Comparison of source-independent methods of elastic waveform inversion

Abstract

In this paper, we investigate several source-independent methods of nonlinear full-waveform inversion of multicomponent elastic-wave data. This includes iterative estimation of source signature (IES), standard trace normalization (STN), and average trace normalization (ATN) inversion methods. All are based on the finite-element method in the frequency domain. One synthetic elastic crosshole model is used to compare the recovered images with all these methods as well as the known source signature (KSS) inversion method. The numerical experiments show that the IES method is superior to both STN and ATN methods in two-component, elastic-wave inversion in the frequency domain when the source signature is unknown. The STN and ATN methods have limitations associated with near-zero amplitudes (or polarity reversals) in traces from one of the components, which destroy the energy balance in the normalized traces and cause a loss of frequency information. But the ATN method is somewhat superior to the STN method in suppressing random noise and improving stability, as the developed formulas and the numerical experiments show. We suggest the IES method as a practical procedure for multicomponent seismic inversion.

Source-independent elastic waveform inversion using a logarithmic wavefield

“…Xu et al (2006) used only random-noise synthetic data to compare the SIWI with the SEWI, and they concluded that the SEWI is more robust than the SIWI for the random-noise synthetic data. In this study, we applied two logarithmic waveform inversion algorithms (the SILWI and the SELWI) to the random-noise and hyperbolic coherent-noise data.…”

“…Although source wavelet information is necessary for successful waveform inversion, it is not easy to estimate the exact source wavelet when the exact subsurface parameters are unknown (Pratt, 1999). To avoid source estimation, Lee and Kim (2003), Zhou and Greenhalgh (2003), Choi et al (2005), and Xu et al (2006) developed the sourceindependent waveform inversion algorithms (SIWI). All of these researchers normalized the wavefields by the reference wavefield to remove the effects of the source wavelet and used the normalized wavefields to construct the misfit function.…”

Ore-body imaging by crosswell seismic waveform inversion: A case study from Kambalda, Western Australia

“…Further details are given in Xu et al (2006). The acoustic-wave finite-element equation in the frequency domain can be expressed as (Marfurt, 1984):…”

“…Assuming that the model velocities are close to the true subsurface distribution, the complex-valued source scalar f(ω) can be solved as follows Xu et al, 2006):…”

Methods for source-independent Q estimation from microseismic and crosswell perforation shot data in a layered, isotropic viscoelastic medium

“…These algorithms are driven by convolution-or deconvolution-based misfit functions using reference synthetic and observed data. Although Xu et al (2006) have shown for some cases in an elastic medium that SIFWI yields results inferior to the results obtained by FWI with estimation of a source function, the capabilities of SIFWI for Q estimation are still unclear.…”