Abstract
The waveform inversion method is applied—using synthetic ocean-bottom seismometer (OBS) data—to study oceanic crust structure. A niching genetic algorithm (NGA) is used to implement the inversion for the thickness and P-wave velocity of each layer, and to update the model by minimizing the objective function, which consists of the misfit and cross-correlation of observed and synthetic waveforms. The influence of specific NGA method parameters is discussed, and suitable values are presented. The NGA method works well for various observation systems, such as those with irregular and sparse distribution of receivers as well as single receiver systems. A strategy is proposed to accelerate the convergence rate by a factor of five with no increase in computational complexity; this is achieved using a first inversion with several generations to impose a restriction on the preset range of each parameter and then conducting a second inversion with the new range. Despite the successes of this method, its usage is limited. A shallow water layer is not favored because the direct wave in water will suppress the useful reflection signals from the crust. A more precise calculation of the air-gun source signal should be considered in order to better simulate waveforms generated in realistic situations; further studies are required to investigate this issue.
Highlights
Seismic waveform inversion is a technique to extract quantitative information on subsurface structure by fitting the synthetic seismograms with that of observation
Through comparison with a travel-time-based method, fullwaveform inversion can improve the resolution of the model as it uses both the amplitude and phase information of various seismic phases contained in seismograms
Waveform inversion has Earthq Sci (2016) 29(4):203–213 been conducted at several regions to extract layered continental crustal and upper-mantle structure using the data recorded from local seismic networks with global optimization methods (Abdelwahed and Zhao 2014; Chang and Baag 2006; Li and Lei 2014a, b; Li et al 2007, 2012)
Summary
Seismic waveform inversion is a technique to extract quantitative information on subsurface structure by fitting the synthetic seismograms with that of observation. For regions where subsurface structure can be approximated by a layered model, global optimization methods, such as genetic algorithm and simulated annealing, can be applied to full-waveform inversion to improve its efficiency and convergence (Sen and Stoffa 2013). Waveform inversion has Earthq Sci (2016) 29(4):203213 been conducted at several regions to extract layered continental crustal and upper-mantle structure using the data recorded from local seismic networks with global optimization methods (Abdelwahed and Zhao 2014; Chang and Baag 2006; Li and Lei 2014a, b; Li et al 2007, 2012). The influence and performance under different observation systems of some key parameters in the NGA method are investigated, and a strategy is proposed to accelerate the convergence rate without increasing the computational complexity This strategy is verified through comparative tests
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