Monitoring System includes waveform sensor stations connected to a centralized processing system in the International Data Center. Recent tools at the IDC use Bayesian analysis to detect and localize seismic events, such as NET-VISA. While the Bayesian approach to seismic monitoring can improve significantly on the performance of classical systems, this approach needs prior...
The range-dependent Acoustic Model (RAM) is a prevalent underwater acoustics modelling program, which employs a 2-D parabolic equation method. Parabolic equation is known as an accurate and reliable method, and it has been extensively used in the underwater acoustic community. Even though the parabolic equation method requires less computation resources than many other methods, an efficient...
The Comprehensive Nuclear-Test-Ban Treaty (Treaty) of 1996 obliges its signatories not to undertake nuclear weapons tests. Kenya is a signatory to the Treaty and operates an infrasound and a primary seismic station in Nairobi. The city has a 2.8% urban growth rate and in 2019, its population was 4.3 million. An increase in anthropogenic activities directly impacts the International Monitoring...
We train deep learning models for seismic detection on 3-component stations from the International Monitoring System (IMS) based on PhaseNet architecture and evaluate the results using the Unconstrained Global Event Bulletin (UGEB). Using 14 years of associated signals from the Late Event Bulletin (LEB), we auto-curate a training data set consisting of signal windows containing associated...
From 2000, when official bulletin production at the International Data Centre (IDC) of the Provisional Technical Secretariat (PTS) started until 2012, comparisons of the Reviewed Event Bulletin (REB) with the Published Bulletin of the International Seismological Center (ISC) had been carried out. As numerous efforts have taken place since then, such as enhancing the automatic as well as the...
The first step in most seismological studies is detecting seismic events. Due to attenuation law, the interstation spacing of seismic networks plays a fundamental role in the capability of phase detection, so the inappropriate density of seismic stations reduces the detection capability. The immediate solution to this problem is to increase the density of stations. But, this is too expensive...
The objective of this study is to improve modeling underwater ambient noise below 100 Hz from local and distant wind. Historically, shipping is assumed to dominate ambient noise at this frequency band, however, the CTBTO hydroacoustic array off Crozet Island provides unique wind noise observations with minimal shipping interference. First, ambient noise is correlated to overhead windspeed...
This study presents a new method based on wavelet transform for moment tensor inversion. The method consists of a semi-automatic data preparation and source inversion prepared in python. The procedure is similar to the point source technique in the time domain but is adjusted using wavelet coefficients. The advantage of our algorithm is to test the centroid moment tensor in all frequency...
NET-VISA is a Physics-Based Generative Model of global scale seismology. The model includes a description of the generation of events which include underwater and atmospheric events, the propagation of waveform energy from the events in multiple phases, and the detection or mis-detection of these phases at the network of stations maintained by the International Monitoring System as well as a...
Nuclear justice associated with the humanitarian consequences of nuclear explosions has become a prominent issue in the broader nuclear weapons discussion since the 2010 NPT Review Conference when States Parties expressed their “deep concern at the catastrophic humanitarian consequences of any use of nuclear weapons." Notably, the term “nuclear justice” within this work exclusively refers to...
In this paper we conduct a study of on-site estimation of the time of arrival (ToA) strongly distorted acoustic signals. Propagation of the acoustic waves from sources is controlled by a complex interplay between source location, winds, temperature, humidity, atmospheric attenuation, and topography, which are the main factors that lead to signal distortion. An algorithm was developed (usable...
CTBTO observation and processing systems are required to be sensitive to low magnitude events. A promising way to increase system sensitivity and improve station tuning is to refine the receiver velocity models underneath International Monitoring System (IMS) stations by incorporating a number of ambient noise processing techniques into the International Data Centre (IDC) practice. In...
This study aims to explore novel physics-guided neural network (PGNN) algorithms as applied to time-domain source functions (TDSF) of explosions for automated emplacement material classification as well as the estimation of yield (W) and depth of burial (DOB) in a regression formulation. We assume that explosions are detonated at the center of cavities embedded in an infinite homogeneous...
This study uses 48 000 synthetically generated time-domain source functions (TDSF) to illustrate the performance of newly developed physics-guided neural network algorithms for classification of the emplacement conditions in materials where the explosions are detonated. TDSFs were constructed at the elastic radii of many explosions for material properties representing the granite, shale,...
Detection, localization, and characterization of energetic events in the atmosphere and at shallow depth of burial using infrasonic signals is often performed via an automated pipeline framework with refinement using interactive tools for an identified event-of-interest. Recent updates to the InfraPy signal analysis software suite authored and maintained by infrasound experts at Los Alamos...
Automatic detection of seismic events in processing pipelines at the International Data Centre and many National Data Centres is mostly done using beamforming on arrays; however, extensive use of single stations can improve the detection capability and accuracy of event location. Advances in deep learning methods enable faster and more accurate processing of large quantities of single station...
This study reviews performance of NET-VISA in operations (vsel3) and results of a full pipeline test of NET-VISA from 2021 in comparison with SELs. NET-VISA performed better than the standard global associator, GA, however several differences in how these algorithms form events were identified. These differences provided fewer constraints in event formation for NET-VISA in comparison with GA,...
In seismic signal analysis it's crucial to be able to distinguish between earthquakes and underground nuclear explosions, which is an important component of the Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO). Many methods have been used, such as the complexity, the spectral ratio, body wave and surface wave magnitudes (mb-Ms), and P and S corner frequencies. The data set of nuclear...
The classification of low magnitude seismic events is an important task in regional earthquake monitoring. This study focuses on the classification of earthquakes, explosions, and mining-induced earthquakes. A 36-dimensional feature extraction dataset was established through eight types of feature quantization methods, and two-classes and three-class models were respectively constructed by the...
Seismic event source identification using recorded signals could be a complex task to solve using classical mathematical methods. Alternatively, many recent research studies have opted for artificial intelligence techniques to deal with this classification problem. Indeed, artificial neural networks, particularly multilayer perceptron (MLP), are one of the techniques that have achieved good...
T waves signals at International Monitoring System hydrophone stations can present complex arrival characteristics caused by bathymetric features along their long range propagation paths through horizontal reflection, refraction, and diffraction. Thus, the interpretation of recorded T waves can be challenging due to differences in observed and expected arrival times, back-azimuths, or energy...
Large earthquakes and aftershock sequences substantially increase the burden of those who monitor seismic data for anthropogenic events. Fortunately, most aftershocks exhibit high degrees of similarity between their waveforms, making them well suited for detection and identification through waveform cross-correlation techniques. Such techniques pose some challenges, however, such as building...
NET-VISA is a Physics-Based Generative Model of global scale seismology. The model includes a description of the generation of events which include underwater and atmospheric events, the propagation of waveform energy from the events in multiple phases, and the detection or mis-detection of these phases at the network of stations maintained by the International Monitoring System as well as a...
We present an improvement to the multichannel maximum-likelihood (MCML) method. This approach is based on the likelihood function derived from a multi-sensor stochastic model expressed in different frequency channels. Using the likelihood function, we determine, for the detection problem, the generalized likelihood ratio with a p-value threshold to discriminate signal of interest and noise....
Studies on the CTBT universalization may benefit from understanding the social dimension of treaty ratification beyond techno-scientific endeavors. Within the emerging academic debate, the role of epistemic community, understood as a network of socially recognized experts in a highly technical issue, with the authority to translate scientific knowledge and social practice to certain policy...
