Determination of the time-dependent moment tensor using time-reverse imaging

Geophysics ◽  
2020 ◽  
pp. 1-61
Author(s):  
Claudia Finger ◽  
Erik Saenger

An approach is presented to determine the time-dependent moment tensor and the origin time in addition to commonly derived locations of seismic events using time-reverse imaging (TRI). It is crucial to locate and characterize the occurring micro-seismicity without making a priori assumptions about the sources to fully understand the subsurface processes inducing seismicity. Low signal-to-noise ratios often force standard methods to make assumptions about sources or only characterize selected larger-magnitude events. In TRI, micro-earthquakes are located by back propagating the full recorded time-reversed wavefield through a velocity model until it ideally convergences on the source location. Therefore, it is less affected by low signal-to-noise ratios and potentially locates and characterizes most of the events. After distinguishing artificial convergence locations from source locations, the quality of the source location and the moment tensors are derived by recording the stress at the determined source locations during the back propagation of the time-reversed wavefield. A robust workflow is derived using synthetic test cases in a realistic scenario with velocity models that only approximate the true velocity model and/or noisy displacement traces. The influence of a rudimentary velocity model on the source-location accuracy and characterisation is significant. The proposed workflow handles these less-than optimal station distributions and velocity models. Finally, the derived workflow is successfully applied to field data recorded at the geothermal field of Los Humeros, Mexico. Although only a one-dimensional velocity model is currently available, source locations and (time-dependent) moment tensors could be determined for selected events.

2021 ◽  
Author(s):  
Claudia Finger ◽  
Erik H. Saenger

<p>In addition to stable and accurate hypocenters of seismic events, the characterisation of events is crucial for the investigation of seismicity in the context of geothermal reservoirs, CO2-sequestration and other geotechnical applications. Since the origin and nature of the seismicity in such cases is still under investigation, tools should rely on as few a priori assumptions about the sources as possible. Here, an approach is presented to determine the time-dependent moment tensor and origin time in addition to commonly derived hypocenter locations of seismic events using time-reverse imaging (TRI). The full six component moment tensor is derived and may be used to display for example focal mechanisms. The workflow consists of determining the location of potential sources, discriminating artificial and true source locations and obtaining the time-dependent moment tensors by recording the stress components at the derived source locations. Since TRI does not rely on the identification of seismic phases but on the simulation of the time-reversed wavefield through an adequate velocity model, no assumptions about the source location or the type of source mechanism is made. TRI is less affected by low signal-to-noise ratios and is thus promising for noisier sites and quasi-simultaneous events. However, a sufficient number of seismic stations are needed to accurately sample the wavefield spatially. The proposed workflow is demonstrated by locating and characterising microseismic events in the geothermal field of Los Humeros, Mexico. Although higher levels of noise are present and only a one-dimensional velocity model is available at this time, selected events could be located and characterised.</p>


2019 ◽  
Vol 220 (1) ◽  
pp. 218-234 ◽  
Author(s):  
Xin Wang ◽  
Zhongwen Zhan

SUMMARY Earthquake focal mechanisms put primary control on the distribution of ground motion, and also bear on the stress state of the crust. Most routine focal mechanism catalogues still use 1-D velocity models in inversions, which may introduce large uncertainties in regions with strong lateral velocity heterogeneities. In this study, we develop an automated waveform-based inversion approach to determine the moment tensors of small-to-medium-sized earthquakes using 3-D velocity models. We apply our approach in the Los Angeles region to produce a new moment tensor catalogue with a completeness of ML ≥ 3.5. The inversions using the Southern California Earthquake Center Community Velocity Model (3D CVM-S4.26) significantly reduces the moment tensor uncertainties, mainly owing to the accuracy of the 3-D velocity model in predicting both the phases and the amplitudes of the observed seismograms. By comparing the full moment tensor solutions obtained using 1-D and 3-D velocity models, we show that the percentages of non-double-couple components decrease dramatically with the usage of 3-D velocity model, suggesting that large fractions of non-double-couple components from 1-D inversions are artifacts caused by unmodelled 3-D velocity structures. The new catalogue also features more accurate focal depths and moment magnitudes. Our highly accurate, efficient and automatic inversion approach can be expanded in other regions, and can be easily implemented in near real-time system.


