Performance of a rotational sensor at Etna, Italy focusing on back-azimuth estimations of volcano-seismic events

<p>The field of rotational seismology has only recently emerged. Portable 3 component rotational sensors are commercially available since a few years which opens the pathway for a first use in volcano-seismology. The combination of rotational and translational components of the wavefield allows identifying and filtering for specific seismic wave types, estimating the back azimuth of an earthquake, and calculating local seismic phase velocities.</p><p>Our work focuses on back-azimuth calculations of volcano-tectonic and long-period events detected at Etna volcano in Italy. Therefore, a continuous full seismic wavefield of 30 days was recorded by a BlueSeis-3A, the first portable rotational sensor, and a broadband Trillium Compact seismometer located next to each other at Mount Etna in August and September of 2019. In this study, we applied two methods for back-azimuth calculations. The first one is based on the similarity of the vertical rotation rate to the horizontal acceleration and the second one uses a polarization analysis from the two horizontal components of the rotation rate. The estimated back-azimuths for volcano-tectonic events were compared to theoretical back-azimuths based on the INGV event catalog and the long-period event back-azimuths were analyzed for their dominant directions. We discuss the quality of our back azimuths with respect to event locations and evaluate the sensitivity and benefits of the rotational sensor focusing on volcano-seismic events on Etna regarding the signal to noise ratios, locations, distances, and magnitudes.</p>

Six Degree-of-Freedom Broadband Ground-Motion Observations with Portable Sensors: Validation, Local Earthquakes, and Signal Processing

ABSTRACT The additional observation of three components of rotational ground motions has benefits for tilt-seismometer coupling (e.g., ocean-bottom seismometry and volcano seismology), local site characterization, wavefield separation, source inversion, glacial and planetary seismology, as well as the monitoring of structural health. Field applications have been mostly hampered by the lack of portable sensors with appropriate broadband operation range and weak-motion sensitivity. Here, we present field observations of the first commercial portable broadband rotation sensor specifically designed for seismology. The sensor is a three-component fiber-optic gyro strictly sensitive to ground rotation only. The sensor field performance and records are validated by comparing it with both array-derived rotation measurements and a navigation-type gyro. We present observations of the 2018 Mw 5.4 Hualien earthquake and the 2016 central Italy earthquake sequence. Processing collocated rotation and classical translation records shows the potential in retrieving wave propagation direction and local structural velocity from point measurements comparable to small-scale arrays of seismic stations. We consider the availability of a portable, broadband, high sensitivity, and low self-noise rotation sensor to be a milestone in seismic instrumentation. Complete and accurate ground-motion observations (assuming a rigid base plate) are possible in the near, local, or regional field, opening up a wide range of seismological applications.

Volcano Ambient Noise Interferometry in the Caribbean (VANIC)

<p><span><span>The hazardous stratovolcanoes in the Lesser Antilles island arc are monitored with sparse seismic networks. The application of ambient noise interferometry to monitor seismic velocity variations (dv/v) on data from such a sparse instrumented volcanic environment often is a challenge. For the purpose of monitoring it is important a) to analyse the applicability of, and differences between, cross- and single-station cross-correlations, b) to estimate the base level of seismic velocity variations during quiet times and c) to understand the characteristics. Within the EUROVOLC instrument “Transnational Access (TA)” a proposal called VANIC was supported to a) use and evaluate different types of ambient noise cross correlations (single stations vs. multiple stations; auto, cross and cross-component correlations) to be applied on seismic recordings from the Guadeloupe seismic network on La Soufriere, b) compare the results with dv/v base level estimates from the sparse Netherlands Caribbean network on The Quill and Mt. Scenery and c) start collaboration between OVSG and KNMI on both monitoring and research levels with a focus on volcano seismology. This presentation will focus is on the results obtained during the TA visit to OVGS.</span></span></p>

Multistage adaptive spectral subtraction of seismic signals

<p>The detection of microearthquakes is an important task in various seismological applications as volcano seismology, induced seismicity, and mining safety. In this work we have developed a novel technique in order to improve the quality and efficiency of STA/LTA based detection of microearthquakes. This technique consists of different stages of filtering employing an adaptive spectral subtraction method, which allows greatly improving the signal/noise ratio.</p><p>The implemented technique consists in a preliminary band-pass filtering of the signal followed by different stages of an adaptive spectral subtraction. The spectral subtraction technique is a non-linear filtering which allows taking into account the actual noise spectrum shape. It allows achieving a good filtering even in cases where the signal and noise spectrum overlaps. In order to take into account of the temporal variation in the background noise spectrum, we designed an adaptive technique. We first divide the incoming signals into short temporal windows. Each window is classified as “noise only” or “meaningful signal” (which can be either a microearthquake or any other relevant transient signal) using different features as the signal energy and the zero-crossing rate. Windows classified as “noise only” are continuously accumulated in a dynamic buffer which allows the average noise spectrum to be estimated and updated in an adaptive manner. This technique can be applied on subsequent stages to further improve the signal/noise ratio. This technique has been implemented in Python for the automatic detection of the microearthquakes on both off-line and near-real time data.</p><p>In order to check the efficiency of the results, we compared the results of an STA/LTA based automatic detection on the initial band-pass filtered signal and on the spectral subtracted signals after different stages of filtering. A notable improvement of the quality of the detection process is observed when repeated spectral subtraction stages are applied. </p><p>We applied this procedure to seismic data recorded by Red Sísmica Canaria, managed by Instituto Volcanológico de Canarias (INVOLCAN), on Tenerife (Canary Islands), comparing results from the proposed detection algorithm with standard approaches as well as with manual detections. We present an extensive statistical analysis of the results, determining the percentage of correct detections, novel detections, false positives and false negatives after each stage of filtering. First results have shown that this technique is also able to detect automatically microearthquakes which went undetected after a manual analysis.</p>

