A stable and efficient approach of inverse Q filtering

By Yanghua Wang. 2002

322 citations recorded by the source corpus.

Stability and efficiency are two issues of general concern in inverse Q filtering. This paper presents a stable, efficient approach to inverse Q filtering, based on the theory of wavefield downward continuation. It is implemented in a layered manner, assuming a depth-dependent, layered-earth Q model. For each individual constant Q layer, the seismic wavefield recorded at the surface is first extrapolated down to the top of the current layer and a constant Q inverse filter is then applied to the current layer. When extrapolating within the overburden, instead of applying wavefield downward continuation directly, a reversed, upward continuation system is solved to obtain a stabilized solution. Within the current constant Q layer, the amplitude compensation operator, which is a 2-D function of traveltime and frequency, is approximated optimally as the product of two 1-D functions depending, respectively, on time and frequency. The constant Q inverse filter that compensates simultaneously for phase and amplitude effects is then implemented efficiently in the Fourier domain.

Subfields: Geophysics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/eb3e3f6c6d76f7e7ce70828d72914c6d384208cd

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In Geophysics

In Ocean Engineering

Citations in the corpus

L1−2 minimization for exact and stable seismic attenuation compensation (2018, methodology): “(ii) Estimate Q directly from the Gabor spectra via attenuationbased or compensation-based Q analysis (Wang 2004), where the five reference Q curves are first estimated.”
Time-varying wavelet estimation and deconvolution by kurtosis maximization (2008, methodology): “The described method can also be used as an alternative to deterministic inverse-Q deconvolution approaches Robinson, 1979; BickelandNatarajan,1985;HargreavesandCalvert,1991;Y. Wang, 2002 .”
Q analysis on reflection seismic data (2004, methodology): “[25] This time-variant Q function is used to design an inverse Q filter, which is then applied to the seismic section in Figure 3. The resultant seismic section, after stabilized inverse Q filtering [ Wang, 2002; Guo and Wang, 2004], is plotted in Figure 5, which shows true amplitude variation of t”
Q-compensated reverse-time migration (2014, methodology): “Early attempts to mitigate these attenuation effects applied inverse Q filtering to seismic trace data (e.g., Bickel and Natarajan, 1985; Hargreaves and Calvert, 1991; Wang, 2002).”
The robustness of seismic attenuation measurements using fixed- and variable-window time-frequency transforms (2009, methodology): “Finally, once attenuation is measured, it is possible o mitigate the resolution loss by applying processes such as nverse-Q filtering Wang, 2002 to aid with structural interpretaions Kaderali et al., 2007 , amplitude-variation-with-offset AVO nalysis Luh, 1993 .”
Bandwidth enhancement: Inverse Q filtering or time-varying Wiener deconvolution? (2012, methodology): “Wang (2002) combines this with a threshold similar to equation 11.”