scholarly journals Using Dense Array Waveform Correlations to Build a Velocity Model with Stochastic Variability

Author(s):  
Arben Pitarka ◽  
Robert Mellors

ABSTRACT In an ongoing effort to improve 3D seismic-wave propagation modeling for frequencies up to 10 Hz, we used cross correlations between vertical-component waveforms from an underground chemical explosion to estimate the statistical properties of small-scale velocity heterogeneities. The waveforms were recorded by a dense 2D seismic array deployed during the Source Physics Experiments for event number 5 (SPE-5) in a series of six underground chemical explosions, conducted at the Nevada National Security Site. The array consisted of 996 geophones with a 50–100 m grid spacing, deployed at the SPE site at the north end of the Yucca Flat basin. The SPE were conducted to investigate the generation and propagation of seismic and acoustic waves from underground explosions. Comparisons of decay rates of waveform cross correlations as function of interstation distance, computed for observed and synthetic seismograms from the SPE-5 chemical explosion, were used to constrain statistical properties of correlated stochastic velocity perturbations representing small-scale heterogeneities added to a geology-based velocity model of the Yucca Flat basin. Using comparisons between recorded and simulated waveform cross correlations, we were able to recover sets of statistical properties of small-scale velocity perturbations in the velocity model that produce the best-fit between the recorded and simulated ground motion. The stochastic velocity fluctuations in the velocity model that produced the smallest misfits have a horizontal correlation distance of between 400 and 800 m, a vertical correlation distance between 100 and 200 m, and a standard deviation of 10% from the nominal model velocity in the alluvium basin layers. They also have a horizontal correlation distance of 1000 m, a vertical correlation distance of 250 m, and a standard deviation of 6% in the underlying and consolidated sedimentary layers, up to a depth of 4 km. Comparisons between observed and simulated wavefields were used to assess the proposed small-scale heterogeneity enhancements to the Yucca Flat basin model. We found that adding a depth-resolved stochastic variability to the geology-based velocity model improves the overall performance of ground-motion simulations of an SPE-5 explosion in the modeled frequency range up to 10 Hz. The results may be applicable to other similar basins.

2020 ◽  
Vol 110 (2) ◽  
pp. 471-488 ◽  
Author(s):  
Samantha M. Palmer ◽  
Gail M. Atkinson

ABSTRACT Spectral decay of ground-motion amplitudes at high frequencies is primarily influenced by two parameters: site-related kappa (κ0) and regional Q (quality factor, inversely proportional to anelastic attenuation). We examine kappa and apparent Q-values (Qa) for M≥3.5 earthquakes recorded at seismograph stations on rock sites in eastern and western Canada. Our database contains 20 earthquakes recorded on nine stations in eastern Canada and 404 earthquakes recorded on eight stations in western Canada, resulting in 105 and 865 Fourier amplitude spectra, respectively. We apply two different methods: (1) a modified version of the classical S-wave acceleration method; and (2) a new stacking method that is consistent with the use of kappa in ground-motion modeling. The results are robust with respect to the method used and also with respect to the frequency band selected, which ranges from 9 to 38 Hz depending on the region, event, and method. Kappa values obtained from the classical method are consistent with those of the stacked method, but the stacked method provides a lower uncertainty. A general observation is that kappa is usually larger, and apparent Q is smaller, for the horizontal component in comparison to the vertical component. We determine an average regional κ0=7  ms (horizontal) and 0 ms (vertical) for rock sites in eastern Canada; we obtain κ0=19  ms (horizontal) and 14 ms (vertical) for rock sites in western Canada. We note that kappa measurements are quite sensitive to details of data selection criteria and methodology, and may be significantly influenced by site effects, resulting in large site-to-site variability.


2021 ◽  
Vol 9 (6) ◽  
pp. 585
Author(s):  
Minghao Wu ◽  
Leen De Vos ◽  
Carlos Emilio Arboleda Chavez ◽  
Vasiliki Stratigaki ◽  
Maximilian Streicher ◽  
...  

