A functional tool to explore the reliability of micro-earthquake focal mechanism solutions for seismotectonic purposes

Improving the knowledge of seismogenic faults requires the integration of geological, seismological, and geophysical information. Among several analyses, the definition of earthquake focal mechanisms plays an essential role in providing information about the geometry of individual faults and the stress regime acting in a region. Fault plane solutions can be retrieved by several techniques operating in specific magnitude ranges, both in the time and frequency domain and using different data. For earthquakes of low magnitude, the limited number of available data and their uncertainties can compromise the stability of fault plane solutions. In this work, we propose a useful methodology to evaluate how well a seismic network, used to monitor natural and/or induced micro-seismicity, estimates focal mechanisms as a function of magnitude, location, and kinematics of seismic source and consequently their reliability in defining seismotectonic models. To study the consistency of focal mechanism solutions, we use a Bayesian approach that jointly inverts the P/S long-period spectral-level ratios and the P polarities to infer the fault plane solutions. We applied this methodology, by computing synthetic data, to the local seismic network operating in the Campania–Lucania Apennines (southern Italy) aimed to monitor the complex normal fault system activated during the Ms 6.9, 1980 earthquake. We demonstrate that the method we propose is effective and can be adapted for other case studies with a double purpose. It can be a valid tool to design or to test the performance of local seismic networks, and more generally it can be used to assign an absolute uncertainty to focal mechanism solutions fundamental for seismotectonic studies.

Development of Qube: A Low-Cost Internet of Things Device for On-Site and Regional Earthquake Warning

Earthquakes are a major global risk. The current earthquake early warning systems based on public seismic stations face challenges such as high cost, low density, high latency, no alert zone, and difficulty in predicting ground motions at the location of the user. This article pursues an alternative consumer-based approach. An Internet of Things consumer device, called a “Qube,” was built for a cost below $100 and is about the size of a Rubik’s cube. The Qube successfully detected earthquakes and issued earthquake warnings through sounding the onboard alarm for on-site warning and sending text messages to local subscribers for regional warning. The Qube is highly sensitive. During nine months of testing from September 2020 to May 2021, it detected all earthquakes over M 3.0 magnitude around Los Angeles, as well as nearby earthquakes down to M 2.3. The Qube uses a geophone for ground-motion velocity sensing and captures earthquake waveforms consistent with a nearby broadband seismometer in the Southern California Seismic Network. By analyzing data of the earthquakes detected by the Qube, an empirical logarithmic formula that is used to estimate local earthquake magnitude based on detected ground-motion amplitude in digital counts was developed. Although the Qube’s response in digital counts to ground-motion velocity in μm/s has not been determined, the empirical formula between Qube’s output and local earthquake magnitude suggests the Qube’s consistency in ground-motion measurement. The Qube has Wi-Fi connectivity and is controllable via a smartphone or computer. The combination of low cost, high sensitivity, and integrated alarm function of the Qube is intended to enable a consumer-based approach with the potential for mass adoption and use in dense networks, creating new opportunities for seismic network, earthquake warning, and educational applications.

SEISMICITY of the URALS and WESTERN SIBERIA in 2015

The article summarizes information about seismic network in the Urals and Western Siberia region, describes processing technique, presents a short analysis of the seismic activity in 2015. Seismic network capability is shown for the whole territory under control. It was found that about 82 % of registered events are explosions in mines and open pits, 37 events are natural or induced ones. For the strongest induced events, variants of source parameters obtained by different agencies are shown. The strongest tectonic event in 2015 and for the last century (after 1914) is the Middle Ural earthquake with ML=4.7, I0=6 that occurred on October 18, 2015.

On the Potential of 3D Transdimensional Surface Wave Tomography for Geothermal Prospecting of the Reykjanes Peninsula

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, surface waves retrieved through the application of seismic interferometry have also been exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a set of localized depth-dependent velocity profiles are obtained at the surface points. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation of the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. It also adapts model resolution to the amount of noise in the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from station–station cross correlations by the Reykjanes seismic network.

