Background Seismicity before and after the 1976 Ms 7.8 Tangshan Earthquake: Is Its Aftershock Sequence Still Continuing?

2020 ◽  
Author(s):  
Yue Liu ◽  
Jiancang Zhuang ◽  
Changsheng Jiang
Keyword(s):  
Aftershock Sequence ◽  
Tangshan Earthquake ◽  
Aftershock Activity ◽  
Background Rate ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences ◽  
Background Seismicity ◽  
Before And After ◽  
Large Earthquakes ◽  
Current Stage

Abstract The aftershock zone of the 1976 Ms 7.8 Tangshan, China, earthquake remains seismically active, experiencing moderate events such as the 5 December 2019 Ms 4.5 Fengnan event. It is still debated whether aftershock sequences following large earthquakes in low-seismicity continental regions can persist for several centuries. To understand the current stage of the Tangshan aftershock sequence, we analyze the sequence record and separate background seismicity from the triggering effect using a finite-source epidemic-type aftershock sequence model. Our results show that the background rate notably decreases after the mainshock. The estimated probability that the most recent 5 December 2019 Ms 4.5 Fengnan District, Tangshan, earthquake is a background event is 50.6%. This indicates that the contemporary seismicity in the Tangshan aftershock zone can be characterized as a transition from aftershock activity to background seismicity. Although the aftershock sequence is still active in the Tangshan region, it is overridden by background seismicity.

scholarly journals Characteristics of seismic activity before and after the 2018 M6.7 Hokkaido Eastern Iburi earthquake

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Takao Kumazawa ◽  
Yosihiko Ogata ◽  
Hiroshi Tsuruoka
Keyword(s):  
Seismic Activity ◽  
Main Shock ◽  
Aftershock Sequence ◽  
Aftershock Activity ◽  
Background Rate ◽  
Etas Model ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences ◽  
Before And After ◽  
Largest Aftershock

AbstractWe applied the epidemic type aftershock sequence (ETAS) model, the two-stage ETAS model and the non-stationary ETAS model to investigate the detailed features of the series of earthquake occurrences before and after the M6.7 Hokkaido Eastern Iburi earthquake on 6 September 2018, based on earthquake data from October 1997. First, after the 2003 M8.0 Tokachi-Oki earthquake, seismic activity in the Eastern Iburi region reduced relative to the ETAS model. During this period, the depth ranges of the seismicity were migrating towards shallow depths, where a swarm cluster, including a M5.1 earthquake, finally occurred in the deepest part of the range. This swarm activity was well described by the non-stationary ETAS model until the M6.7 main shock. The aftershocks of the M6.7 earthquake obeyed the ETAS model until the M5.8 largest aftershock, except for a period of several days when small, swarm-like activity was found at the southern end of the aftershock region. However, when we focus on the medium and larger aftershocks, we observed quiescence relative to the ETAS model from 8.6 days after the main shock until the M5.8 largest aftershock. For micro-earthquakes, we further studied the separated aftershock sequences in the naturally divided aftershock volumes. We found that the temporal changes in the background rate and triggering coefficient (aftershock productivity) in respective sub-volumes were in contrast with each other. In particular, relative quiescence was seen in the northern deep zones that includes the M5.8 largest aftershock. Furthermore, changes in the b-values of the whole aftershock activity showed an increasing trend with respect to the logarithm of elapsed time during the entire aftershock period, which is ultimately explained by the spatially different characteristics of the aftershocks.

scholarly journals Combining a Locally Restricted Anisotropic Spatial Kernel with an ETAS Incomplete Model for Better Forecasts of the 2019 Ridgecrest Sequence

2021 ◽  
Author(s):  
Christian Grimm ◽  
Sebastian Hainzl ◽  
Martin Käser ◽  
Helmut Küchenhoff
Keyword(s):  
Aftershock Sequence ◽  
Large Area ◽  
Short Term ◽  
Aftershock Activity ◽  
Time Model ◽  
Strong Earthquakes ◽  
Etas Model ◽  
Incomplete Model ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences

Abstract Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model seismic clustering is the Epidemic Type Aftershock Sequence (ETAS) model, that shows three major biases: First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three effects can substantially bias the parameter estimation and particularly lead to underestimated cluster sizes. In this article, we combine the approach of Grimm (2021), which introduced a generalized anisotropic and locally restricted spatial kernel, with the ETAS-Incomplete (ETASI) time model of Hainzl (2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g.~allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and desaster response.

