scholarly journals Rotational Ground Motion Measurements for Regional Seismic Moment Tensors: a Review

2021 ◽  
Author(s):  
Stefanie Donner

Seismic moment tensors are an important tool in geosciences on all spatial scales and for a broad range of applications. The basic underlying theory is established since decades. However, various factors influence the reliability of the inversion result, several of them are mutually dependent. Hence, a reliable retrieval of seismic moment tensors is still hampered in many cases, especially at regional event-receiver distances.To sample the entire wavefield due to a seismic source we need six components: three translational and three rotational ones. Up to now, only translational ground motion recordings were used for moment tensor retrieval, missing out valuable information. Using rotational in addition to the classical translational ground motions during waveform inversion for moment tensors mainly adds information on the vertical displacement gradient to the inversion problem. Furthermore, having available six instead of only three components per receiver location provides additional constraints on the sampling of the radiation pattern. As a result, the moment tensor components are resolved with higher precision and accuracy, even when the number of recording receivers is considerably reduced. Especially, components with a dependence to depth as well as the centroid depth can benefit significantly from additional rotational ground motion. Up to the time of writing this review only a few studies are published on the topic. Here, I summarise their findings and provide an overview over the possible capabilities of including rotational ground motion measurements to waveform inversion for seismic moment tensor retrieval.

2020 ◽  
Vol 223 (1) ◽  
pp. 161-179
Author(s):  
S Donner ◽  
M Mustać ◽  
B Hejrani ◽  
H Tkalčić ◽  
H Igel

SUMMARY Seismic moment tensors are an important tool and input variable for many studies in the geosciences. The theory behind the determination of moment tensors is well established. They are routinely and (semi-) automatically calculated on a global scale. However, on regional and local scales, there are still several difficulties hampering the reliable retrieval of the full seismic moment tensor. In an earlier study, we showed that the waveform inversion for seismic moment tensors can benefit significantly when incorporating rotational ground motion in addition to the commonly used translational ground motion. In this study, we test, what is the best processing strategy with respect to the resolvability of the seismic moment tensor components: inverting three-component data with Green’s functions (GFs) based on a 3-D structural model, six-component data with GFs based on a 1-D model, or unleashing the full force of six-component data and GFs based on a 3-D model? As a reference case, we use the inversion based on three-component data and 1-D structure, which has been the most common practice in waveform inversion for moment tensors so far. Building on the same Bayesian approach as in our previous study, we invert synthetic waveforms for two test cases from the Korean Peninsula: one is the 2013 nuclear test of the Democratic People’s Republic of Korea and the other is an Mw  5.4 tectonic event of 2016 in the Republic of Korea using waveform data recorded on stations in Korea, China and Japan. For the Korean Peninsula, a very detailed 3-D velocity model is available. We show that for the tectonic event both, the 3-D structural model and the rotational ground motion, contribute strongly to the improved resolution of the seismic moment tensor. The higher the frequencies used for inversion, the higher is the influence of rotational ground motions. This is an important effect to consider when inverting waveforms from smaller magnitude events. The explosive source benefits more from the 3-D structural model than from the rotational ground motion. Nevertheless, the rotational ground motion can help to better constraint the isotropic part of the source in the higher frequency range.


2021 ◽  
Author(s):  
◽  
Elizabeth de Joux Robertson

<p>The aim of this project is to enable accurate earthquake magnitudes (moment magnitude, MW) to be calculated routinely and in near real-time for New Zealand earthquakes. This would be done by inversion of waveform data to obtain seismic moment tensors. Seismic moment tensors also provide information on fault-type. I use a well-established seismic moment tensor inversion method, the Time-Domain [seismic] Moment Tensor Inversion algorithm (TDMT_INVC) and apply it to GeoNet broadband waveform data to generate moment tensor solutions for New Zealand earthquakes. Some modifications to this software were made. A velocity model can now be automatically used to calculate Green's functions without having a pseudolayer boundary at the source depth. Green's functions can be calculated for multiple depths in a single step, and data are detrended and a suitable data window is selected. The seismic moment tensor solution that has either the maximum variance reduction or the maximum double-couple component is automatically selected for each depth. Seismic moment tensors were calculated for 24 New Zealand earthquakes from 2000 to 2005. The Global CMT project has calculated CMT solutions for 22 of these, and the Global CMT project solutions are compared to the solutions obtained in this project to test the accuracy of the solutions obtained using the TDMT_INVC code. The moment magnitude values are close to the Global CMT values for all earthquakes. The focal mechanisms could only be determined for a few of the earthquakes studied. The value of the moment magnitude appears to be less sensitive to the velocity model and earthquake location (epicentre and depth) than the focal mechanism. Distinguishing legitimate seismic signal from background seismic noise is likely to be the biggest problem in routine inversions.</p>


2020 ◽  
Vol 221 (1) ◽  
pp. 77-88
Author(s):  
Sean R Ford ◽  
Gordon D Kraft ◽  
Gene A Ichinose

SUMMARY Event screening is an explosion monitoring practice that aims to identify an event as an explosion (‘screened in’) or not (‘screened out’). Confidence in event screening can be increased if multiple independent approaches are used. We describe a new approach to event screening using the seismic moment tensor and its representation on the hypersphere, specifically the 5-sphere of 6-degree unit vectors representing the normalized symmetric moment tensor. The sample of moment tensors from an explosion data set is unimodal on the 5-sphere and can be parametrized by the Langevin distribution, which is sometimes referred to as the Normal distribution on the hypersphere. Screening is then accomplished by finding the angle from the explosion population mean to any newly measured moment tensor and testing if that angle is in the tail of the Langevin distribution (conservatively quantified as greater than 99.9 per cent of the cumulative density). We apply the screen to a sample of earthquakes from the Western USA and the September 2017 explosion and subsequent collapse at the Pungyye-Ri Test Site in North Korea. All the earthquakes and the collapse screen out, but the explosion does not.


