Lamé parameters inversion based on elastic impedance and its application

Wang, Baoli; Yin, Xingyao; Zhang, Fanchang

doi:10.1007/s11770-006-0026-z

Cited by 20 publications

(2 citation statements)

References 6 publications

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“…Moreover, it is a challenging task to extract reasonable space variant wavelets of each incident angle at different azimuths used for AVAZ inversion. This can be addressed by azimuthal elastic impedance (EI) extended from the concept of EI (Connolly 1999;Whitcombe 2002;Wang et al 2006;Yin et al 2013;Zong et al 2013Zong et al , 2016Mozayan et al 2018). In the last decades, there were abundant studies on the application of azimuthal EI in anisotropic inversion (Martins 2006;Chen et al 2014bChen et al , 2017bPan et al 2018b;Pan and Zhang 2019).…”

Section: Introductionmentioning

confidence: 99%

Azimuthal elastic impedance-based Fourier coefficient variation with angle inversion for fracture weakness

Zhang

Pan

et al. 2020

Pet. Sci.

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Quantitative inversion of fracture weakness plays an important role in fracture prediction. Considering reservoirs with a set of vertical fractures as horizontal transversely isotropic media, the logarithmic normalized azimuthal elastic impedance (EI) is rewritten in terms of Fourier coefficients (FCs), the 90° ambiguity in the azimuth estimation of the symmetry axis is resolved by judging the sign of the second FC, and we choose the FCs with the highest sensitivity to fracture weakness and present a feasible inversion workflow for fracture weakness, which involves: (1) the inversion for azimuthal EI datasets from observed azimuthal angle gathers; (2) the prediction for the second FCs and azimuth of the symmetry axis from the estimated azimuthal EI datasets; and (3) the estimation of fracture weakness combining the extracted second FCs and azimuth of the symmetry axis iteratively, which is constrained utilizing the Cauchy sparse regularization and the low-frequency regularization in a Bayesian framework. Tests on synthetic and field data demonstrate that the 90° ambiguity in the azimuth estimation of the symmetry axis has been removed, and reliable fracture weakness can be obtained when the estimated azimuth of the symmetry axis deviates less than 30°, which can guide the prediction of fractured reservoirs.

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Section: Introductionmentioning

confidence: 99%

Azimuthal elastic impedance-based Fourier coefficient variation with angle inversion for fracture weakness

Zhang

Pan

et al. 2020

Pet. Sci.

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“…In 2008, Wang Baoli proposed Fatti Approximation-based EI formula (EI-Fatti) derived from the Fatti approximation of Zoeppritz equation [8], which can extract P-wave impedance and S-wave impedance directly from the inversed seismic data volume.…”

Section: Introduction Of Ei Formulamentioning

confidence: 99%

Accuracy Comparison of Elastic Impedance Formula

Zhang

Liu

Tong

et al. 2012

AMR

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Elastic impedance (EI) inversion is one of the prestack seismic inversion methods, which can obtain P-wave and S-wave velocity, density, Poisson ratio, Lame coefficients and other elastic parameters. But there have been many EI formulas nowadays, so which formula should be used in inversion is an urgent problem. This paper divides these formulas into two categories, and use several forward modeling to test the accuracy of these EI formulas. It shows that using the first kind of EI formulas in near offset seismic data can get high precision results.

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Multiple elastic attribute fusion approach based on affinity propagation clustering strategy for gas hydrate reservoir identification

et al. 2023

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Pre-stack seismic inversion based on sensitive elastic parameters is critical in reservoir lithology prediction and geofluid identification. The ability of a single elastic attribute to identify a reservoir depends on its sufficient sensitivity to distinguish the target reservoir from the surrounding sediments. In general, high-dimensional data space composed of multiple elastic attributes is more conducive to describing reservoir characteristics. Therefore, a multiple elastic attribute fusion method using affinity propagation clustering strategy for gas hydrate reservoir identification is proposed. Rock-physics modeling is the most effective tool to determine the influence of microscopic physical parameters on macroscopic elastic response and to quantitatively evaluate the sensitivity of elastic attributes. Consequently, a rock-physics model of hydrate sediments considering the non-negligible shear properties of hydrates is constructed to clarify reservoir-sensitive elastic parameters. Additionally, a clustering evaluation indicator is defined to determine the optimal data clustering dimension in terms of feasibility and economy of the proposed method, and to avoid bias in the results due to data redundancy. It is shown that the 3D elastic attribute space consisting of shear modulus, Young's modulus, and S-wave velocity has the best discrimination ability for hydrate reservoirs. The logging data are used to verify the feasibility and effectiveness of the proposed method. Finally, the hydrate reservoir development is accurately discriminated by using the multiple elastic attributes yield from the pre-stack seismic inversion and combined with the fusion strategy.

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Lamé parameters inversion based on elastic impedance and its application

Cited by 20 publications

References 6 publications

Azimuthal elastic impedance-based Fourier coefficient variation with angle inversion for fracture weakness

Azimuthal elastic impedance-based Fourier coefficient variation with angle inversion for fracture weakness

Accuracy Comparison of Elastic Impedance Formula

Multiple elastic attribute fusion approach based on affinity propagation clustering strategy for gas hydrate reservoir identification

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