Ray-based Tomography for Q Estimation and Q Compensation in Complex Media

Cavalca, M.; Moore, Ian D.; Zhang, L.; Ng, Swee Leng; Fletcher, Richard; Bayly, Martin

doi:10.3997/2214-4609.20149151

Cited by 14 publications

(5 citation statements)

References 8 publications

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“…To mitigate the influence of source radiation patterns, Zhou (2009, 2010) inverted the Q distribution by using the ratio of amplitudes of neighbouring rays. Cavalca et al (2011) used tomography to estimate the Q distribution of the subsurface structure and compensate for seismic absorption in depth-migrated images. Here, we propose an improved method by eliminating source effect.…”

Section: Tomographic Inversion Of Near-surface Absorptionmentioning

confidence: 99%

Frequency-dependent near-surface Q factor measurements via a cross-hole survey

Zheng

Zhang

et al. 2015

Journal of Applied Geophysics

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Section: Tomographic Inversion Of Near-surface Absorptionmentioning

confidence: 99%

Frequency-dependent near-surface Q factor measurements via a cross-hole survey

Zheng

Zhang

et al. 2015

Journal of Applied Geophysics

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“…This results in distortions to the phase and amplitude information at the target level which can lead to poor identification and interpretation, errors in amplitude versus offset analyses and inaccuracies in inverting to rock properties. Q tomography and Q imaging address the Earth's attenuation effects by first deriving a spatially and temporally variant 3D interval 1/Q model using ray-based reflection tomography techniques and then incorporating this model within a migration operator (Cavalca et al, 2011).…”

Section: Theorymentioning

confidence: 99%

FWI and Q-Tomography on broadband processed data - SE Asia case study

Menzel-Jones¹,

Petton²,

Anstey³

et al. 2015

Proceedings

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SUMMARYImaging below shallow gas bodies is one geophysical challenge encountered in offshore Southeast Asia basins. There are two key components in addressing this challenge: 1) the derivation of an accurate, highresolution, geologically consistent velocity model and 2) compensating for the loss in signal strength and frequency bandwidth due to absorption of the signal as it propagates through the gas bodies.In this study, we present the application of FWI and Q tomography to a shallow-water, shallow-gas dataset from offshore Southeast Asia. We demonstrate the successful ability of FWI and Q tomography to resolve the low P-wave velocities and high attenuation of shallow gas bodies and subsequently compensate for the complex kinematics and absorption during depth migration.

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“…High resolution is a key requirement of seismic processing for the detection of subtle hydrocarbon reservoirs (Hale, 1981, 1982; Ferber, 2005; Cavalca et al ., 2011; Van der Baan, 2012). However, the resolution of original field data does not usually meet the above requirement due to the anelasticity of the subsurface medium and the influence of the seismic wavelet.…”

Section: Introductionmentioning

confidence: 99%

Warped mapping–based blind deconvolution for resolution improvement

Liu

2022

Geophysical Prospecting

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Owing to the influence of absorption and scattering, the components of seismic waves, especially those with higher frequencies, always suffer amplitude attenuation and phase distortion during their propagation through the earth. Nonstationary blind deconvolution takes such attenuations into account for prestack seismic data. This not only compensates for attenuation‐induced energy loss but also simultaneously addresses the energy loss associated with the reflectivity series and wavelet. Additionally, nonstationary blind deconvolution can greatly improve the resolution of seismic data. However, prestack nonstationary blind deconvolution is difficult to implement because it is not easy to estimate the attenuation function of prestack seismic data unless the quality factor of the Earth is assumed to be constant. In this regard, we introduced a nonstationary blind deconvolution method for prestack gathering. First, we used warped mapping to calculate the attenuation function of the prestack data. Then, we incorporated the attenuation function into the nonstationary sparse spike deconvolution based on Toeplitz‐sparse matrix factorization for reflectivity series and wavelet estimation. The proposed method is velocity‐independent and can be adapted to the time‐varying Q model. To validate its stability and effectiveness, numerical and real data examples were adopted. The results show that the proposed method provides a straightforward routine for the estimation of prestack reflectivity coefficients for further processing and inversion.

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Ray-based Tomography for Q Estimation and Q Compensation in Complex Media

Cited by 14 publications

References 8 publications

Frequency-dependent near-surface Q factor measurements via a cross-hole survey

Frequency-dependent near-surface Q factor measurements via a cross-hole survey

FWI and Q-Tomography on broadband processed data - SE Asia case study

Warped mapping–based blind deconvolution for resolution improvement

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