scholarly journals Rupture process by waveform inversion using simulated annealing and simulation of broadband ground motions

2005 ◽  
Vol 57 (7) ◽  
pp. 571-590 ◽  
Author(s):  
Yoshiaki Shiba ◽  
Kojiro Irikura
Keyword(s):  
Simulated Annealing ◽  
Ground Motions ◽  
Waveform Inversion ◽  
Rupture Process

Rupture Process of the Mainshock of the 2019 Ridgecrest Earthquake Sequence from Waveform Inversion with Empirical Green’s Functions

2021 ◽  
Author(s):  
Shuang-Lan Wu ◽  
Atsushi Nozu ◽  
Yosuke Nagasaka
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Ground Motions ◽  
Strong Motion ◽  
Rupture Process ◽  
Earthquake Sequence ◽  
Slip Model ◽  
Near Fault ◽  
Empirical Green’S Functions ◽  
Empirical Green's Functions

ABSTRACT The 2019 Mw 7.1 mainshock of the Ridgecrest earthquake sequence, which was the first event exceeding Mw 7.0 in California since the 1999 Hector Mine earthquake, caused near-fault ground motions exceeding 0.5g and 70  cm/s. In this study, the rupture process and the generation mechanism of strong ground motions of the mainshock were investigated through waveform inversions of strong-motion data in the frequency range of 0.2–2.0 Hz using empirical Green’s functions (EGFs). The results suggest that the mainshock involved two large slip regions: the primary one with a maximum slip of approximately 4.4 m was centered ∼3  km northwest of the hypocenter, which was slightly shallower than the hypocenter, and the secondary one was centered ∼25  km southeast of the hypocenter. Outside these regions, the slip was rather small and restricted to deeper parts of the fault. A relatively small rupture velocity of 2.1  km/s was identified. The robustness of the slip model was examined by conducting additional inversion analyses with different combinations of EGF events and near-fault stations. In addition, using the preferred slip model, we synthesized strong motions at stations that were not used in the inversion analyses. The synthetic waveforms captured the timing of the main phases of observed waveforms, indicating the validity of the major spatiotemporal characteristics of the slip model. Our large slip regions are also generally visible in the models proposed by other researchers based on different datasets and focusing on lower frequency ranges (generally lower than 0.5 Hz). In particular, two large slip regions in our model are very consistent with two of the four subevents identified by Ross et al. (2019), which may indicate that part of the large slip regions that generated low-frequency ground motions also generated high-frequency ground motions up to 2.0 Hz during the Ridgecrest mainshock.

Full-waveform inversion of salt models using shape optimization and simulated annealing

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R793-R804 ◽  
Author(s):  
Debanjan Datta ◽  
Mrinal K. Sen ◽  
Faqi Liu ◽  
Scott Morton
Keyword(s):  
Simulated Annealing ◽  
Least Squares ◽  
Level Set ◽  
Waveform Inversion ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform ◽  
Starting Model

A good starting model is imperative in full-waveform inversion (FWI) because it solves a least-squares inversion problem using a local gradient-based optimization method. A suboptimal starting model can result in cycle skipping leading to poor convergence and incorrect estimation of subsurface properties. This problem is especially crucial for salt models because the strong velocity contrasts create substantial time shifts in the modeled seismogram. Incorrect estimation of salt bodies leads to velocity inaccuracies in the sediments because the least-squares gradient aims to reduce traveltime differences without considering the sharp velocity jump between sediments and salt. We have developed a technique to estimate velocity models containing salt bodies using a combination of global and local optimization techniques. To stabilize the global optimization algorithm and keep it computationally tractable, we reduce the number of model parameters by using sparse parameterization formulations. The sparse formulation represents sediments using a set of interfaces and velocities across them, whereas a set of ellipses represents the salt body. We use very fast simulated annealing (VFSA) to minimize the misfit between the observed and synthetic data and estimate an optimal model in the sparsely parameterized space. The VFSA inverted model is then used as a starting model in FWI in which the sediments and salt body are updated in the least-squares sense. We partition model updates into sediment and salt updates in which the sediments are updated like conventional FWI, whereas the shape of the salt is updated by taking the zero crossing of an evolving level set surface. Our algorithm is tested on two 2D synthetic salt models, namely, the Sigsbee 2A model and a modified SEG Advanced Modeling Program (SEAM) Phase I model while fixing the top of the salt. We determine the efficiency of the VFSA inversion and imaging improvements from the level set FWI approach and evaluate a few sources of uncertainty in the estimation of salt shapes.

Crosshole Waveform Inversion – Quantifying Anisotropy through Simulated Annealing

2012 ◽  
Author(s):  
Michael Afanasiev ◽  
R. Gerhard Pratt ◽  
Rie Kamei ◽  
Glenn McDowell
Keyword(s):  
Simulated Annealing ◽  
Waveform Inversion
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