Multiscale adjoint waveform tomography for surface and body waves

Abstract

International audienceWe have developed a wavelet-multiscale adjoint scheme for the elastic full-waveform inversion of seismic data, including body waves (BWs) and surface waves (SWs). We start the inversion on the SW portion of the seismograms. To avoid cycle skipping and reduce the dependence on the initial model of these dispersive waves, we commence by minimizing an envelope-based misfit function. Subsequently, we proceed to the minimization of a waveform-difference (WD) metric applied to the SWs only. After that, we fit BWs and SWs indiscriminately using a WD misfit metric. In each of these three steps, we guide the iterative inversion through a sequence of nested subspace projections in a wavelet basis. SW analysis preserves a wealth of near-surface features that would be lost in conventional BW tomography. We used a toy model to illustrate the dispersive and cycle-skipping behavior of the SWs, and to introduce the two ways by which we combat the nonlinearity of waveform inversions involving SWs. The first is the wavelet-based multiscale character of the method, and the second the envelope-based misfit function. Next, we used an industry synthetic model to perform realistic numerical experiments to further develop a strategy for SW and joint SW as well as BW tomography. The effect of incorrect density information on wave-speed inversions was also evaluated. We ultimately formalize a flexible scheme for full-waveform inversion based on adjoint methods that includes BWs and SWs, and also considers P- and S-wave speeds, as well as density. Our method is applicable to waveform inversion in exploration geophysics, geotechnical engineering, regional, and global seismology.Read More: http://library.seg.org/doi/10.1190/geo2014-0461.

Skeletonized wave equation of surface wave dispersion inversion

“…Results with synthetic data showed this to be a robust and efficient method for reconstructing the S-velocity model at the near surface. Another surfacewave inversion strategy is proposed by (Yuan et al, 2015), who developed a wavelet multi-scale adjoint method which combined surface waves and body waves. Synthetic tests showed that this approach can avoid cycle skipping for some models .…”

Wave-equation dispersion inversion

“…Inverting surface waves for the S-wave velocity model falls into two categories: (1) the classical method of inverting dispersion curves (Evison et al 1959;Park et al 1998;Xia 2014) for a 1-D layered medium, and (2) full waveform inversion (Groos et al 2014;Solano et al 2014;Dou & Ajo-Franklin 2014;Bohlen et al 2015;Yuan et al 2015) for 2-D and 3-D media. The classical method accurately inverts for a 1-D S-wave velocity model, but becomes less accurate with increasing lateral heterogeneity in the subsurface.…”

The imprint of crustal density heterogeneities on regional seismic wave propagation

“…However, depending on the tomographic resolution and data quality, the biases may be larger than the error bars. A qualitative look at the detrimental effects that incorrect density information has on the wave speed models has recently been shown by Yuan et al (2015).…”