2020 ◽  
Vol 110 (5) ◽  
pp. 2095-2111 ◽  
Author(s):  
Daniela Kühn ◽  
Sebastian Heimann ◽  
Marius P. Isken ◽  
Elmer Ruigrok ◽  
Bernard Dost

ABSTRACT Since 1991, induced earthquakes have been observed and linked to gas production in the Groningen field. Recorded waveforms are complex, resulting partly from a Zechstein salt layer overlying the reservoir and partly from free-surface reverberations, internal multiples, interface conversions, guided waves, and waves diving below the reservoir. Therefore, picking of polarities or amplitudes for use in moment tensor inversion is problematic, whereas phase identification may be circumvented employing full waveform techniques. Although moment tensors have become a basic tool to analyze earthquake sources, their uncertainties are rarely reported. We introduce a method for probabilistic moment tensor estimation and demonstrate its use on the basis of a single event within the Groningen field, concentrating on detailed tests of input data and inversion parameters to derive rules of good practice for moment tensor estimation of events recorded in the Groningen field. In addition to the moment tensor, event locations are provided. Hypocenters estimated simultaneously with moment tensors are often less sensitive to uncertainties in crustal structure, which is pertinent for the application to the Groningen field, because the task of relating earthquakes to specific faults hitherto suffers from a limited resolution of earthquake locations. Because of the probabilistic approach, parameter trade-offs, uncertainties, and ambiguities are mapped. In addition, the implemented bootstrap method implicitly accounts for modeling errors affecting every station and phase differently. A local 1D velocity model extracted from a full 3D velocity model yields more consistent results than other models applied previously. For all velocity models and combinations of input data tested, a shift in location of 1 km to the south is observed for the test event compared to the public catalog. A full moment tensor computed employing the local 1D velocity model features negative isotropic components and may be interpreted as normal fault and collapse at reservoir level.


2018 ◽  
Author(s):  
Claudia Werner ◽  
Erik H. Saenger

Abstract. Time Reverse Imaging (TRI) is evolving into a standard technique for localizing and characterizing seismic events. In recent years, TRI has been applied to a wide range of applications from the lab scale over the field scale up to the global scale. No identification of events and their onset times is necessary when localizing events with TRI. Therefore, it is especially suited for localizing quasi-simultaneous events and events with a low signal-to-noise ratio. However, in contrast to more regularly applied localization methods, the prerequisites for applying TRI are not sufficiently known. To investigate the significance of station distributions, complex velocity models and signal-to-noise ratios for the localization quality, numerous simulations were performed using a finite difference code to propagate elastic waves through three-dimensional models. Synthetic seismograms were reversed in time and re-inserted into the model. The time-reversed wavefield backpropagates through the model and, in theory, focuses at the source location. This focusing was visualized using imaging conditions. Additionally, artificial focusing spots were removed with an illumination map specific to the setup. Successful localizations were sorted into four categories depending on their reliability. Consequently, individual simulation setups could be evaluated by their ability to produce reliable localizations. Optimal inter-station distances, minimum apertures, relations between array and source location, heterogeneities of inter-station distances and total number of stations were investigated for different source depth as well as source types. Additionally, the quality of the localization was analysed when using a complex velocity model or a low signal-to-noise ratio. Finally, an array in Southern California was investigated for its ability to localize seismic events in specific target depths while using the actual velocity model for that region. In addition, the success rate with recorded data was estimated. Knowledge about the prerequisites for using TRI enables the estimation of success rates for a given problem. Furthermore, it reduces the time needed for adjusting stations to achieve more reliable localizations and provides a foundation for designing arrays for applying TRI.


1989 ◽  
Vol 79 (2) ◽  
pp. 493-499
Author(s):  
Stuart A. Sipkin

Abstract The teleseismic long-period waveforms recorded by the Global Digital Seismograph Network from the two largest Superstition Hills earthquakes are inverted using an algorithm based on optimal filter theory. These solutions differ slightly from those published in the Preliminary Determination of Epicenters Monthly Listing because a somewhat different, improved data set was used in the inversions and a time-dependent moment-tensor algorithm was used to investigate the complexity of the main shock. The foreshock (origin time 01:54:14.5, mb 5.7, Ms 6.2) had a scalar moment of 2.3 × 1025 dyne-cm, a depth of 8 km, and a mechanism of strike 217°, dip 79°, rake 4°. The main shock (origin time 13:15:56.4, mb 6.0, Ms 6.6) was a complex event, consisting of at least two subevents, with a combined scalar moment of 1.0 × 1026 dyne-cm, a depth of 10 km, and a mechanism of strike 303°, dip 89°, rake −180°.


