The RAMONES Service for Rapid Assessment of Seismic Moment and Radiated Energy in Central Italy: Concepts, Capabilities, and Future Perspectives

2021 ◽  
Author(s):  
Daniele Spallarossa ◽  
Matteo Picozzi ◽  
Davide Scafidi ◽  
Paola Morasca ◽  
Chiara Turino ◽  
...  
Keyword(s):  
Seismic Moment ◽  
Rapid Assessment ◽  
Central Italy ◽  
Web Interface ◽  
S Wave ◽  
Data Set ◽  
Decomposition Approach ◽  
Peak Displacement ◽  
Radiated Energy ◽  
Attenuation Models

Abstract We present Rapid Assessment of MOmeNt and Energy Service (RAMONES), a service for disseminating through a web interface, the estimates of seismic moment (M0) and radiated energy (ER) for earthquakes occurring in central Italy with local magnitudes above 1.7. The service is based on a fully-automatic procedure developed for downloading and processing open seismological data from the European Integrated Data Archive, Italian Civil Protection repository, and Incorporated Research Institutions for Seismology (IRIS). In its actual configuration, RAMONES uses the seismic catalog generated through the event webservice of the Italian Institute of Geophysics and Volcanology (compliant with International Federation of Digital Seismograph Networks standards) to guide the data download. The concept of RAMONES is to estimate M0 and ER from features extracted directly from recordings, namely the S-wave peak displacement (PDS) and the integral of the squared velocity (IV2S) evaluated over the S-wave window at local distances. A data set composed of 6515 earthquakes recorded in central Italy between 2008 and 2018 was used to calibrate the attenuation models relating M0 to PDS and ER to IV2S, including station corrections. The calibration values for M0 and ER were extracted from the source spectra obtained by applying a decomposition approach to the Fourier amplitude spectra known as the generalized inversion technique. To test the capabilities of RAMONES, we validate the attenuation models by performing residual analysis over about 60 earthquakes occurring in 2019 that were used for the spectral decomposition analysis but not considered in the calibration phase. Since January 2020, a testing operational phase has been running, and RAMONES has analyzed about 800 earthquakes by September 2020. The distribution of the source parameters and their relevant scaling relationships are automatically computed and disseminated in the form of maps, parametric tables, figures, and reports available through the RAMONES web interface.

Real-time monitoring of seismic moment and radiated energy

2020 ◽  
Author(s):  
Davide Scafidi ◽  
Daniele Spallarossa ◽  
Matteo Picozzi ◽  
Dino Bindi
Keyword(s):  
Real Time ◽  
Seismic Moment ◽  
P Wave ◽  
Calibration Data ◽  
S Wave ◽  
Data Set ◽  
Local Networks ◽  
Radiated Energy ◽  
The Impact ◽  
Large Earthquakes