Automatic transient signal detection and volcanic tremor extraction using music information retrieval strategies

<p>Volcanic tremor is one of the most important signal in volcano seismology because of its potential to be a tool for forecasting eruptions and better understanding of underlying volcanic process. Despite different suggested mechanisms for volcanic tremor generation, the exact process of that is not well understood yet. This signal usually comes along with large number of earthquakes happening during unrest period that affect the shape and amplitude of tremor. A delicate signal processing is required to separate earthquakes and other transient signals from seismic waveform to derive a time series of volcanic tremor which can provide a new insight into tremor source investigations. Exploiting the idea of harmonic and percussive separation in musical signal processing we have developed a method to extract volcanic tremor and transient events from the seismic signal. By using the concept of periodicity as underlying generation process of tremor, we are able to extract the volcanic tremor signal based on the self similarity properties of spectra in time-frequency domain. The separation process results in two spectrograms representing repeating (long-lasting) and non-repeating (short-lived) patterns.</p><p>From the spectrogram of the repeating pattern we reconstruct the signal in time domain by adding the original spectrogram’s phase information, thus creating an modified version of the long-lasting tremor signal.</p><p>Further, we can derive a characteristic function for transient events by integrating the amplitude of the non-repeating spectrogram in each time frame. This function has non zero value in transient event instances and zero value in time periods devoid of such events. Considering transient events as earthquakes we apply an onset detector to time first arrivals of the transient signal by using the slope of the function. First we determine local maxima of the function showing good correspondence to even the tiniest transient signals. From the peak locations we calculate the slope of each point within a period of 6 seconds preceding each peak. The uncertainty of positive P peaks is up to 0.32 seconds which is equal to the hope size of the calculated spectrogram. The advantage of timing earthquakes through this method is the ability of detecting very low seismic events, although due to the small window size of short time Fourier transform the process is time consuming. The result of this study is promising, while further testing is on-going to validate the method as well as determine applications and limitations.</p>

FAME: Fibre optic cables: an Alternative tool for Monitoring volcanic Events

<p>In the framework of EUROVOLCs Trans-national grants, we propose the FAME project aiming at validating Distributed Acoustic Sensing (DAS) technology as a complementary and alternative tool for monitoring volcanic and seismic activity at Etna volcano. DAS technology provides records of strain signals with unprecedented spatial and temporal resolution.</p><p>We deployed a fibre optic cable connected to an iDAS (Silixa) interrogator set-up at the Observatory Pizzi Deneri in the summit area. To allow for a continuously recording of the iDAS, a solar panel power system was designed using battery back-up and inverter to supply 200 W at 220 V/AC. An internet connection was set up for a full remote control capability. The iDAS interrogated a 1.5 km long fibre cable, buried at a depth of about 30 cm by digging a trench in Piano delle Concazze area. The DAS measurements were validated with conventional measurements from 26 broadband seismometers and 3 arrays of 3 infrasound sensors from the Geophysical Instrument Pool Potsdam (GIPP). We deployed instruments along the fibre optic cable, covering an area of about 0.1 km2. The DAS and conventional sensors acquired data from 4 July to 23 September 2019 without major interruptions.</p><p>Here, we show key features of this the extraordinary multidisciplinary dataset. Thanks to the high spatial resolution (2 m), we could find locations of hypothesized faults in Piano delle Concazze area. Thanks to the long acquisition period, we continuously tracked Etna activity, marked by several eruptive episodes, including ash emissions, strombolian and effusive activities from the summit craters. The most intense and sustained eruptive events occurred in 18-20 July, 27-28 July and 9-13 September. We investigate the application of well-established analysis techniques in volcano-seismology to DAS dataset in order to assess the performance of the system in detecting and characterizing volcanic events.</p><p>Our findings demonstrate that DAS technology can record on a long term basis volcanic activity, which suggests DAS technology can be integrated to volcanic monitoring systems.</p>

PROLOGUE

<p>In 1989 the first bases of what is now a strong and consolidated Spanish-Italian scientific relationship in Seismology and in Volcano-Seismology were established. The first stage took place at the University of Catania, in the former Department of Earth Sciences, placed in the old Science Faculty, when a pre-doctoral student from the University of Granada, Cartuja Observatory (now called Andalusian Institute of Geophysics), arrived to complete his formation in seismology. During this stage, in addition to the training process, new contacts with researchers and mainly with pre-doctoral students of the former International Institute of Volcanology of the Italian National Research Council (IIV-CNR) were stablished. These contacts have endured, grown and created a strong international scientific network with consolidated and credible research production. In a short time new working groups were integrated such as the Osservatorio Vesuviano in Naples or the Department of Physics of the University of Salerno from the Italian side, and the Department of Applied Physics of the University of Almería or the Volcanology Department of the Spanish Research Council (CSIC) in Spain. At the present this non-official (but very active) network comprises many Italian Research Centers belonging to the National Institute of Geophysics and Volcanology (INGV) such as Catania, Naples, Rome, Palermo, Pisa or Bologna; Italian Universities as Salerno, Naples, L’Aquila or Calabrian, several Spanish Universities such as Granada, Almería, Jaen, Complutense, Cádiz or La Laguna, but also from other countries such as USA, Russia, Ireland, Portugal, México, Argentina, Germany, France, Norway or UK among others. This collaboration includes a continuous pre-doctoral students training protocols in which the exchange of fellows among the different institutions is fluent. [...]</p>