scholarly journals Implications of 3D Seismic Raytracing on Focal Mechanism Determination

2019 ◽  
Vol 109 (6) ◽  
pp. 2746-2754
Author(s):  
Katharina Newrkla ◽  
Hasbi Ash Shiddiqi ◽  
Annie Elisabeth Jerkins ◽  
Henk Keers ◽  
Lars Ottemöller
Keyword(s):  
Focal Mechanism ◽  
Historical Earthquakes ◽  
Velocity Model ◽  
Waveform Data ◽  
Focal Mechanism Solutions ◽  
Velocity Models ◽  
Maximum Value ◽  
3D Velocity Model ◽  
First Motion

Abstract The purpose of this study is to investigate apparent first‐motion polarities mismatch at teleseismic distances in the determination of focal mechanism. We implement and compare four seismic raytracing algorithms to compute ray paths and travel times in 1D and 3D velocity models. We use the raytracing algorithms to calculate the takeoff angles from the hypocenter of the 24 August 2016 Mw 6.8 Chauk earthquake (depth 90 km) in central Myanmar to the stations BFO, GRFO, KONO, and ESK in Europe using a 3D velocity model of the upper mantle below Asia. The differences in the azimuthal angles calculated in the 1D and 3D velocity models are considerable and have a maximum value of 19.6°. Using the takeoff angles for the 3D velocity model, we are able to resolve an apparent polarity mismatch where these stations move from the dilatational to the compressional quadrant. The polarities of synthetic waveforms change accordingly when we take the takeoff angles corresponding to the 3D model into account. This method has the potential to improve the focal mechanism solutions, especially for historical earthquakes where limited waveform data are available.

The S wave project for focal mechanism studies earthquakes of 1962

1964 ◽  
Vol 54 (6B) ◽  
pp. 2199-2208 ◽  
Author(s):  
William Stauder ◽  
G. A. Bollinger
Keyword(s):  
Focal Mechanism ◽  
P Wave ◽  
S Wave ◽  
Polarization Data ◽  
Saint Louis ◽  
Saint Louis University ◽  
S Waves ◽  
Focal Mechanism Solutions ◽  
First Motion

Abstract The Department of Geophysics of Saint Louis University has instituted a routine program for the determination of the focal mechanism of the larger earthquakes of each year using methods developed for the use of S waves in focal mechanism studies. Suites of records from selected stations are assembled from the WWSS microfilm file for each earthquake of interest. A combination of P-wave first motion and S-wave polarization data is then used to determine graphically the mechanism of the earthquakes. Thirty-six earthquakes of 1962 were selected for study. The focal mechanism solutions are presented for twenty-three of these shocks. There is evidence of patterns characteristic of the focal mechanism of earthquakes occurring in Kamchatka, the Aleutian Islands and South America. A complete presentation of all the data and of all the solutions is available in a more lengthy report.

scholarly journals Earthquake location in tectonic structures of the Alpine Chain: the case of the Constance Lake (Central Europe) seismic sequence

2021 ◽  
Author(s):  
Francesca D’Ajello Caracciolo ◽  
Rodolfo Console
Keyword(s):  
Central Europe ◽  
Velocity Model ◽  
Moho Depth ◽  
Seismic Sequence ◽  
Tectonic Structures ◽  
Study Region ◽  
Waveform Data ◽  
Seismic Stations ◽  
Velocity Models ◽  
Master Event

AbstractA set of four magnitude Ml ≥ 3.0 earthquakes including the magnitude Ml = 3.7 mainshock of the seismic sequence hitting the Lake Constance, Southern Germany, area in July–August 2019 was studied by means of bulletin and waveform data collected from 86 seismic stations of the Central Europe-Alpine region. The first single-event locations obtained using a uniform 1-D velocity model, and both fixed and free depths, showed residuals of the order of up ± 2.0 s, systematically affecting stations located in different areas of the study region. Namely, German stations to the northeast of the epicenters and French stations to the west exhibit negative residuals, while Italian stations located to the southeast are characterized by similarly large positive residuals. As a consequence, the epicentral coordinates were affected by a significant bias of the order of 4–5 km to the NNE. The locations were repeated applying a method that uses different velocity models for three groups of stations situated in different geological environments, obtaining more accurate locations. Moreover, the application of two methods of relative locations and joint hypocentral determination, without improving the absolute location of the master event, has shown that the sources of the four considered events are separated by distances of the order of one km both in horizontal coordinates and in depths. A particular attention has been paid to the geographical positions of the seismic stations used in the locations and their relationship with the known crustal features, such as the Moho depth and velocity anomalies in the studied region. Significant correlations between the observed travel time residuals and the crustal structure were obtained.