Imaging structure and geometry of slabs in the greater Alpine area – a P-wave travel-time tomography using AlpArray Seismic Network data

We perform a teleseismic P-wave travel-time tomography to examine the geometry and structure of subducted lithosphere in the upper mantle beneath the Alpine orogen. The tomography is based on waveforms recorded at over 600 temporary and permanent broadband stations of the dense AlpArray Seismic Network deployed by 24 different European institutions in the greater Alpine region, reaching from the Massif Central to the Pannonian Basin and from the Po Plain to the river Main. Teleseismic travel times and travel-time residuals of direct teleseismic P waves from 331 teleseismic events of magnitude 5.5 and higher recorded between 2015 and 2019 by the AlpArray Seismic Network are extracted from the recorded waveforms using a combination of automatic picking, beamforming and cross-correlation. The resulting database contains over 162 000 highly accurate absolute P-wave travel times and travel-time residuals. For tomographic inversion, we define a model domain encompassing the entire Alpine region down to a depth of 600 km. Predictions of travel times are computed in a hybrid way applying a fast TauP method outside the model domain and continuing the wave fronts into the model domain using a fast marching method. We iteratively invert demeaned travel-time residuals for P-wave velocities in the model domain using a regular discretization with an average lateral spacing of about 25 km and a vertical spacing of 15 km. The inversion is regularized towards an initial model constructed from a 3D a priori model of the crust and uppermost mantle and a 1D standard earth model beneath. The resulting model provides a detailed image of slab configuration beneath the Alpine and Apenninic orogens. Major features are a partly overturned Adriatic slab beneath the Apennines reaching down to 400 km depth still attached in its northern part to the crust but exhibiting detachment towards the southeast. A fast anomaly beneath the western Alps indicates a short western Alpine slab whose easternmost end is located at about 100 km depth beneath the Penninic front. Further to the east and following the arcuate shape of the western Periadriatic Fault System, a deep-reaching coherent fast anomaly with complex internal structure generally dipping to the SE down to about 400 km suggests a slab of European origin limited to the east by the Giudicarie fault in the upper 200 km but extending beyond this fault at greater depths. In its eastern part it is detached from overlying lithosphere. Further to the east, well-separated in the upper 200 km from the slab beneath the central Alps but merging with it below, another deep-reaching, nearly vertically dipping high-velocity anomaly suggests the existence of a slab beneath the eastern Alps of presumably the same origin which is completely detached from the orogenic root. Our image of this slab does not require a polarity switch because of its nearly vertical dip and full detachment from the overlying lithosphere. Fast anomalies beneath the Dinarides are weak and concentrated to the northernmost part and shallow depths. Low-velocity regions surrounding the fast anomalies beneath the Alps to the west and northwest follow the same dipping trend as the overlying fast ones, indicating a kinematically coherent thick subducting lithosphere in this region. Alternatively, these regions may signify the presence of seismic anisotropy with a horizontal fast axis parallel to the Alpine belt due to asthenospheric flow around the Alpine slabs. In contrast, low-velocity anomalies to the east suggest asthenospheric upwelling presumably driven by retreat of the Carpathian slab and extrusion of eastern Alpine lithosphere towards the east while low velocities to the south are presumably evidence of asthenospheric upwelling and mantle hydration due to their position above the European slab.

A Seismic Network to Monitor the 2020 EGS Stimulation in the Espoo/Helsinki Area, Southern Finland

We present the deployment of a seismic network in the Helsinki capital area of Finland that was installed to monitor the response to the second stimulation phase of an ∼6-kilometer-deep enhanced geothermal system in 2020. The network consists of a dozen permanent broadband stations and more than 100, predominantly short-period, temporary stations. This 2020 deployment is characterized by a mix of single stations and arrays with diverse configurations. It covers a larger area and exhibits a smaller azimuthal gap compared with the network that monitored the first stimulation in 2018. We surveyed the outcropping rocks at one of the large array sites to study surface expressions of shear or weakness zones that are possibly connected to the stimulated volume at depth. We link the relatively large number of macroseismic reports received during the stimulation to an increased public awareness of the project together with an increased sensitivity because the second stimulation occurred during the local COVID-19 mobility restrictions. The spatial distribution of the reports seems to be controlled by the radiation pattern of the induced earthquakes and hence by the stress state in the reservoir. The continuous records contain strong energy at high frequencies above 50 Hz that is attributed to anthropogenic processes in the densely populated urban area. However, the exceptionally low attenuation of the bedrock yields good signal-to-noise ratio seismograms of the induced small events, the largest of which was magnitude ML 1.2. The signal quality of the obtained noise correlation functions is similarly very good. The data set has been collected to underpin a wide range of seismic analysis techniques for complementary scientific studies of the evolving reservoir processes and the induced event properties. These scientific studies should inform the legislation and educate the public for transparent decision making around geothermal power generation.