Estimation of quality factor                                          <i>Q</i> from pre‐stack CMP records using EPIFVO analysis

Zhao, Jing; Gao, Jinghuai; Wang, Da Xing; Mengli, Zhang

doi:10.1190/1.3627562

Cited by 3 publications

(2 citation statements)

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“…In seismic exploration, we can also use the quality factor Q to study the attenuation of seismic waves, which represents the ratio of the total energy of the elastic wave to the energy loss in a period, which is defined as Q � 2π(E/ΔE) [17,18]. Besides, we set the inverse of Q as the specific attenuation η a , and η a is proportional to the medium density ρ, porosity φ, and viscosity ψ but inversely proportional to the penetration ξ [18,19].…”

Section: Absorptionmentioning

confidence: 99%

A Propagation Loss Coefficient Model of Low-Frequency Elastic Wave in Coal Strata Set

Guo

Liu

et al. 2020

Mathematical Problems in Engineering

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Elastic waves cause energy loss during the transmission of coal measures. These losses include propagation loss, dielectric absorption loss, scattering loss, and frequency migration loss. The absorption loss is mainly caused by the inelastic absorption. The scattering loss is caused by the uneven heat absorption in the formation. The frequency shift loss is caused by the piezoelectric effect of coal-bearing formations and the intermodulation of different frequency signals. After considering the influence factors of the coal seam structure, this paper presents a model of low-frequency elastic waves loss coefficient. The paper proposed the loss coefficient of the elastic wave in the coal measure strata by considering two main attenuation mechanisms: intrinsic absorption and scattering. This paper theoretically studied the effects of the model parameters such as density, porosity, particle size, and wave frequency on the loss of wave energy using COMSOL simulation. Besides, the comparison of MATLAB simulation results shows that the simulation results produced by the model proposed in this paper are similar to the models embedded in COMSOL. This work can be applied to coal, oil, and gas exploration and is also helpful to study the mechanisms of wave attention on the low-frequency band.

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Section: Absorptionmentioning

confidence: 99%

A Propagation Loss Coefficient Model of Low-Frequency Elastic Wave in Coal Strata Set

Guo

Liu

et al. 2020

Mathematical Problems in Engineering

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“…Futterman (1962) and Kjartansson (1979) have proposed the expression of amplitude attenuation and phase velocity dispersion for description of the earth Q-filter. In order to remove the effect of the earth Qfilter, scholars have developed many methods for Q value inversion using VSP data (Hauge, 1981;Stainsby and Worthington, 1985;Badri and Mooney, 1987;Tonn, 1991;Xu C and R Stewart, 2006;Gao and Yang, 2007;Gao et al, 2008;Blias, 2012) or surface seismic data (Yan and Liu, 2009;Wang, 2011;Zhao et al, 2013), and then use it for inverse Q-filter (Hargreaves and Calvert 1991;Wang, 2002Wang, , 2003Wang, , 2006Yao et al, 2003;Liu et al, 2013;Chen et al, 2014) with amplitude and phase compensation. Inverse Q-filter amplitude compensation for seismic resolution enhancement is widely recognized and applied by the industry, and lots of papers have been published to share the good result for actual seismic data; while the effect of inverse Q-filter phase compensation (Bano, 1996) for velocity dispersion correction to actual seismic data is rarely published.…”

Section: Introductionmentioning

confidence: 99%

Seismic Wave Dispersion Effects and Inverse Q‐Filter Phase Compensation

Zhang

Wang

et al. 2014

Chinese J of Geophysics

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Based on the expression of amplitude attenuation and phase velocity dispersion proposed by Futterman, and considering the well-seismic matching, we derived the expression of seismic wave velocity dispersion between phase velocity and amplitude spectrum for the following four cases: without inverse Q-filter, with only inverse Q-filter amplitude compensation, with only inverse Q-filter phase compensation, with inverse Q-filter phase and amplitude compensation. We explained the necessity of inverse Q-filter phase compensation in theory. Through the zero-offset VSP data example of dynamite and vibroseis source with the same acquisition geometry, we verified the velocity dispersion expression derived in this paper. Through the example of well-seismic calibration, we further illustrated that inverse Q-filter phase compensation can effectively eliminate seismic wave velocity dispersion, enhance well-seismic matching, finally improve the reliability of surface seismic data.

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