Operational Earthquake Forecasting during the 2019 Ridgecrest, California, Earthquake Sequence with the UCERF3-ETAS Model

2020 ◽  
Vol 91 (3) ◽  
pp. 1567-1578 ◽  
Author(s):  
Kevin R. Milner ◽  
Edward H. Field ◽  
William H. Savran ◽  
Morgan T. Page ◽  
Thomas H. Jordan
Keyword(s):  
High Performance ◽  
Aftershock Sequence ◽  
Lessons Learned ◽  
Ease Of Use ◽  
Earthquake Forecasting ◽  
Earthquake Rupture ◽  
Etas Model ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences ◽  
High Performance Computing Cluster

Abstract The first Uniform California Earthquake Rupture Forecast, Version 3–epidemic-type aftershock sequence (UCERF3-ETAS) aftershock simulations were running on a high-performance computing cluster within 33 min of the 4 July 2019 M 6.4 Searles Valley earthquake. UCERF3-ETAS, an extension of the third Uniform California Earthquake Rupture Forecast (UCERF3), is the first comprehensive, fault-based, epidemic-type aftershock sequence (ETAS) model. It produces ensembles of synthetic aftershock sequences both on and off explicitly modeled UCERF3 faults to answer a key question repeatedly asked during the Ridgecrest sequence: What are the chances that the earthquake that just occurred will turn out to be the foreshock of an even bigger event? As the sequence unfolded—including one such larger event, the 5 July 2019 M 7.1 Ridgecrest earthquake almost 34 hr later—we updated the model with observed aftershocks, finite-rupture estimates, sequence-specific parameters, and alternative UCERF3-ETAS variants. Although configuring and running UCERF3-ETAS at the time of the earthquake was not fully automated, considerable effort had been focused in 2018 on improving model documentation and ease of use with a public GitHub repository, command line tools, and flexible configuration files. These efforts allowed us to quickly respond and efficiently configure new simulations as the sequence evolved. Here, we discuss lessons learned during the Ridgecrest sequence, including sensitivities of fault triggering probabilities to poorly constrained finite-rupture estimates and model assumptions, as well as implications for UCERF3-ETAS operationalization.

Integration of geological and seismological data in earthquakes occurrence models for Italy: towards a unified model for different forecast perspectives

2019 ◽  
Vol 219 (3) ◽  
pp. 2148-2164
Author(s):  
A M Lombardi
Keyword(s):  
Aftershock Sequence ◽  
Earthquake Forecasting ◽  
Short Term ◽  
Background Rate ◽  
Etas Model ◽  
Term Forecast ◽  
Earthquake Predictability ◽  
Background Seismicity ◽  
Different Types

SUMMARY The operational earthquake forecasting (OEF) is a procedure aimed at informing communities on how seismic hazard changes with time. This can help them live with seismicity and mitigate risk of destructive earthquakes. A successful short-term prediction scheme is not yet produced, but the search for it should not be abandoned. This requires more research on seismogenetic processes and, specifically, inclusion of any information about earthquakes in models, to improve forecast of future events, at any spatio-temporal-magnitude scale. The short- and long-term forecast perspectives of earthquake occurrence followed, up to now, separate paths, involving different data and peculiar models. But actually they are not so different and have common features, being parts of the same physical process. Research on earthquake predictability can help to search for a common path in different forecast perspectives. This study aims to improve the modelling of long-term features of seismicity inside the epidemic type aftershock sequence (ETAS) model, largely used for short-term forecast and OEF procedures. Specifically, a more comprehensive estimation of background seismicity rate inside the ETAS model is attempted, by merging different types of data (seismological instrumental, historical, geological), such that information on faults and on long-term seismicity integrates instrumental data, on which the ETAS models are generally set up. The main finding is that long-term historical seismicity and geological fault data improve the pseudo-prospective forecasts of independent seismicity. The study is divided in three parts. The first consists in models formulation and parameter estimation on recent seismicity of Italy. Specifically, two versions of ETAS model are compared: a ‘standard’, previously published, formulation, only based on instrumental seismicity, and a new version, integrating different types of data for background seismicity estimation. Secondly, a pseudo-prospective test is performed on independent seismicity, both to test the reliability of formulated models and to compare them, in order to identify the best version. Finally, a prospective forecast is made, to point out differences and similarities in predicting future seismicity between two models. This study must be considered in the context of its limitations; anyway, it proves, beyond argument, the usefulness of a more sophisticated estimation of background rate, inside short-term modelling of earthquakes.