2021 ◽  
Author(s):  
Savvaidis Alexandros ◽  
Roselli Pamela

&lt;p&gt;In the scope to investigate the possible interactions between injected fluids, subsurface geology, stress field and triggering earthquakes, we investigate seismic source parameters related to the seismicity in West Texas (USA). The analysis of seismic moment tensor is an excellent tool to understand earthquake source process kinematics; moreover, changes in the fluid volume during faulting leads to existence of non-double-couple (NDC) components (Frohlich, 1994; Julian et al., 1998; Miller et al., 1998). The NDC percentage in the source constitutes the sum of absolute ISO and CLVD components so that %NDC= % ISO + %CLVD and %ISO+%CLVD+%DC=100%. It is currently known that the presence of NDC implies more complex sources (mixed shear-tensile earthquakes) correlated to fluid injections, geothermal systems and volcano-seismology where induced and triggered seismicity is observed.&lt;/p&gt;&lt;p&gt;With this hypothesis, we analyze the micro-earthquakes (M &lt;2 .7) recorded by the Texas Seismological Network (TexNet) and a temporary network constituted by 40 seismic stations (equipped by either broadband or 3 component geophones). Our study area is characterized by Northwest-Southeast faults that follow the local stress/field (SH&lt;sub&gt;max&lt;/sub&gt;) and the geological characteristic of the shallow basin structure of the study area. After a selection based on signal-to-noise ratio, we filter (1-50 Hz) the seismograms and estimate P-wave pulse polarities and the first P-wave ground displacement pulse in time domain. Then, we perform the full moment tensor analysis by using hybridMT technique (Andersen, 2001; Kwiatek et al., 2016) with a detailed 1D velocity model. The key parameter is the polarity/area of the first P-wave ground displacement pulse in time domain. Uncertainties of estimated moment tensors are expressed by normalized root-mean-square (RMS errors) between theoretical and estimated amplitudes (Vavricuk et al., 2014). We also evaluate the quality of the seismic moment tensors by bootstrap and resampling. In our preliminary results we obtain NDC percentage (in terms of %ISO and %CLVD components), Mw, seismic moment, P, T and B axes orientation for each source inverted.&lt;/p&gt;


1999 ◽  
Vol 89 (5) ◽  
pp. 1390-1394 ◽  
Author(s):  
David Bowers ◽  
John A. Hudson

Abstract We compare several published definitions of the scalar moment M0, a measure of the size of a seismic disturbance derived from the second-order seismic moment tensor M (with eigenvalues m1 ≥ m3 ≥ m2). While arbitrary, a useful definition is in terms of a total moment, MT0 = MI + MD, where MI = |M|, with M = (m1 + m2 + m3)/3, is the isotropic moment, and MD = max(|mj − M|; j = 1, 2, 3), is the deviatoric moment. This definition is consistent with other definitions of M0 if M is a double couple. This definition also gives physically appealing and simple results for the explosion and crack sources. Furthermore, our definitions of MT0, MI and MD are in accord with the parameterization of the moment tensor into a deviatoric part (represented by T which lies in [−1,1]) and a volumetric part (represented by k which lies in [−1, 1]) proposed by Hudson et al. (1989).


2021 ◽  
Author(s):  
◽  
Elizabeth de Joux Robertson

<p>The aim of this project is to enable accurate earthquake magnitudes (moment magnitude, MW) to be calculated routinely and in near real-time for New Zealand earthquakes. This would be done by inversion of waveform data to obtain seismic moment tensors. Seismic moment tensors also provide information on fault-type. I use a well-established seismic moment tensor inversion method, the Time-Domain [seismic] Moment Tensor Inversion algorithm (TDMT_INVC) and apply it to GeoNet broadband waveform data to generate moment tensor solutions for New Zealand earthquakes. Some modifications to this software were made. A velocity model can now be automatically used to calculate Green's functions without having a pseudolayer boundary at the source depth. Green's functions can be calculated for multiple depths in a single step, and data are detrended and a suitable data window is selected. The seismic moment tensor solution that has either the maximum variance reduction or the maximum double-couple component is automatically selected for each depth. Seismic moment tensors were calculated for 24 New Zealand earthquakes from 2000 to 2005. The Global CMT project has calculated CMT solutions for 22 of these, and the Global CMT project solutions are compared to the solutions obtained in this project to test the accuracy of the solutions obtained using the TDMT_INVC code. The moment magnitude values are close to the Global CMT values for all earthquakes. The focal mechanisms could only be determined for a few of the earthquakes studied. The value of the moment magnitude appears to be less sensitive to the velocity model and earthquake location (epicentre and depth) than the focal mechanism. Distinguishing legitimate seismic signal from background seismic noise is likely to be the biggest problem in routine inversions.</p>


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