Seismic Wave Propagation and Basin Amplification in the Wasatch Front, Utah

Author(s):  
Morgan P. Moschetti ◽  
David Churchwell ◽  
Eric M. Thompson ◽  
John M. Rekoske ◽  
Emily Wolin ◽  
...  

Abstract Ground-motion analysis of more than 3000 records from 59 earthquakes, including records from the March 2020 Mw 5.7 Magna earthquake sequence, was carried out to investigate site response and basin amplification in the Wasatch Front, Utah. We compare ground motions with the Bayless and Abrahamson (2019; hereafter, BA18) ground-motion model (GMM) for Fourier amplitude spectra, which was developed on crustal earthquake records from California and other tectonically active regions. The Wasatch Front records show a significantly different near-source rate of distance attenuation than the BA18 model, which we attribute to differences in (apparent) geometric attenuation. Near-source residuals show a period dependence of this effect, with greater attenuation at shorter periods (T<0.5  s) and a correlation between period and the distance over which the discrepancy manifests (∼20–50  km). We adjusted the recorded ground motions for these regional path effects and solved for station site terms using linear mixed-effects regressions, with groupings for events and stations. We analyzed basin amplification by comparing the site terms with the basin geometry and basin depths from two seismic-velocity models for the region. Sites over the deeper parts of the sedimentary basins are amplified by factors of 3–10, relative to sites with thin sedimentary cover, with greater amplification at longer periods (T≳1  s). Average ground-motion variability increases with period, and long-period variability exhibits a slight increase at the basin edges. These results indicate regional seismic wave propagation effects requiring further study, and potentially a regionalized GMM, as well as highlight basin amplification complexities that may be incorporated into seismic hazard assessments.

Author(s):  
Jaeseok Lee ◽  
Jung-Hun Song ◽  
Seongryong Kim ◽  
Junkee Rhie ◽  
Seok Goo Song

ABSTRACT Accurate and practical ground-motion predictions for potential large earthquakes are crucial for seismic hazard analysis of areas with insufficient instrumental data. Studies on historical earthquake records of the Korean Peninsula suggest that damaging earthquakes are possible in the southeastern region. Yet classical ground-motion prediction methods are limited in considering the physical rupture process and its effects on ground motion in complex velocity structures. In this study, we performed ground-motion simulations based on rigorous physics through pseudodynamic source modeling and wave propagation simulations in a 3D seismic velocity model. Ensembles of earthquake scenarios were generated by emulating the one- and two-point statistics of earthquake source parameters derived from a series of dynamic rupture models. The synthetic seismograms and the distributions of simulated peak ground velocities (PGVs) were compared with the observations of the 2016 Mw 5.4 Gyeongju earthquake in the Korean Peninsula. The effects of surface-wave radiation, rupture directivity, and both local and regional amplifications from the 3D wave propagation were reproduced accurately in the spatial distribution of simulated PGVs, in agreement with the observations from dense seismic networks by mean log residuals of −0.28 and standard deviations of 0.78. Amplifications in ground motions were found in regions having low crustal velocities and in regions of constructive interference from the crustal shear-wave phases associated with postcritical reflections from the Moho discontinuity. We extended the established approach to earthquake scenarios of Mw 6.0, 6.5, and 7.0, at the same location, to provide the distribution of ground motions from potential large earthquakes in the area. Although we demonstrate the value of these simulations, improvements in the accuracy of the 3D seismic velocity model and the scaling relationship of the source models would be necessary for a more accurate estimation of near-source ground motions.


Author(s):  
Bob Paap ◽  
Dirk Kraaijpoel ◽  
Brecht Wassing ◽  
Jan-Diederik van Wees

Summary Numerical simulations of seismic wave propagation usually rely on a simple source model consisting of an idealized point location and a moment tensor. In general, this is a valid approximation when the source dimensions are small relative to the distance of points at which the seismic wave motions are to be evaluated. Otherwise, a more realistic spatio-temporal source representation is required to accurately calculate ground motions at the position of monitoring stations. Here, we present a generic approach to couple geomechanical simulations to seismic wave propagation models using the concept of the equivalent force field. This approach allows the simulation of seismic wave propagation resulting from the spatio-temporal dependent earthquake nucleation and rupture processes. Within the geomechanical package two separate geomechanics codes are used to simulate both the slow loading stage leading to earthquake nucleation as well as the successive dynamic rupture stage. We demonstrate the approach to a case of induced seismicity, where fault reactivation occurs due to production from a natural gas reservoir.


2021 ◽  
Vol 1 (3) ◽  
pp. 126-134
Author(s):  
Yan Yang ◽  
Angela F. Gao ◽  
Jorge C. Castellanos ◽  
Zachary E. Ross ◽  
Kamyar Azizzadenesheli ◽  
...  

Abstract Seismic wave propagation forms the basis for most aspects of seismological research, yet solving the wave equation is a major computational burden that inhibits the progress of research. This is exacerbated by the fact that new simulations must be performed whenever the velocity structure or source location is perturbed. Here, we explore a prototype framework for learning general solutions using a recently developed machine learning paradigm called neural operator. A trained neural operator can compute a solution in negligible time for any velocity structure or source location. We develop a scheme to train neural operators on an ensemble of simulations performed with random velocity models and source locations. As neural operators are grid free, it is possible to evaluate solutions on higher resolution velocity models than trained on, providing additional computational efficiency. We illustrate the method with the 2D acoustic wave equation and demonstrate the method’s applicability to seismic tomography, using reverse-mode automatic differentiation to compute gradients of the wavefield with respect to the velocity structure. The developed procedure is nearly an order of magnitude faster than using conventional numerical methods for full waveform inversion.


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