Point process modelling of reservoir-induced seismicity

2001 ◽  
Vol 38 (A) ◽  
pp. 232-242 ◽  
Author(s):  
Masajiro Imoto
Keyword(s):  
Point Process ◽  
Induced Seismicity ◽  
Earthquake Hazard ◽  
Information Criterion ◽  
Aftershock Sequence ◽  
Water Levels ◽  
Tectonic Activity ◽  
Reservoir Induced Seismicity ◽  
Epidemic Type Aftershock Sequence ◽  
Background Seismicity

A point process procedure can be used to study reservoir-induced seismicity (RIS), in which the intensity function representing earthquake hazard is a combination of three terms: a constant background term, an ETAS (epidemic-type aftershock sequence) term for aftershocks, and a time function derived from observation of water levels of a reservoir. This paper presents the results of such a study of the seismicity in the vicinity of the Tarbela reservoir in Pakistan. Making allowance for changes in detection capability and the background seismicity related to tectonic activity, earthquakes of magnitude ≥ 2.0, occurring between May 1978 and January 1982 and whose epicentres were within 100 km of the reservoir, were used in this analysis. Several different intensities were compared via their Akaike information criterion (AIC) values relative to those of a Poisson process. The results demonstrate that the seismicity within 20 km of the reservoir correlates with water levels of the reservoir, namely, active periods occur about 250 days after the appearance of low water levels. This suggests that unloading the reservoir activates the seismicity beneath it. Seasonal variations of the seismicity in an area up to 100 km from the reservoir were also found, but these could not be adequately interpreted by an appropriate RIS mechanism.

scholarly journals Strong foreshock signal preceding the L'Aquila (Italy) earthquake (<i>M</i><sub>w</sub> 6.3) of 6 April 2009

2010 ◽  
Vol 10 (1) ◽  
pp. 19-24 ◽  
Author(s):  
G. A. Papadopoulos ◽  
M. Charalampakis ◽  
A. Fokaefs ◽  
G. Minadakis
Keyword(s):  
Hanging Wall ◽  
B Value ◽  
Aftershock Sequence ◽  
Earthquake Catalogue ◽  
Seismicity Rate ◽  
Background Seismicity ◽  
Before And After ◽  
Spatially Distributed ◽  
Drastic Increase ◽  
Seismogenic Area

Abstract. We used the earthquake catalogue of INGV extending from 1 January 2006 to 30 June 2009 to detect significant changes before and after the 6 April 2009 L'Aquila mainshock (Mw=6.3) in the seismicity rate, r (events/day), and in b-value. The statistical z-test and Utsu-test were applied to identify significant changes. From the beginning of 2006 up to the end of October 2008 the activity was relatively stable and remained in the state of background seismicity (r=1.14, b=1.09). From 28 October 2008 up to 26 March 2009, r increased significantly to 2.52 indicating weak foreshock sequence; the b-value did not changed significantly. The weak foreshock sequence was spatially distributed within the entire seismogenic area. In the last 10 days before the mainshock, strong foreshock signal became evident in space (dense epicenter concentration in the hanging-wall of the Paganica fault), in time (drastic increase of r to 21.70 events/day) and in size (b-value dropped significantly to 0.68). The significantly high seismicity rate and the low b-value in the entire foreshock sequence make a substantial difference from the background seismicity. Also, the b-value of the strong foreshock stage (last 10 days before mainshock) was significantly lower than that in the aftershock sequence. Our results indicate the important value of the foreshock sequences for the prediction of the mainshock.

How Do Statistical Parameters of Induced Seismicity Correlate with Fluid Injection? Case of Oklahoma

2021 ◽  
Author(s):  
Hideo Aochi ◽  
Julie Maury ◽  
Thomas Le Guenan
Keyword(s):  
Induced Seismicity ◽  
Aftershock Sequence ◽  
Statistical Parameters ◽  
Exponential Equation ◽  
Seismicity Rate ◽  
Epidemic Type Aftershock Sequence ◽  
Background Seismicity ◽  
Mechanical Interpretation ◽  
Independent Variable ◽  
Grid Points

Abstract The seismicity evolution in Oklahoma between 2010 and 2018 is analyzed systematically using an epidemic-type aftershock sequence model. To retrieve the nonstationary seismicity component, we systematically use a moving window of 200 events, each within a radius of 20 km at grid points spaced every 0.2°. Fifty-three areas in total are selected for our analysis. The evolution of the background seismicity rate μ is successfully retrieved toward its peak at the end of 2014 and during 2015, whereas the triggering parameter K is stable, slightly decreasing when the seismicity is activated. Consequently, the ratio of μ to the observed seismicity rate is not stationary. The acceleration of μ can be fit with an exponential equation relating μ to the normalized injected volume. After the peak, the attenuation phase can be fit with an exponential equation with time since peak as the independent variable. As a result, the evolution of induced seismicity can be followed statistically after it begins. The turning points, such as activation of the seismicity and timing of the peak, are difficult to identify solely from this statistical analysis and require a subsequent mechanical interpretation.