Assessing uncertainties in velocity models and images with a fast nonlinear uncertainty quantification method

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. R63-R75 ◽  
Author(s):  
Gregory Ely ◽  
Alison Malcolm ◽  
Oleg V. Poliannikov
Keyword(s):  
Uncertainty Quantification ◽  
Seismic Imaging ◽  
Low Frequency ◽  
Expansion Method ◽  
Velocity Model ◽  
Image Features ◽  
Visible Image ◽  
Waveform Data ◽  
Velocity Models ◽  
Seismic Reflections

Seismic imaging is conventionally performed using noisy data and a presumably inexact velocity model. Uncertainties in the input parameters propagate directly into the final image and therefore into any quantity of interest, or qualitative interpretation, obtained from the image. We considered the problem of uncertainty quantification in velocity building and seismic imaging using Bayesian inference. Using a reduced velocity model, a fast field expansion method for simulating recorded wavefields, and the adaptive Metropolis-Hastings algorithm, we efficiently quantify velocity model uncertainty by generating multiple models consistent with low-frequency full-waveform data. A second application of Bayesian inversion to any seismic reflections present in the recorded data reconstructs the corresponding structures’ position along with its associated uncertainty. Our analysis complements rather than replaces traditional imaging because it allows us to assess the reliability of visible image features and to take that into account in subsequent interpretations.

Generalization of traveltime inversion

Geophysics ◽  
1992 ◽  
Vol 57 (1) ◽  
pp. 9-14 ◽  
Author(s):  
Gérard C. Herman
Keyword(s):  
Time Windows ◽  
Velocity Model ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Error Norm ◽  
Arrival Times ◽  
Traveltime Inversion ◽  
Velocity Models ◽  
Use Of Data

A nonlinear inversion method is presented, especially suited for the determination of global velocity models. In a certain sense, it can be considered as a generalization of methods based on traveltimes of reflections, with the requirement of accurately having to determine traveltimes replaced by the (less stringent and less subjective) requirement of having to define time windows around main reflections (or composite reflections) of interest. It is based on an error norm, related to the phase of the wavefield, which is directly computed from wavefield measurements. Therefore, the cumbersome step of interpreting arrivals and measuring arrival times is avoided. The method is applied to the reconstruction of a depth‐dependent global velocity model from a set of plane‐wave responses and is compared to other methods. Despite the fact that the new error norm only makes use of data having a temporal bandwidth of a few Hz, its behavior is very similar to the behavior of the error norm used in traveltime inversion.

A new 3D velocity model of Central Apennines: insights from 2D/3D geological modelling and earthquake relocation.

2021 ◽  
Author(s):  
Andrea D'Ambrosio ◽  
Eugenio Carminati ◽  
Carlo Doglioni ◽  
Lorenzo Lipparini ◽  
Mario Anselmi ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Cross Sections ◽  
3D Model ◽  
Velocity Model ◽  
Earthquake Relocation ◽  
Central Apennines ◽  
Seismic Stations ◽  
Velocity Models ◽  
3D Velocity Model ◽  
Seismogenic Faults

