Contamination of Frequency–Magnitude Slope (b-Value) by Quarry Blasts: An Example for Italy

Artifacts often affect seismic catalogs. Among them, the presence of man-made contaminations such as quarry blasts and explosions is a well-known problem. Using a contaminated dataset reduces the statistical significance of results and can lead to erroneous conclusions, thus the removal of such nonnatural events should be the first step for a data analyst. Blasts misclassified as natural earthquakes, indeed, may artificially alter the seismicity rates and then the b-value of the Gutenberg and Richter relationship, an essential ingredient of several forecasting models. At present, datasets collect useful information beyond the parameters to locate the earthquakes in space and time, allowing the users to discriminate between natural and nonnatural events. However, selecting them from webservices queries is neither easy nor clear, and part of such supplementary but fundamental information can be lost during downloading. As a consequence, most of statistical seismologists ignore the presence in seismic catalog of explosions and quarry blasts and assume that they were not located by seismic networks or in case they were eliminated. We here show the example of the Italian Seismological Instrumental and Parametric Database. What happens when artificial seismicity is mixed with natural one?

Long Memory in Earthquake Time Series: The Case Study of the Geysers Geothermal Field

The present study aims at proving the existence of long memory (or long-range dependence) in the earthquake process through the analysis of time series of induced seismicity. Specifically, we apply alternative statistical techniques borrowed from econometrics to the seismic catalog of The Geysers geothermal field (California), the world’s largest geothermal field. The choice of the study area is essentially guided by the completeness of the seismic catalog at smaller magnitudes (a drawback of conventional catalogs of natural seismicity). Contrary to previous studies, where the long-memory property was examined by using non-parametric approaches (e.g., rescaled range analysis), we assume a fractional integration model for which the degree of memory is defined by a real parameter d, which is related to the best known Hurst exponent. In particular, long-memory behavior is observed for d > 0. We estimate and test the value of d (i.e., the hypothesis of long memory) by applying parametric, semi-parametric, and non-parametric approaches to time series describing the daily number of earthquakes and the logarithm of the (total) seismic moment released per day. Attention is also paid to examining the sensitivity of the results to the uncertainty in the completeness magnitude of the catalog, and to investigating to what extent temporal fluctuations in seismic activity induced by injection operations affect the value of d. Temporal variations in the values of d are analyzed together with those of the b-value of the Gutenberg and Richter law. Our results indicate strong evidence of long memory, with d mostly constrained between 0 and 0.5. We observe that the value of d tends to decrease with increasing the magnitude completeness threshold, and therefore appears to be influenced by the number of information in the chain of intervening related events. Moreover, we find a moderate but significant negative correlation between d and the b-value. A negative, albeit weaker correlation is found between d and the fluid injection, as well as between d and the annual number of earthquakes.

Inhomogeneity of Macroseismic Intensities in Italy and Consequences for Macroseismic Magnitude Estimation

We show that macroseismic intensities assessed in Italy in the last decade are not homogeneous with those of the previous periods. This is partly related to the recent adoption of the European Macroseismic Scale (EMS) in place of the Mercalli–Cancani–Sieberg (MCS) scale used up to about one decade ago. The underestimation of EMS with respect to MCS is about a half of a degree on average and, even more significant, if the MCS intensities are estimated according to the approach developed for the quick evaluations of damage by macroseismic seismologists of the Italian Department of Civil Protection. We also show the inhomogeneity over time of the average differences between instrumental and macroseismic magnitudes computed from intensity data, indicating an average overestimation of magnitudes of about 0.3 units for the instrumental ones before year 1960 and of about 0.2 units for the macroseismic ones after such date. This is consistent with previous studies that hypothesized the incorrect calibration of mechanical recording seismometers operating in Italy and in the surrounding countries before the introduction of the standard electromagnetic seismometers from the beginning of 1960s. For such reasons, the magnitudes of preinstrumental earthquakes in the Catalogo Parametrico dei Terremoti Italiani seismic catalog, used for the most recent seismic hazard assessment in Italy, might be overestimated, on average, by about 0.1–0.2 magnitude units.