<p>Understanding the dynamics of faulting is a crucial target in earthquake source physics (Yoo et al., 2010). To study earthquake dynamics it is indeed necessary to look at the source complexity from different perspectives; in this regard, useful information is provided by the seismic moment (M0), which is a static measure of the earthquake size, and the seismic radiated energy (ER), which is connected to the rupture kinematics and dynamics (e.g. Bormann & Di Giacomo 2011a). Studying spatial and temporal evolution of scaling relations between scaled energy (i.e., e = ER/M0) versus the static measure of source dimension (M0) can provide valuable indications for understanding the earthquake generation processes, single out precursors of stress concentrations, foreshocks and the nucleation of large earthquakes (Picozzi et al., 2019). In the last ten years, seismology has undergone a terrific development. Evolution in data telemetry opened the new research field of real-time seismology (Kanamori 2005), which targets are the rapid determination of earthquake location and size, the timely implementation of emergency plans and, under favourable conditions, earthquake early warning. On the other hand, the availability of denser and high quality seismic networks deployed near faults made possible to observe very large numbers of micro-to-small earthquakes, which is pushing the seismological community to look for novel big data analysis strategies. Large earthquakes in Italy have the peculiar characteristic of being followed within seconds to months by large aftershocks of magnitude similar to the initial quake or even larger, demonstrating the complexity of the Apennines’ faults system (Gentili and Giovanbattista, 2017). Picozzi et al. (2017) estimated the radiated seismic energy and seismic moment from P-wave signals for almost forty earthquakes with the largest magnitude of the 2016-2017 Central Italy seismic sequence. Focusing on S-wave signals recorded by local networks, Bindi et al. (2018) analysed more than 1400 earthquakes in the magnitude ranges 2.5 ≤ Mw ≤ 6.5 of the same region occurred from 2008 to 2017 and estimated both ER and M0, from which were derived the energy magnitude (Me) and Mw for investigating the impact of different magnitude scales on the aleatory variability associated with ground motion prediction equations. In this work, exploiting first steps made in this direction by Picozzi et al. (2017) and Bindi et al. (2018), we derived a novel approach for the real-time, robust estimation of seismic moment and radiated energy of small to large magnitude earthquakes recorded at local scales. In the first part of the work, we describe the procedure for extracting from the S-wave signals robust estimates of the peak displacement (PDS) and the cumulative squared velocity (IV2S). Then, exploiting a calibration data set of about 6000 earthquakes for which well-constrained M0 and theoretical ER values were available, we describe the calibration of empirical attenuation models. The coefficients and parameters obtained by calibration were then used for determining ER and M0 of a testing dataset</p>

scholarly journals Earthquake Seismic Moment, Rupture Radius and Stress-drop from P-wave Displacement Amplitude vs Time Curves

2021 ◽  
Author(s):  
aldo zollo ◽  
sahar nazeri ◽  
Simona Colombelli
Keyword(s):  
Stress Drop ◽  
Seismic Moment ◽  
Central Italy ◽  
Average Stress ◽  
Displacement Amplitude ◽  
P Wave ◽  
Parametric Modelling ◽  
Peak Displacement ◽  
Reliable Determination ◽  
Anelastic Attenuation

The reliable determination of earthquake source parameters is a relevant task of seismological investigations which ground nowadays on high quality seismic waveforms collected by near-source dense arrays of ground motion sensors. Here we propose a parametric modelling technique which analyzes the time-domain P-wave signal recorded in the near-source range of small-to-large size earthquakes. Assuming a triangular moment-rate function and a uniform speed, circular rupture model, we develop the equations to estimate the seismic moment, rupture radius and stress-drop from the corner-time and plateau level of the average logarithm of the P-wave displacement vs time curves (LPDT). The constant-Q, anelastic attenuation effect is accounted by a post-processing procedure that evaluates the Q-unperturbed moment-rate triangular shape.<br>The methodology has been validated through the application to the acceleration records of the 2016-2017 Central Italy and 2007-2019 Japan earthquake sequences covering a wide moment magnitude range (Mw 2.5 - 6.5) and recording distance < 100 km. After correcting for the anelastic attenuation function, the estimated average stress-drop and the confidence interval (〈∆σ〉=0.60 (0.42-0.87) MPa and 〈∆σ〉=1.53 (1.01-2.31) for crustal and subcrustal events of Japan and 〈∆σ〉=0.36(0.30-0.44) MPa for Central Italy) show, for both regions, a self-similar, constant stress-drop scaling of the rupture duration/radius with seismic moment. The smaller sensitivity of the spatially averaged, time-varying peak displacement amplitude to the radiation from localized high slip patch on the fracture surface, could explain the retrieved smaller average stress-drops for sub-crustal earthquakes in Japan and M>5.5 events in Central Italy relative to previous estimates using spectral methods.<br><br>

scholarly journals Earthquake Seismic Moment, Rupture Radius and Stress-drop from P-wave Displacement Amplitude vs Time Curves