<p>The Central Apennines fold-and-thrust belt (Central Italy) is characterized by the presence of several active faults, potentially capable of generating damaging earthquakes. To support seismic hazard studies over the area, a new 3D velocity model was built, integrating a wide range of surface and subsurface data.</p><p>The tectonic framework of the area (from Sulmona plain to Maiella Mt), is still debated in literature, also due to the lack of both an adequate geophysical data set and a reliable velocity model at the crustal scale.</p><p>In addition, the low number of seismic stations available for the acquisition of Vp/Vs arrival times, and the very low seismicity detected in the study area (the Sulmona and Caramanico Apennine valleys are considered as “seismic gaps”), lead to a difficult interpretation of the subsurface tectonic structures.</p><p>3D velocity modelling could well represent an important tool to support these deep crustal reconstructions as well earthquake relocation studies and could enhance the definition of seismogenic faults deep geometries, hence supporting a better risk assessment over the area of these potential locked faults.</p><p>Using the knowledge developed within the oil&gas industry as well in gas/CO<sub>2</sub> storage projects for the construction of 3D velocity models, extensively used to obtain subsurface imaging and define the geometry of the reservoirs and traps in the depth domain, a similar methodological approach was implemented over the study area.</p><p>The subsurface dataset was partially inherited by the past hydrocarbon exploration activities (e.g. seismic lines, exploration wells and sonic logs) and by the literature (e.g. time/depth regional models). Tomographic sections and relocated earthquake hypocentres were also integrated form geophysical studies. Geological maps (1:50.000 & 1:100.000 scale) represent the surface dataset that we used to create the surface interpretation of the regional geology.</p><p>As a first step, 18 2D balanced regional geological cross-sections, dip-oriented (W-E) across the Central Apennine, were built define the structural picture at regional scale. The cross-sections were built using MOVE (Petroleum Experts) and Petrel (Schlumberger) software. The following modelling step was the 3D model construction, in which the surface/subsurface data as well as all the geological sections were integrated in the final 3D structural and geological model.</p><p>The main geological layers reconstructed in the 3D model were than populated using the appropriated interval velocity values, building the final 3D velocity model in which the lateral velocity variation due to the presence of different facies/geological domains were considered.</p><p>As one of the results, we defined several 1D-velocity models coherent with the regional 3D velocity model, in which the key seismic stations and the earthquakes hypocentres dataset for the most potential seismogenic faults were included. 1D models were characterized by different degree of simplification, in order to test diverse approaches for the earthquake relocation. For this exercise, we used public dataset extracted by the analysis of microseismicity of the Sulmona basin.</p><p>We believe that the proposed approach can represents an effective method for combining geological and geophysical data to improve the subsurface and seismogenic faults interpretation, contributing to the seismic hazard assessment.</p>

Combination of P and S data for the determination of earthquake focal mechanism

1971 ◽  
Vol 61 (6) ◽  
pp. 1655-1673 ◽  
Author(s):  
Umesh Chandra
Keyword(s):  
Focal Mechanism ◽  
P Wave ◽  
Wave Polarization ◽  
S Wave ◽  
Polarization Data ◽  
Wave Data ◽  
Earthquake Focal Mechanism ◽  
First Motion ◽  
Depth Ranges

abstract A method has been proposed for the combination of P-wave first-motion directions and S-wave polarization data for the numerical determination of earthquake focal mechanism. The method takes into account the influence of nearness of stations with inconsistent P-wave polarity observations, with respect to the assumed nodal planes. The mechanism solutions for six earthquakes selected from different geographic locations and depth ranges have been determined. Equal area projections of the nodal planes together with the P-wave first-motion and S-wave polarization data are presented for each earthquake. The quality of resolution of nodal plane determination on the basis of P-wave data, S-wave polarization, and the combination of P and S-wave data according to the present method, is discussed.

Diffraction imaging and depth-velocity inversion with 3D P-Cable seismic data

2021 ◽  
Author(s):  
Alexander Bauer ◽  
Benjamin Schwarz ◽  
Dirk Gajewski
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Computational Cost ◽  
Velocity Model ◽  
Data Cube ◽  
Velocity Inversion ◽  
Velocity Models ◽  
North East ◽  
3D Velocity Model ◽  
Zero Offset

<p>Most established methods for the estimation of subsurface velocity models rely on the measurements of reflected or diving waves and therefore require data with sufficiently large source-receiver offsets. For seismic data that lacks these offsets, such as vintage data, low-fold academic data or near zero-offset P-Cable data, these methods fail. Building on recent studies, we apply a workflow that exploits the diffracted wavefield for depth-velocity-model building. This workflow consists of three principal steps: (1) revealing the diffracted wavefield by modeling and adaptively subtracting reflections from the raw data, (2) characterizing the diffractions with physically meaningful wavefront attributes, (3) estimating depth-velocity models with wavefront tomography. We propose a hybrid 2D/3D approach, in which we apply the well-established and automated 2D workflow to numerous inlines of a high-resolution 3D P-Cable dataset acquired near Ritter Island, a small volcanic island located north-east of New Guinea known for a catastrophic flank collapse in 1888. We use the obtained set of parallel 2D velocity models to interpolate a 3D velocity model for the whole data cube, thus overcoming possible issues such as varying data quality in inline and crossline direction and the high computational cost of 3D data analysis. Even though the 2D workflow may suffer from out-of-plane effects, we obtain a smooth 3D velocity model that is consistent with the data.</p>

