Simulating three-dimensional seismograms in 2.5-dimensional structures by combining two-dimensional finite difference modelling and ray tracing

Miksat, J.; Müller, Thilo; Wenzel, Friedemann

doi:10.1111/j.1365-246x.2008.03800.x

Cited by 18 publications

(9 citation statements)

References 29 publications

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“…However, note that on one seismogram, p = p(t) is different for the various seismic phases. Miksat et al (2008) showed that using ray tracing to calculate the F factor for each phase, line source seismogram can be corrected to obtain the point source seismogram, phase by phase. However, ray tracing is complicated and processing phase by phase is cumbersome.…”

Section: -D Spreadingmentioning

confidence: 99%

Global synthetic seismograms using a 2-D finite-difference method

Helmberger

Clayton

et al. 2014

Geophysical Journal International

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finite-difference (FD) synthetics, which fill the gap between fast 1-D analytic synthetics and time-consuming full 3-D synthetics in our ability to model seismograms, have been used in many studies. We address several issues involving 2-D FD methods in generating global synthetic seismograms. These include: (1) interfacing point source excitation for earthquakes with 2-D FD methods; (2) out-of-plane spreading corrections and (3) reducing the spherical Earth to the flattened models. The first issue is tackled using two methods, a 'transparent source box' approach and a moment tensor excitation approach, where each has its own advantages. Moreover, our 'source box' excitation does not have the late-time drift problem that occurred in previous studies. The out-of-plane geometric spreading correction is accounted for by estimating the ray parameter and applying a post-simulation filter to 2-D synthetics. Finally, parameters of the Earth-flattening transformation are discussed and validated. The effectiveness of this method is demonstrated by comparing our synthetics with frequency-wavenumber summation, normal-mode and 3-D spectral-element synthetics.

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Section: -D Spreadingmentioning

confidence: 99%

Global synthetic seismograms using a 2-D finite-difference method

Helmberger

Clayton

et al. 2014

Geophysical Journal International

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“…All spatial and temporal modelling parameters are listed in Table 1. The source is implemented by adding the stress glut (Olsen et al 2006; Miksat et al 2008) to the source gridpoint. The source time function of the added stresses for the considered M L = 3.8 earthquake is described by a Herrman window with a half width of 0.5 s. The moment magnitude, which is needed to calculate the stress glut, is obtained from local magnitude by the empirical relationship of Lin & Lee (2008) for earthquakes in Taiwan.…”

Section: Numerical Modellingmentioning

confidence: 99%

Numerical modelling of ground motion in the Taipei Basin: basin and source effects

Miksat¹,

Wen

Wenzel³

et al. 2010

Geophysical Journal International

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S U M M A R YThe Taipei basin in northern Taiwan is located in a high seismicity region and was affected by several earthquakes in the past (M L = 7.3 on 1909 April 15; M L = 6.8 on 1986 November 15; the Chi-Chi M L = 7.3 earthquake on 1999 September 21 and M L = 6.8 on 2002 March 31). The main characteristic of the Taipei basin is its complex shape with a deep western and shallow eastern part. The uppermost Sungshan formation with its low shear wave velocities (90-200 m s −1 ) is also a distinct feature of the basin. Based on the large data base of earthquake records obtained from the Taiwan Strong Motion Instrumentation Program network, many studies on ground motion within the Taipei basin exist. However, the influence of the various subsurface structures on the observed ground motions as well as the variability of ground motion with respect to earthquake location is not fully understood. We apply a 3-D finitedifference method to simulate wave propagation up to 1 Hz for a small earthquake close to the basin in order to resolve these open questions. By varying source and structural parameters, we explore the variability of ground motion.Our study includes a subsurface model that is based on recent studies on the basin structure and on the crustal structure of Taiwan. From our simulations we find a good fit between simulated and observed waveforms and peak ground accelerations for the considered small earthquake near the basin. We also explore the influence of fault plane orientation, hypocentre location, deep basin structure and soft soil surface layers of the Sungshan formation by varying the subsurface structure and earthquake position. Our studies reveal that the basin structure produces an amplification factor of about 4 compared to hard rock conditions. Additionally, the soft soil Sungshan formation produce amplification of a factor of 2. This results in a maximum amplification of the basin structure of about 8, which is in good comparison with amplification values larger than 5 found from the analysis of observed earthquakes. These values clearly exceed the amplification values of about 2-3 obtained when applying standard 1-D site effect analysis.Our simulations for different earthquake positions show that ground motion depends strongly on earthquake location and fault orientation. Therefore, the application of average values of spectral amplification obtained from the analysis of recorded data from distant earthquakes with different azimuths and fault planes may significantly underestimate future ground motions of possible earthquakes on known faults close to the Taipei basin. The simulation of a small earthquake near the Taipei basin presented in this study will help to set up adequate simulation parameters for a possible large earthquake close to the Taipei basin. Such a simulation of a scenario earthquake close to the Taipei basin would allow to significantly improve hazard assessment as no observations of strong earthquakes in the vicinity of the basin exist.

