Layer-stripping full waveform inversion with damped seismic reflection data

Abstract

Full waveform inversion (FWI) directly minimizes errors between synthetic and observed data. For the surface acquisition geometry, reflections generated from deep reflectors are sensitive to overburden structure, so it is reasonable to update the macro velocity model in a top-to-bottom manner. For models dominated by horizontally layered structures, combination of offset/time weighting and constant update depth control (CUDC) is sufficient for layer-stripping FWI. CUDC requires ray tracing to determine reflection traveltimes at a constant depth. As model complexity increases, the multi-path effects will have to be considered. We developed a new layer-stripping FWI method utilizing damped seismic reflection data, which does not need CUDC and ray tracing. Numerical examples show that effective update depth (EUD) can be controlled by damping constants even in complex regions and the inversion result is more accurate than conventional methods. KEY WORDS: full waveform inversion, velocity model building, layer-stripping strategy, damped wave equation, sensitivity analysis.

Integrated assessment on the implementation of sustainable heat technologies in the built environment in Harbin, China

“…The optimization is often trapped into local minima when FWI is performed from a very poor starting model, using the data without long offset, lowfrequency information. A number of solutions to mitigate such difficulties have been proposed, using multiscale strategies from low to high frequencies (Bunks et al, 1995), layer stripping from long to near offset (Bian and Yu, 2011), the modifications of the misfit functions based on cross-correlation (Luo and Schuster, 1991), deconvolution (Warner and Guasch, 2016) or optimal transport distance . These ideas can be explored easily within the framework of SMIwiz, but out of the scope of this work.…”

Time‐damping Full Waveform Inversion of Multi‐dominant‐frequency Wavefields

“…It can be seen from the inversion results that the full-wave inversion method proposed in this paper can not only adapt to the seismic data missing low-frequency components, but also has good adaptability to the velocity model which has strong contrast, and is an improvement of the existing time damping full waveform inversion method (Yoon et al, 2003;Wang & Rao, 2009;Bian & Yu, 2011;Kwak et al, 2013;Chen et al, 2015) and the second order time integral wave field full waveform inversion method (Chen & Chen et al, 2016).…”

“…However, the effect of these multi-scale inversion methods is limited due to the lack of low-frequency components and the weak energy of the components which are far away from the main frequency components. In order to reduce the influence of travel time mismatch in the shallow part of model inversion and its accumulation effect on the deep part inversion, layer peeling, time damping and time windowing are proposed (Yoon et al, 2003;Wang & Rao, 2009;Bian & Yu, 2011;Kwak et al, 2013;Chen et al, 2015). These methods are also difficult to apply in practice due to the lack of low frequency components.…”