Comparison of the seismicity evolution during the 2000 and 2003 stimulations at Soultz-sous-Forêts.

2021 ◽  
Author(s):  
Julie Maury ◽  
Hideo Aochi
Keyword(s):  
Stress Transfer ◽  
Aftershock Sequence ◽  
Operational Parameters ◽  
Hydraulic Stimulation ◽  
Background Rate ◽  
Seismicity Rate ◽  
Wellhead Pressure ◽  
Existing Structures ◽  
Background Seismicity ◽  
Two Peaks

&lt;p&gt;The research site of Soultz-sous-For&amp;#234;ts (Alsace, France) was a pioneer pilot geothermal site in Europe. In this study, we use the available data from 2000 and 2003 hydraulic stimulation tests to analyze the seismicity evolution. We apply the ETAS (Epidemic-Type Aftershock Sequence) model to extract the background seismicity rate during the two stimulation periods.&lt;/p&gt;&lt;p&gt;For the 2003 sequence, to retrieve the nonstationary seismicity component, we use a moving window of 400 events for the whole catalog. The evolution of the background seismicity rate &amp;#956; is successfully retrieved with an evolution in two peaks coherent with the wellhead pressure evolution, while the triggering parameter &amp;#922; is stable. At the end of the stimulation &amp;#956; decrease significantly. Then we look at the evolution of ETAS parameter by selecting five clusters of seismicity. The evolution of &amp;#956; for each cluster is in agreement with a propagation of the pressure away from the well with the cluster closer to the well showing one early peak only, the middle clusters showing two peaks and the far cluster showing a later peak. All clusters show a decrease of &amp;#956; at the end of stimulation.&lt;/p&gt;&lt;p&gt;For the 2000 sequence, the background seismicity rate is less well constrained but it stays globally constant during the stimulation with some decrease after its end. We see no clear peak in &amp;#956; as was present during 2003 and K is relatively low. However, &amp;#956; also decreases at the end of the stimulation. The selection of clusters does not change this global behavior and all clusters present grossly the same characteristics.&lt;/p&gt;&lt;p&gt;Our results are in agreement with the different characteristics observed by several authors (e.g. Calo and Dorbath, 2013; Dorbath et al, 2009) between these two stimulations. On one hand, the 2003 stimulation consists in an activation of several existing structures that yields a seismicity well explained by the ETAS model with a combined effect of Coulomb stress transfer and perturbation induced by the stimulation (e.g. pore pressure variation).&amp;#160; The evolution in space is also coherent with the finding of Calo and Dorbath (2013) that the injected water goes far from the well avoiding increase in effective stress near the well. In this case, background seismicity rate can be related to the measured pressure. On the other hand, the 2000 stimulation developed a 3D reservoir with the creation of a fresh shear zone (Cornet et al, 2015) and so the direct effects of the stimulation are dominants. However, no clear relation between the background seismicity rate and the operational parameters can be observed. At the end of stimulation, we observe a decrease of background rate corresponding to a progressive return to a natural background rate, similar to what is observed in other settings (Oklahoma, Rousse).&lt;/p&gt;

scholarly journals The Relevance of Foreshocks in Earthquake Triggering: A Statistical Study

2018 ◽  
Author(s):  
Eugenio Lippiello ◽  
Cataldo Godano ◽  
Lucilla De Arcangelis
Keyword(s):  
Statistical Study ◽  
Aftershock Sequence ◽  
Statistical Features ◽  
Earthquake Triggering ◽  
Etas Model ◽  
Epidemic Type Aftershock Sequence ◽  
The One ◽  
Triggering Process ◽  
Large Earthquakes ◽  
Good Agreement

An increase of seismic activity is often observed before large earthquakes. Events responsible for this increase are usually named foreshock and their occurrence probably represents the most reliable precursory pattern. Many foreshocks statistical features can be interpreted in terms of the standard mainshock-to-aftershock triggering process and are recovered in the Epidemic Type Aftershock Sequence ETAS model. Here we present a statistical study of instrumental seismic catalogs from four different geographic regions. We focus on some common features of foreshocks in the four catalogs which cannot be reproduced by the ETAS model. In particular we find in instrumental catalogs a significantly larger number of foreshocks than the one predicted by the ETAS model. We show that this foreshock excess cannot be attributed to catalog incompleteness. We therefore propose a generalized formulation of the ETAS model, the ETAFS model, which explicitly includes foreshock occurrence. Statistical features of aftershocks and foreshocks in the ETAFS model are in very good agreement with instrumental results.

Sign in / Sign up

Export Citation Format

Share Document