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

Shigapov, R.; Kashtan, Boris; Droujinine, Alexander; Mulder, W.A.

doi:10.1190/segam2013-0948.1

Cited by 3 publications

(5 citation statements)

References 27 publications

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“…) and so‐called source‐independent waveform inversion (SIWI) (Choi and Alkhalifah ; Shigapov et al . ). Due to the trade‐offs between the source signature and attenuation, SIWI is better suited for attenuation analysis.…”

Section: Introductionmentioning

confidence: 97%

“…There are two main strategies to account for the influence of the source wavelet: joint inversion for the source signal and medium parameters Sun et al 2014) and so-called source-independent waveform inversion (SIWI) (Choi and Alkhalifah 2011;Shigapov et al 2013). Due to the trade-offs between the source signature and attenuation, SIWI is better suited for attenuation analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the trade-offs between the source signature and attenuation, SIWI is better suited for attenuation analysis. Shigapov et al (2013) compare three types of source-independent misfit functions in the frequency domain designed to remove the influence of the source wavelet from attenuation estimation. Their synthetic test for microseismic and crosswell data from a layered isotropic viscoelastic medium shows that the best inversion results are obtained with the convolution-based objective function.…”

Section: Introductionmentioning

confidence: 99%

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Source‐independent waveform inversion for attenuation estimation in anisotropic media

Bai

Tsvankin

2019

Geophysical Prospecting

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In previous publications, we presented a waveform‐inversion algorithm for attenuation analysis in heterogeneous anisotropic media. However, waveform inversion requires an accurate estimate of the source wavelet, which is often difficult to obtain from field data. To address this problem, here we adopt a source‐independent waveform‐inversion algorithm that obviates the need for joint estimation of the source signal and attenuation coefficients. The key operations in that algorithm are the convolutions (1) of the observed wavefield with a reference trace from the modelled data and (2) of the modelled wavefield with a reference trace from the observed data. The influence of the source signature on attenuation estimation is mitigated by defining the objective function as the ℓ2‐norm of the difference between the two convolved data sets. The inversion gradients for the medium parameters are similar to those for conventional waveform‐inversion techniques, with the exception of the adjoint sources computed by convolution and cross‐correlation operations. To make the source‐independent inversion methodology more stable in the presence of velocity errors, we combine it with the local‐similarity technique. The proposed algorithm is validated using transmission tests for a homogeneous transversely isotropic model with a vertical symmetry axis that contains a Gaussian anomaly in the shear‐wave vertical attenuation coefficient. Then the method is applied to the inversion of reflection data for a modified transversely isotropic model from Hess. It should be noted that due to the increased nonlinearity of the inverse problem, the source‐independent algorithm requires a more accurate initial model to obtain inversion results comparable to those produced by conventional waveform inversion with the actual wavelet.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Source‐independent waveform inversion for attenuation estimation in anisotropic media

Bai

Tsvankin

2019

Geophysical Prospecting

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“…To overcome this restriction, we propose to use viscoelastic full waveform inversion with a source-independent misfit function. Based on the spectral ratios from the previous section we can construct logarithmic and deconvolution-based misfit functions (Shigapov et al, 2013). Here we restrict ourselves to a convolution-based misfit function,…”

Section: Source-independent Viscoelastic Full Waveform Inversion In Tmentioning

confidence: 99%

“…Usually, the source wavelet is not well known, so we focus on Q estimation techniques that can handle this problem. Earlier, we revisited the spectral ratio method and checked the capabilities of source-independent full waveform inversion in a layered viscoelastic medium under the far-field assumption (Shigapov et al, 2013). However, sometimes Q estimation in the near field of a source is required.…”

Section: Introductionmentioning

confidence: 99%

Effects of the Near Field on Source-independent Q Estimation

Shigapov¹,

Kashtan²,

Droujinine³

et al. 2013

Proceedings

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SUMMARYWe consider the problem of Q estimation from microseismic and from perforation shot data. Assuming that the source wavelet is not well known, we focused on the spectral ratio method and on sourceindependent viscoelastic full waveform inversion. We derived 3-D near-field approximations of monopole and dipole Green's tensors in a homogeneous viscoelastic medium. We show that the spectral ratio method is not applicable in the near-field region, but a two-step source-independent viscoelastic full waveform inversion strategy applied to synthetic data can first recover the purely elastic velocities and then provide an attenuation estimate.

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