Detection of possible seismic station phase reversals using parametric data from seismological bulletins

2021 ◽  
Author(s):  
Konstantinos Lentas
Keyword(s):  
Goodness Of Fit ◽  
Seismic Station ◽  
Waveform Data ◽  
Seismic Stations ◽  
Velocity Models ◽  
Parametric Data ◽  
Source Mechanisms ◽  
First Motion ◽  
Earthquake Mechanism ◽  
Using Data

<p>A simple and fast technique to detect systematic changes in the performance of seismic stations by using parametric data is being presented. The methodology is based on a simple principal, notably, quantifying the goodness of fit of first motion manually picked polarities from seismological bulletins versus available earthquake mechanism solutions over time. The probability of the reporting polarity data fitting (and not fitting) source mechanisms is quantified by calculating the probability distribution of several Bernoulli trials over a randomly perturbed set of hypocentres and velocity models for each earthquake mechanism - station polarity combination. The method was applied to the registered seismic stations in the bulletin of the International Seismological Centre (ISC) after grouping each polarity pick by reporting agency, using data from the past two decades. The overall agreement of first motion polarities against source mechanisms is found to be good with a few cases of seismic stations showing indications of systematic phase reversals over certain time periods. Specifically, results were obtained for 50% of the registered stations at the ISC, and from these stations 70% show reliable operation during the operational time period under investigation, with only 3% showing the opposite, and 7% showing evidence of systematic changes in the quality of the reported first motion polarities. The rest showed great variability over short periods of time, which does not allow one to draw any conclusions. Comparing waveform data with the associated reported polarities revealed a mixture of cases of either questionable picking or true station phase reversals.</p>

scholarly journals Fault Geometry and Mechanism of the Mw 5.7 Nakchu Earthquake in Tibet Inferred from InSAR Observations and Stress Measurements

2021 ◽  
Vol 13 (24) ◽  
pp. 5142
Author(s):  
Yujiang Li ◽  
Yongsheng Li ◽  
Xingping Hu ◽  
Haoqing Liu
Keyword(s):  
Focal Mechanism ◽  
Historical Earthquakes ◽  
Tectonic Stress ◽  
Indian Plate ◽  
Coseismic Deformation ◽  
Normal Faulting ◽  
Eurasian Plate ◽  
Seismogenic Fault ◽  
Stress Measurements ◽  
Focal Mechanism Solutions

Different types of focal mechanism solutions for the 19 March 2021 Mw 5.7 Nakchu earthquake, Tibet, limit our understanding of this earthquake’s seismogenic mechanism and geodynamic process. In this study, the coseismic deformation field was determined and the geometric parameters of the seismogenic fault were inverted via Interferometric Synthetic Aperture Radar (InSAR) processing of Sentinel-1 data. The inversion results show that the focal mechanism solutions of the Nakchu earthquake are 237°/69°/−70° (strike/dip/rake), indicating that the seismogenic fault is a NEE-trending, NW-dipping fault dominated by the normal faulting with minor sinistral strike-slip components. The regional tectonic stress field derived from the in-situ stress measurements shows that the orientation of maximum principal compressive stress around the epicenter of the Nakchu earthquake is NNE, subparallel to the fault strike, which controlled the dominant normal faulting. The occurrence of seven M ≥ 7.0 historical earthquakes since the M 7.0 Shenza earthquake in 1934 caused a stress increase of 1.16 × 105 Pa at the hypocenter, which significantly advanced the occurrence of the Nakchu earthquake. Based on a comprehensive analysis of stress fields and focal mechanisms of the Nakchu earthquake, we propose that the dominated normal faulting occurs to accommodate the NE-trending compression of the Indian Plate to the Eurasian Plate and the strong historical earthquakes hastened the process. These results provide a theoretical basis for understanding the geometry and mechanics of the seismogenic fault that produced the Nakchu earthquake.

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