2019 ◽  
Vol 217 (3) ◽  
pp. 1727-1741 ◽  
Author(s):  
D W Vasco ◽  
Seiji Nakagawa ◽  
Petr Petrov ◽  
Greg Newman

SUMMARY We introduce a new approach for locating earthquakes using arrival times derived from waveforms. The most costly computational step of the algorithm scales as the number of stations in the active seismographic network. In this approach, a variation on existing grid search methods, a series of full waveform simulations are conducted for all receiver locations, with sources positioned successively at each station. The traveltime field over the region of interest is calculated by applying a phase picking algorithm to the numerical wavefields produced from each simulation. An event is located by subtracting the stored traveltime field from the arrival time at each station. This provides a shifted and time-reversed traveltime field for each station. The shifted and time-reversed fields all approach the origin time of the event at the source location. The mean or median value at the source location thus approximates the event origin time. Measures of dispersion about this mean or median time at each grid point, such as the sample standard error and the average deviation, are minimized at the correct source position. Uncertainty in the event position is provided by the contours of standard error defined over the grid. An application of this technique to a synthetic data set indicates that the approach provides stable locations even when the traveltimes are contaminated by additive random noise containing a significant number of outliers and velocity model errors. It is found that the waveform-based method out-performs one based upon the eikonal equation for a velocity model with rapid spatial variations in properties due to layering. A comparison with conventional location algorithms in both a laboratory and field setting demonstrates that the technique performs at least as well as existing techniques.


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. KS59-KS69 ◽  
Author(s):  
Chao Song ◽  
Zedong Wu ◽  
Tariq Alkhalifah

Passive seismic monitoring has become an effective method to understand underground processes. Time-reversal-based methods are often used to locate passive seismic events directly. However, these kinds of methods are strongly dependent on the accuracy of the velocity model. Full-waveform inversion (FWI) has been used on passive seismic data to invert the velocity model and source image, simultaneously. However, waveform inversion of passive seismic data uses mainly the transmission energy, which results in poor illumination and low resolution. We developed a waveform inversion using multiscattered energy for passive seismic to extract more information from the data than conventional FWI. Using transmission wavepath information from single- and double-scattering, computed from a predicted scatterer field acting as secondary sources, our method provides better illumination of the velocity model than conventional FWI. Using a new objective function, we optimized the source image and velocity model, including multiscattered energy, simultaneously. Because we conducted our method in the frequency domain with a complex source function including spatial and wavelet information, we mitigate the uncertainties of the source wavelet and source origin time. Inversion results from the Marmousi model indicate that by taking advantage of multiscattered energy and starting from a reasonably acceptable frequency (a single source at 3 Hz and multiple sources at 5 Hz), our method yields better inverted velocity models and source images compared with conventional FWI.


2019 ◽  
Vol 91 (1) ◽  
pp. 114-125 ◽  
Author(s):  
Natalia A. Ruppert ◽  
Avinash Nayak ◽  
Clifford Thurber ◽  
Cole Richards

Abstract The 30 November 2018 magnitude 7.1 Anchorage earthquake occurred as a result of normal faulting within the lithosphere of subducted Yakutat slab. It was followed by a vigorous aftershock sequence with over 10,000 aftershocks reported through the end of July 2019. The Alaska Earthquake Center produced a reviewed aftershock catalog with a magnitude of completeness of 1.3. This well‐recorded dataset provides a rare opportunity to study the relationship between the aftershocks and fault rupture of a major intraslab event. We use tomoDD algorithm to relocate 2038 M≥2 aftershocks with a regional 3D velocity model. The relocated aftershocks extend over a 20 km long zone between 47 and 57 km depth and are primarily confined to a high VP/VS region. Aftershocks form two clusters, a diffuse southern cluster and a steeply west‐dipping northern cluster with a gap in between where maximum slip has been inferred. We compute moment tensors for the Mw>4 aftershocks using a cut‐and‐paste method and careful selection of regional broadband stations. The moment tensor solutions do not exhibit significant variability or systematic differences between the northern and southern clusters and, on average, agree well with the mainshock fault‐plane parameters. We propose that the mainshock rupture initiated in the Yakutat lower crust or uppermost mantle and propagated both upward into the crust to near its top and downward into the mantle. The majority of the aftershocks are confined to the seismically active Yakutat crust and located both on and in the hanging wall of the mainshock fault rupture.


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>


2021 ◽  
Author(s):  
Minhee Choi ◽  
David W. Eaton ◽  
et al.

Catalog of relocated seismicity, table of moment tensor parameters, detailed methodology of the velocity model, hierarchical clustering, moment tensors, stress inversion, Coulomb stress calculation, and Figures S1–S12.<br>


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