2021 ◽  
Author(s):  
aldo zollo ◽  
sahar nazeri ◽  
Simona Colombelli
Keyword(s):  
Stress Drop ◽  
Seismic Moment ◽  
Central Italy ◽  
Average Stress ◽  
Displacement Amplitude ◽  
P Wave ◽  
Parametric Modelling ◽  
Peak Displacement ◽  
Reliable Determination ◽  
Anelastic Attenuation

The reliable determination of earthquake source parameters is a relevant task of seismological investigations which ground nowadays on high quality seismic waveforms collected by near-source dense arrays of ground motion sensors. Here we propose a parametric modelling technique which analyzes the time-domain P-wave signal recorded in the near-source range of small-to-large size earthquakes. Assuming a triangular moment-rate function and a uniform speed, circular rupture model, we develop the equations to estimate the seismic moment, rupture radius and stress-drop from the corner-time and plateau level of the average logarithm of the P-wave displacement vs time curves (LPDT). The constant-Q, anelastic attenuation effect is accounted by a post-processing procedure that evaluates the Q-unperturbed moment-rate triangular shape.<br>The methodology has been validated through the application to the acceleration records of the 2016-2017 Central Italy and 2007-2019 Japan earthquake sequences covering a wide moment magnitude range (Mw 2.5 - 6.5) and recording distance < 100 km. After correcting for the anelastic attenuation function, the estimated average stress-drop and the confidence interval (〈∆σ〉=0.60 (0.42-0.87) MPa and 〈∆σ〉=1.53 (1.01-2.31) for crustal and subcrustal events of Japan and 〈∆σ〉=0.36(0.30-0.44) MPa for Central Italy) show, for both regions, a self-similar, constant stress-drop scaling of the rupture duration/radius with seismic moment. The smaller sensitivity of the spatially averaged, time-varying peak displacement amplitude to the radiation from localized high slip patch on the fracture surface, could explain the retrieved smaller average stress-drops for sub-crustal earthquakes in Japan and M>5.5 events in Central Italy relative to previous estimates using spectral methods.<br><br>

The matter of size: On the moment magnitude of microseismic events

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. KS31-KS41 ◽  
Author(s):  
Wenjie Jiao ◽  
Michael Davidson ◽  
Arcangelo Sena ◽  
Bradley L. Bankhead ◽  
Yu Xia ◽  
...  
Keyword(s):  
Seismic Moment ◽  
Body Wave ◽  
Attenuation Factor ◽  
Moment Magnitude ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Microseismic Events ◽  
The Moment ◽  
Scalar Moment

We investigated the method of estimating seismic moment and moment magnitude for microseismic events. We determined that the [Formula: see text] defined by Bowers and Hudson is the proper scalar moment to be used in microseismic studies for characterizing the size of an event and calculating its moment magnitude. For non-double-couple sources, the proportional relationship between body-wave amplitude and seismic moment in the Brune model breaks down. So under such situations, the Brune model is not an appropriate way to estimate the seismic moment and magnitude. Moreover, the S-wave alone is not sufficient for determining the total seismic moment. Instead, the P-wave must be analyzed. An example Barnett Shale data set was studied, and the results concluded that the magnitudes estimated with the Brune model could be off by as much as 1.92, with an absolute average of 0.35. The moment magnitudes based on the scalar moment [Formula: see text] also gave a significantly different event size distribution and b-value estimation. Finally, attenuation also played a role in estimating the moment magnitude. With a typical average attenuation factor of [Formula: see text], the average magnitude correction for our field data set was on the order of 0.15. However, it could reach 0.3 for events far away from the monitoring well.

scholarly journals An automatically generated high-resolution earthquake catalogue for the 2016–2017 Central Italy seismic sequence, including P and S phase arrival times

2020 ◽  
Author(s):  
D Spallarossa ◽  
M Cattaneo ◽  
D Scafidi ◽  
M Michele ◽  
L Chiaraluce ◽  
...  
Keyword(s):  
Real Time ◽  
Central Italy ◽  
Earthquake Catalogue ◽  
Hazard Evaluation ◽  
Depth Range ◽  
Data Set ◽  
Epicentral Area ◽  
Earthquake Parameters ◽  
Waveform Data ◽  
Arrival Times

Summary The 2016–17 central Italy earthquake sequence began with the first mainshock near the town of Amatrice on August 24 (MW 6.0), and was followed by two subsequent large events near Visso on October 26 (MW 5.9) and Norcia on October 30 (MW 6.5), plus a cluster of 4 events with MW &gt; 5.0 within few hours on January 18, 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450,000 events in the year following the first mainshock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hours on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84,401 to 450,000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ± 0.9km in epicentral location and ± 1.5km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting.