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“…where

ω

is the angular frequency, the quantity

σ

is defined as

σ = c r,

c is the acoustic wave speed, and r is the distance. However, the asymptotic filter transfer function is derived from a half‐space, which is an approximation to our case, such an approximation has been applied to the inhomogeneous media with acceptable results (Miksat, Müller and Wenzel ; Auer et al . ).…”

Section: Sichuan Data Applicationsmentioning

confidence: 99%

Applying joint traveltime and waveform inversion to image the Sichuan Basin, China

Zhang

2017

Near Surface Geophysics

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We apply a joint first-arrival traveltime and early-arrival waveform inversion method to image complex near-surface structures in the Sichuan Basin, China. The area includes rugged topography and large near-surface velocity variations. Due to the near-surface effects, it is difficult to produce highquality reflection images of the deep subsurface. First-arrival traveltime tomography is often applied for near-surface imaging, but the results may not be sufficiently accurate because of ray assumptions and the limited traveltime information. Waveform inversion should allow complex structures to be resolved; however, it may fall into local minima because of cycle skipping issues and may also produce artefacts in very shallow areas that are associated with rugged topography. Therefore, we combine the advantages of the two methods and mitigate their problems by performing joint inversion of the two types of data. We demonstrate the effectiveness of the joint inversion method using synthetic and real data from Sichuan, China. In the real data example, we compare the velocity models resolved from waveform inversion alone with those resolved from the joint inversion. We calculate long-wavelength static corrections and apply them to the data processing. The common midpoint stacking results show that the joint inversion method produces a more effective statics solution. 1995). FWI can resolve the details of a velocity model because it is based on the waveform information; thus, FWI should be able to image geologically complex areas (Tarantola 1984;Sheng 2006). The FWI solution should also provide a higher resolution velocity image than traveltime tomography (Gauthier, Virieux and Tarantola 1986).However, the objective function of waveform inversion is highly nonlinear and may include many local minima. The inversion may fall into a local minima due to cycle skipping between the predicted and observed data (Virieux and Operto 2009). Several methods have been proposed recently to overcome or mitigate the cycle skipping issue. Ma and Hale (2013) proposed a hybrid waveform inversion method in which wave-equation reflection traveltime inversion was used to update the lowwavenumber component, and FWI was employed to update the high-wavenumber details of the velocity model. Wu, Luo and Wu (2013) developed a waveform envelope inversion method to utilise low-frequency information from the data. The envelope inversion method can avoid the cycle skipping problem and retrieve the long-wavelength background velocity model for FWI. Warner and Guasch (2014) proposed adaptive waveform inversion, which reformulates the objective functions in terms of matching filters. The difference between the observed and predicted data is projected onto the time lag of the filter. Other

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Simulating three-dimensional seismograms in 2.5-dimensional structures by combining two-dimensional finite difference modelling and ray tracing

Cited by 18 publications

References 29 publications

Global synthetic seismograms using a 2-D finite-difference method

Global synthetic seismograms using a 2-D finite-difference method

Numerical modelling of ground motion in the Taipei Basin: basin and source effects

Applying joint traveltime and waveform inversion to image the Sichuan Basin, China

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