Efficient waveform inversion for average earthquake rupture in three-dimensional structures

Hsieh, Ming Che; Zhao, Li; Fong, Kuo

doi:10.1093/gji/ggu209

Cited by 16 publications

(9 citation statements)

References 34 publications

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“…Despite the conceptual simplicity of the seismic source inverse problem, methods for the characterization of point-localized sources continue to proliferate, focusing on near-real-time operation and automation (e.g., Bernardi et al, 2004;Cesca et al, 2010;Käufl et al, 2015;Scognamiglio et al, 2009;Vackár et al, 2017), uncertainty quantification (e.g., Mustać & Tkalčić, 2016;Silwal & Tape, 2016;Staehler & Sigloch, 2014, 2017Valentine & Trampert, 2012;Wéber, 2006), the incorporation of 3-D structural models (e.g., Chen et al, 2007;Fichtner & Tkalcic, 2010;Hejrani et al, 2017;Hingee et al, 2011;Hsieh et al, 2014;Liu et al, 2004;Zhu & Zhou, 2016), and the use of new types of seismological observables (e.g., Donner et al, 2016;O'Toole et al, 2012).…”

Section: Developments and Challenges In Seismic Source Inversionmentioning

confidence: 99%

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

Fichtner

Simutė

2018

JGR Solid Earth

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We present a probabilistic seismic point source inversion, taking into account 3‐D heterogeneous Earth structure. Our method rests on (1) reciprocity and numerical wavefield simulations in complex media and (2) Hamiltonian Monte Carlo sampling that requires only a small amount of test models to provide reliable uncertainty information on the timing, location, and mechanism of the source. Using spectral element simulations of 3‐D, viscoelastic, anisotropic wave propagation, we precompute receiver side strain tensors in time and space. This enables the fast computation of synthetic seismograms for any hypothetical source within the volume of interest, and thus a Bayesian solution of the inverse problem. To improve efficiency, we developed a variant of Hamiltonian Monte Carlo sampling. Taking advantage of easily computable derivatives, numerical examples indicate that Hamiltonian Monte Carlo can converge to the posterior probability density with orders of magnitude less samples than the derivative‐free Metropolis‐Hastings algorithm, which we use for benchmarking. Exact numbers depend on observational errors and the quality of the prior. We apply our method to the Japanese Islands region where we previously constrained 3‐D structure of the crust and upper mantle using full‐waveform inversion with a minimum period of 15 s.

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Section: Developments and Challenges In Seismic Source Inversionmentioning

confidence: 99%

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

Fichtner

Simutė

2018

JGR Solid Earth

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“…The synthetic ground motions for the scenario earthquakes were generated through 3D waveform simulation (Zhang and Chen 2006;Hsieh et al 2014). Zhang and Chen (2006) developed a traction-image finite-difference algorithm involving 3D simulation and surface topography.…”

Section: Wave Simulation Through the 3d Finite-difference Schemementioning

confidence: 99%

“…Zhang and Chen (2006) developed a traction-image finite-difference algorithm involving 3D simulation and surface topography. Hsieh et al (2014) applied the algorithm to Taiwan for source inversion. They used a 3-D velocity structure based on the tomography model for the Taiwan region developed by Kuo-Chen et al (2012) and ETOPO1 (Amante and Eakins 2009) for the surface topography which has a resolution of 1-arc-minute (about 1.85 km).…”

Section: Wave Simulation Through the 3d Finite-difference Schemementioning

confidence: 99%

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Synthetic Ground-Motion Simulation Using a Spatial Stochastic Model with Slip Self-Similarity: Toward Near-Source Ground-Motion Validation

Lee

Fong²,

Hsieh³

et al. 2016

Terr. Atmos. Ocean. Sci.

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Near-fault ground motion is a key to understanding the seismic hazard along a fault and is challenged by the ground motion prediction equation approach. This paper presents a developed stochastic-slip-scaling source model, a spatial stochastic model with slipped area scaling toward the ground motion simulation. We considered the near-fault ground motion of the 1999 Chi-Chi earthquake in Taiwan, the most massive near-fault disastrous earthquake, proposed by Ma et al. (2001) as a reference for validation. Three scenario source models including the developed stochastic-slip-scaling source model, meanslip model and characteristic-asperity model were used for the near-fault ground motion examination. We simulated synthetic ground motion through 3D waveforms and validated these simulations using observed data and the ground-motion prediction equation (GMPE) for Taiwan earthquakes. The mean slip and characteristic asperity scenario source models over-predicted the near-fault ground motion. The stochastic-slip-scaling model proposed in this paper is more accurately approximated to the near-fault motion compared with the GMPE and observations. This is the first study to incorporate slipped-area scaling in a stochastic slip model. The proposed model can generate scenario earthquakes for predicting ground motion.

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“…Alternatively, regional waveforms in dense network help resolve rupture directivity via the relative location between hypocenter and the largest slip patch, such as the 2011 M w 5.8 Virginia earthquake and the 2011 M w 5.7 Oklahoma earthquake (Hartzell et al, 2013;Hellweg & Boatwright, 1999;Ide, 2001;Sun & Hartzell, 2014). Chen et al (2005) proposed a theoretical framework of finite moment tensor (FMT) inversion, and this technique was applied to several moderate earthquakes in southwest Taiwan (Hsieh et al, 2014), providing semiautomatic and near-real-time determinations of finite source parameters. Tan and Helmberger (2010) derived the relative source time function of the 2003 Big Bear earthquake sequence with calibration from empirical Green's function (EGF) and then inverted for fault strike, rupture length, and rupture time.…”

Section: Introductionmentioning

confidence: 99%

Resolving Horizontal Rupture Directivity of Moderate Crustal Earthquake in Sparse Network With Ambient Noise Location

2018

JGR Solid Earth

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Earthquake rupture directivity can remove fault plane ambiguity in earthquake moment tensor solutions; thus, it is helpful to improve reliability of shake map and understanding the seismogenic processes. In this paper, we propose an algorithm to resolve the horizontal rupture directivity of moderate crustal earthquakes in two steps. The first step is to determine the two candidate fault planes from focal mechanism inversion. Then, rupture directivity is estimated via the difference between the hypocenter and the centroid location which is constrained on the candidate fault planes. Accurate centroid location is determined with ambient noise location method, in which the noise cross‐correlation functions (NCFs) provide a stable calibration for the path effects. This technique is applied to the 2011 Oklahoma earthquake, and the estimated centroid location is about 2–4 km southwest to the hypocenter, indicating that the mainshock ruptured along the 234° plane for about 4–8 km. The result is consistent with directivity estimation using a foreshock as reference event and also agrees with early aftershock distribution as well as finite fault inversion. More applications to the 2004 Parkfield earthquake and the 2014 Napa earthquake are performed to explore the effectiveness and limitation of this method. This method is helpful for determining rupture directivity of earthquakes in sparse network but requiring one or two nearby stations. Alternatively, temporary stations can be installed in the area of high seismic hazard, then a library of NCFs and path calibrations would be available for rapidly determining rupture directivity of future earthquakes.

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Efficient waveform inversion for average earthquake rupture in three-dimensional structures

Cited by 16 publications

References 34 publications

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

Synthetic Ground-Motion Simulation Using a Spatial Stochastic Model with Slip Self-Similarity: Toward Near-Source Ground-Motion Validation

Resolving Horizontal Rupture Directivity of Moderate Crustal Earthquake in Sparse Network With Ambient Noise Location

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