On the mN, M Relation for Eastern North American Earthquakes

1987 ◽  
Vol 58 (4) ◽  
pp. 119-124 ◽  
Author(s):  
Gail M. Atkinson ◽  
David M. Boore
Keyword(s):  
North America ◽  
Stochastic Model ◽  
Ground Motion ◽  
Seismic Moment ◽  
The Other ◽  
Moment Magnitude ◽  
Scaling Relations ◽  
Eastern North America ◽  
Data Set ◽  
Meaningful Data

Abstract A stochastic model of ground motion has been used as a basis for comparison of data and theoretically-predicted relations between mN (commonly denoted by mbLg) and moment magnitude for eastern North America (ENA) earthquakes. mN magnitudes are recomputed for several historical ENA earthquakes, to ensure consistency of definition and provide a meaningful data set. We show that by itself the magnitude relation cannot be used as a discriminant between two specific spectral scaling relations, one with constant stress and the other with stress increasing with seismic moment, that have been proposed for ENA earthquakes.

Hierarchical production planning in forestry using price-directed decomposition

2007 ◽  
Vol 37 (10) ◽  
pp. 2010-2021 ◽  
Author(s):  
Samuel D. Pittman ◽  
B. Bruce Bare ◽  
David G. Briggs
Keyword(s):  
Production Planning ◽  
Net Present Value ◽  
Forest Planning ◽  
Planning Model ◽  
Data Set ◽  
Decomposition Approach ◽  
Hierarchical Production Planning ◽  
Production Models ◽  
Planning Models ◽  
Land Inventory

Forest planning models have increased in size and complexity as planners address a growing array of economic, ecological, and societal issues. Hierarchical production models offer a means of better managing these large and complex models. Hierarchical production planning models decompose large models into a set of smaller linked models. For example, in this paper, a Lagrangian relaxation formulation and a modified Dantzig–Wolfe decomposition – column generation routine are used to solve a hierarchical forest planning model that maximizes the net present value of harvest incomes while recognizing specific geographical units that are subject to harvest flow and green-up constraints. This allows the planning model to consider forest-wide constraints such as harvest flow, as well as address separate subproblems for each contiguous management zone for which detailed spatial plans are computed. The approach taken in this paper is different from past approaches in forest hierarchical planning because we start with a single model and derive a hierarchical model that addresses integer subproblems using Dantzig–Wolfe decomposition. The decomposition approach is demonstrated by analyzing a set of randomly generated planning problems constructed from a large forest and land inventory data set.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

scholarly journals Rapid assessment of S-wave profiles from the inversion of multichannel

1998 ◽  
Vol 41 (1) ◽  
Author(s):  
G. A. Tselentis ◽  
G. Delis
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Structure ◽  
Rapid Assessment ◽  
Detailed Knowledge ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Wave Profiles ◽  
Shear Wave Velocity Structure

The importance of detailed knowledge of the shear-wave velocity structure of the upper geological layers was recently stressed in strong motion studies. In this work we describe an algorithm which we have developed to infer the 1D shear wave velocity structure from the inversion of multichannel surface wave dispersion data (ground-roll). Phase velocities are derived from wavenumber-frequency stacks while the inversion process is speeded up by the use of Householder transformations. Using synthetic and experimental data, we examined the applicability of the technique in deducing S-wave profiles. The comparison of the obtained results with those derived from cross-hole measurements and synthesized wave fields proved the reliability of the technique for the rapid assessment of shear wave profiles during microzonation investigations.

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