Automatic swarm analyzer based on matched filtering algorithms: El Hierro 2011 and Torreperogil 2012-2013

<p>Dense seismic swarms usually show a high number of earthquakes per hour, the events may overlap and in most of the cases seismic records are characterized by a low signal-to-noise ratio. As a result, the manual characterization performed by seismic and volcanic observatories can become very complicated or impossible to perform. In order to solve this problem, we have developed a set of algorithms whose purpose is to detect the events, pick their phases and give a location (in an absolute and relative way) of the earthquakes associated with a known swarm. </p><p> </p><p>These algorithms have been tested in two different tectonic environments: the volcano-tectonic pre-eruptive swarm of El Hierro, Spain (2011) and the tectonic seismic series of Torreperogil, Spain (2012-2013).  Both crises mainly differ in the distances from the seismic stations to the hypocentres of the swarms: in the case of El Hierro,  data corresponds to local epicentral distances (5-20Km) while the case of Torreperogil seismic series deals with regional distances (10-180km). Otherwise, both series present a similar evolution of the seismic network: as the number of earthquakes increased, more stations were deployed and the network became denser. </p><p> </p><p>To analyze these series, we have used two sets of well relocated earthquakes of both swarms as masters, considering manually analyzed events by National Geographic Institute (IGN) with magnitude mbLg greater than 1.5. After the application of the new algorithms, we have increased the number of earthquakes of  the IGN seismic catalog by a factor of 4.5 for Torreperogil and 2.9 for El Hierro. Similarly, the number of picked phases for these two series has been increased by a factor of 4.5 and 3.5, respectively.</p>

Power-law patterns in sequences of statistically related events preceding to the main event

Используя статистическую модель связанных событий и данные сейсмического каталога КФ ФИЦ ГС РАН за период 01.01.1962-31.12.2002 (n = 79283 события) для зоны субдукции Курило-Камчатской островной дуги (50°-60° с.ш., 156°-166° в.д., классы 4.1-16.1, глубины 0-600 км) построены последовательности событий, предшествующих главному событию заданной магнитуды и связанных с ним в пространственно-временной области. Проведён статистический анализ наличия степенных закономерностей в этих последовательностях на основании релаксационной модели деформационной активности. Степенные закономерности были выделены только в последовательностях связанных событий, предшествующих главному событию с энергетическим классом меньше 12 (показатель степени 0.5-0.7). Это объясняется большим объёмом выборки для главных событий такого класса и небольшой пространственно-временной областью их подготовки, что уменьшает вероятность попадания афтершоков от более крупных событий, предшествующих главному удару, в рассматриваемые последовательности. Using a statistical model of related events and data from the seismic catalog of the FRC GS RAS for the period 01.01.1962-31.12.2002 (n = 79283 events) for the subduction zone of the Kuril-Кamchatka island arc (50°-60° N, 156°-166° E, classes 4.1-16.1, depths 0-600 km) the sequences of events preceding the main event of a given magnitude and associated with it in the spatio-temporal region are constructed. A statistical analysis of the power laws presence in these sequences was carried out on the basis of the relaxation model of deformation activity. It was possible to obtain power-law patterns in sequences of related events for main events thet energy class is less than 12. The exponent takes the values of 0.5-0.7. The possibility of detecting of power-law patterns for the main events of such an energy class is explained by a large sample size for them and by a by a small spatio-temporal region of event preparation that reduces the probability to got the aftershocks from events with larger energy preceding the one under consideration into the sequence of related events.

Gutenberg-Richter b value studies along the Mexican Subduction Zone and data constraints

The Gutenberg-Richter b value is one of the most important tools for seismic hazard studies; this value is most useful in estimating seismicity rates, and also is related to ambient stress levels and shows changes precursory to the occurrence of large earthquakes. However, correct and reliable determinations of the b value are critically dependent on having adequate data samples. Studies oriented to corroborate whether precursory changes in the b value occur before large (M ? 7.0) along the Mexican subduction zone, were done based on data from the Servicio Sismológico Nacional (SSN, Mexico’s National Seismological Service) seismic catalog, from 1988 to 2018. Results for five earthquakes are suggestive that precursory changes may occur, but differences between measured values are not significant because of large uncertainties due to the SSN using different magnitude scales for small (below M ~4.5) and medium to large (above M ~4.5) magnitudes. We submit that until an appropriate scale is implemented for small magnitudes, results from b-value studies based on SSN data should be considered critically.

The Homogenized Instrumental Seismic Catalog (HORUS) of Italy from 1960 to Present

We implemented an automatic procedure to update in near-real time (daily to hourly) a homogeneous catalog of Italian instrumental seismicity to be used for forecasting experiments and other statistical analyses. The magnitudes of all events are homogeneously revalued to be consistent with Mw standard estimates made by the Global Centroid Moment Tensor project. For the time interval from 1960 to 15 April 2005, catalogs and online resources available for the Italian area were merged and all magnitudes were homogenized to Mw according to empirical relationships computed using the chi-square regression method, which properly consider the uncertainties of both variables. From 16 April 2005 to the present, an automatic procedure periodically downloads the data of the online bulletin of the Istituto Nazionale di Geofisica e Vulcanologia and of online moment tensor catalogs from respective websites, merges the different sources, and applies traditional magnitude conversions to Mw. The final catalog is provided on a website for public dissemination.