The present work introduces an analysis of the measurement and model effects that exist in monopile scour protection experiments with repeated small scale tests. The damage erosion is calculated using the three dimensional global damage number S3D and subarea damage number S3D,i. Results show that the standard deviation of the global damage number σ(S3D)=0.257 and is approximately 20% of the mean S3D, and the standard deviation of the subarea damage number σ(S3D,i)=0.42 which can be up to 33% of the mean S3D. The irreproducible maximum wave height, chaotic flow field and non-repeatable armour layer construction are regarded as the main reasons for the occurrence of strong model effects. The measurement effects are limited to σ(S3D)=0.039 and σ(S3D,i)=0.083, which are minor compared to the model effects.


Geophysics ◽  
2008 ◽  
Vol 73 (2) ◽  
pp. S47-S61 ◽  
Author(s):  
Paul Sava ◽  
Oleg Poliannikov

The fidelity of depth seismic imaging depends on the accuracy of the velocity models used for wavefield reconstruction. Models can be decomposed in two components, corresponding to large-scale and small-scale variations. In practice, the large-scale velocity model component can be estimated with high accuracy using repeated migration/tomography cycles, but the small-scale component cannot. When the earth has significant small-scale velocity components, wavefield reconstruction does not completely describe the recorded data, and migrated images are perturbed by artifacts. There are two possible ways to address this problem: (1) improve wavefield reconstruction by estimating more accurate velocity models and image using conventional techniques (e.g., wavefield crosscorrelation) or (2) reconstruct wavefields with conventional methods using the known background velocity model but improve the imaging condition to alleviate the artifacts caused by the imprecise reconstruction. Wedescribe the unknown component of the velocity model as a random function with local spatial correlations. Imaging data perturbed by such random variations is characterized by statistical instability, i.e., various wavefield components image at wrong locations that depend on the actual realization of the random model. Statistical stability can be achieved by preprocessing the reconstructed wavefields prior to the imaging condition. We use Wigner distribution functions to attenuate the random noise present in the reconstructed wavefields, parameterized as a function of image coordinates. Wavefield filtering using Wigner distribution functions and conventional imaging can be lumped together into a new form of imaging condition that we call an interferometric imaging condition because of its similarity to concepts from recent work on interferometry. The interferometric imaging condition can be formulated both for zero-offset and for multioffset data, leading to robust, efficient imaging procedures that effectively attenuate imaging artifacts caused by unknown velocity models.


2021 ◽  
Author(s):  
Jagdish Chandra Vyas ◽  
Martin Galis ◽  
Paul Martin Mai

<p>Geological observations show variations in fault-surface topography not only at large scale (segmentation) but also at small scale (roughness). These geometrical complexities strongly affect the stress distribution and frictional strength of the fault, and therefore control the earthquake rupture process and resulting ground-shaking. Previous studies examined fault-segmentation effects on ground-shaking, but our understanding of fault-roughness effects on seismic wavefield radiation and earthquake ground-motion is still limited.  </p><p>In this study we examine the effects of fault roughness on ground-shaking variability as a function of distance based on 3D dynamic rupture simulations. We consider linear slip-weakening friction, variations of fault-roughness parametrizations, and alternative nucleation positions (unilateral and bilateral ruptures). We use generalized finite difference method to compute synthetic waveforms (max. resolved frequency 5.75 Hz) at numerous surface sites  to carry out statistical analysis.  </p><p>Our simulations reveal that ground-motion variability from unilateral ruptures is almost independent of  distance from the fault, with comparable or higher values than estimates from ground-motion prediction equations (e.g., Boore and Atkinson, 2008; Campbell and Bozornia, 2008). However, ground-motion variability from bilateral ruptures decreases with increasing distance, in contrast to previous studies (e.g., Imtiaz et. al., 2015) who observe an increasing trend with distance. Ground-shaking variability from unilateral ruptures is higher than for bilateral ruptures, a feature due to intricate seismic radiation patterns related to fault roughness and hypocenter location. Moreover, ground-shaking variability for rougher faults is lower than for smoother faults. As fault roughness increases the difference in ground-shaking variabilities between unilateral and bilateral ruptures increases. In summary, our simulations help develop a fundamental understanding of ground-motion variability at high frequencies (~ 6 Hz) due small-scale geometrical fault-surface variations.</p>


Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. R11-R28 ◽  
Author(s):  
Kun Xiang ◽  
Evgeny Landa

Seismic diffraction waveform energy contains important information about small-scale subsurface elements, and it is complementary to specular reflection information about subsurface properties. Diffraction imaging has been used for fault, pinchout, and fracture detection. Very little research, however, has been carried out taking diffraction into account in the impedance inversion. Usually, in the standard inversion scheme, the input is the migrated data and the assumption is taken that the diffraction energy is optimally focused. This assumption is true only for a perfectly known velocity model and accurate true amplitude migration algorithm, which are rare in practice. We have developed a new approach for impedance inversion, which takes into account diffractive components of the total wavefield and uses the unmigrated input data. Forward modeling, designed for impedance inversion, includes the classical specular reflection plus asymptotic diffraction modeling schemes. The output model is composed of impedance perturbation and the low-frequency model. The impedance perturbation is estimated using the Bayesian approach and remapped to the migrated domain by the kinematic ray tracing. Our method is demonstrated using synthetic and field data in comparison with the standard inversion. Results indicate that inversion with taking into account diffraction can improve the acoustic impedance prediction in the vicinity of local reflector discontinuities.


2015 ◽  
Vol 31 (3) ◽  
pp. 1629-1645 ◽  
Author(s):  
Ronnie Kamai ◽  
Norman Abrahamson

We evaluate how much of the fling effect is removed from the NGA database and accompanying GMPEs due to standard strong motion processing. The analysis uses a large set of finite-fault simulations, processed with four different high-pass filter corners, representing the distribution within the PEER ground motion database. The effects of processing on the average horizontal component, the vertical component, and peak ground motion values are evaluated by taking the ratio between unprocessed and processed values. The results show that PGA, PGV, and other spectral values are not significantly affected by processing, partly thanks to the maximum period constraint used when developing the NGA GMPEs, but that the bias in peak ground displacement should not be ignored.


2021 ◽  
Author(s):  
Grigorios Lavrentiadis ◽  
Norman A. Abrahamson ◽  
Nicolas M. Kuehn

Abstract A new non-ergodic ground-motion model (GMM) for effective amplitude spectral (EAS) values for California is presented in this study. EAS, which is defined in Goulet et al. (2018), is a smoothed rotation-independent Fourier amplitude spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset Ancheta et al. (2013). The Bayless and Abrahamson (2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to 40% smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past event.


2012 ◽  
Vol 15 (8) ◽  
pp. 1439-1453 ◽  
Author(s):  
Behrouz Asgarian ◽  
Anahita Norouzi ◽  
Pejman Alanjari ◽  
Masoud Mirtaheri

2005 ◽  
Vol 12 (5) ◽  
pp. 671-689 ◽  
Author(s):  
D. Chalikov

Abstract. A numerical model for long-term simulation of gravity surface waves is described. The model is designed as a component of a coupled Wave Boundary Layer/Sea Waves model, for investigation of small-scale dynamic and thermodynamic interactions between the ocean and atmosphere. Statistical properties of nonlinear wave fields are investigated on a basis of direct hydrodynamical modeling of 1-D potential periodic surface waves. The method is based on a nonstationary conformal surface-following coordinate transformation; this approach reduces the principal equations of potential waves to two simple evolutionary equations for the elevation and the velocity potential on the surface. The numerical scheme is based on a Fourier transform method. High accuracy was confirmed by validation of the nonstationary model against known solutions, and by comparison between the results obtained with different resolutions in the horizontal. The scheme allows reproduction of the propagation of steep Stokes waves for thousands of periods with very high accuracy. The method here developed is applied to simulation of the evolution of wave fields with large number of modes for many periods of dominant waves. The statistical characteristics of nonlinear wave fields for waves of different steepness were investigated: spectra, curtosis and skewness, dispersion relation, life time. The prime result is that wave field may be presented as a superposition of linear waves is valid only for small amplitudes. It is shown as well, that nonlinear wave fields are rather a superposition of Stokes waves not linear waves. Potential flow, free surface, conformal mapping, numerical modeling of waves, gravity waves, Stokes waves, breaking waves, freak waves, wind-wave interaction.


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