Estimation of shear-wave interval attenuation from mode-converted data

2012

The Leading Edge

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Attenuation of seismic waves is sensitive to the physical properties of the subsurface and has been observed in vertical seismic profiling (VSP) and reflection data. De et al. (1994) report measurements of the P- and S-wave quality factors from VSP surveys and sonic logs. Klimentos (1995) measures compressional and shear attenuation from sonic logs in sandstone formations with variable oil, water, and gas saturation and observes that [Formula: see text] and [Formula: see text] can be used for pore-fluid discrimination. Maultzsch et al. (2007) evaluate P-wave azimuthal attenuation anisotropy from 3D VSP data acquired over a fractured hydrocarbon reservoir and infer fracture directions from attenuation analysis. Attenuation anisotropy has also been observed in P-wave reflection data (Clark et al., 2009; Vasconcelos and Jenner, 2005). Seismic attenuation is most commonly measured using the spectral-ratio method. Zhu et al. (2007) extend the spectral-ratio method to anisotropic media and apply it to physical modeling data acquired for a transversely isotropic (TI) sample. Computing spectral ratios helps eliminate the source spectrum and can be used to obtain accurate effective and interval attenuation coefficients of P- and S-waves in layered anisotropic media (Behura and Tsvankin, 2009a; Shekar and Tsvankin, 2011).

mentioning

confidence: 99%

Anisotropic attenuation analysis of crosshole data generated during hydraulic fracturing

Shekar

2012

The Leading Edge

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“…requires the subsurface structure to be relatively simple. If the overburden is laterally homogeneous and has a horizontal symmetry plane, anisotropic attenuation coefficients of P-and S-waves can be estimated without knowledge of the velocity field using the layer-stripping method of Behura and Tsvankin (2009a) and Shekar and Tsvankin (2011). It should be mentioned that the attenuation-layer stripping method yields attenuation coefficients corresponding to a given source-receiver offset or group angle.…”

Section: Basic Elements Of Inversion Methodologymentioning

confidence: 99%

“…Since their method operates in the τ − p domain, it is restricted to laterally homogeneous target layers. Shekar and Tsvankin (2011) extend the attenuation layer-stripping method of Behura and Tsvankin (2009a) to mode-converted (PS) waves with the goal of estimating the interval S-wave attenuation coefficient. By identifying PP and PS events with shared ray segments and applying the PP+PS=SS method, they first perform kinematic construction of pure shear (SS) events in the target layer and overburden.…”

Section: Introductionmentioning

confidence: 99%

Attenuation analysis for heterogeneous transversely isotropic media

Shekar

SEG Technical Program Expanded Abstracts 2012

2012

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Attenuation coefficients obtained from seismic data may provide sensitive attributes for reservoir characterization and increase the robustness of AVO (amplitude variation with offset) analysis. Here, we present an algorithm for ray tracing in attenuative anisotropic media based on the methodology ofCervený and Psencik. Both kinematic and dynamic ray tracing are carried out in an elastic reference medium, with the attenuation terms incorporated as perturbations along the ray. Numerical examples for smoothly varying transversely isotropic (TI) media demonstrate the accuracy of the method. The dynamic ray-tracing technique provides an efficient forward-modeling operator that can be used in the inversion for anisotropic attenuation. We outline an inversion methodology for estimating attenuation coefficients in 2D heterogeneous anisotropic media. A necessary prerequisite for accurate attenuation analysis is reconstruction of the heterogeneous velocity field. If the subsurface can be approximated by a piecewise-factorized VTI (TI with a vertical axis of symmetry) medium, the anisotropic velocity model can be built using the migration velocity analysis algorithm proposed by Sarkar and Tsvankin. Attenuation coefficients in each factorized block can then be estimated using gradient-based inversion that employs dynamic ray tracing.

“…Actual and estimated attenuation parameters for the two-layer model from Figure 4. The quality factor Q S0 was not estimated in this test because it requires special processing of mode-converted data (see Shekar and Tsvankin, 2011). We process reflections in the offset range from 30 m to 840 m with an increment of 90 m and estimate the corresponding phase angles from the group angles using a linearized relationship (Tsvankin, 2012).…”

Section: Velocity Dispersionmentioning

confidence: 99%

Time-domain finite-difference modeling for attenuative anisotropic media

Bai

2016

GEOPHYSICS

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Accurate and efficient modeling of seismic wavefields that accounts for both attenuation and anisotropy is essential for further development of processing methods. Here, we present a 2D time-domain finite-difference algorithm for generating multicomponent data in viscoelastic transversely isotropic media with a vertical symmetry axis (VTI). Within the framework of the generalized standard linear solid (GSLS) model, the relaxation function is expressed through the τ-parameters (which quantify the difference between the stress and strain relaxation times) defined for anisotropic media. This approach produces nearly constant values of all components of the quality-factor matrix within a specified frequency band. The developed algorithm is based on a set of anisotropic viscoelastic wave equations parameterized by memory variables. Synthetic examples for TI models with different structural complexity confirm the accuracy of the proposed scheme and illustrate the influence of attenuation and attenuation anisotropy on multicomponent wavefields.