Multiscale frequency-domain seismic inversion for fracture weakness

Pan, Xinpeng; Li, Lin; Zhang, Guangzhi

doi:10.1016/j.petrol.2020.107845

Cited by 15 publications

(2 citation statements)

References 34 publications

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“…However, multiple seismic attenuation inversion approaches are only developed in an isotropic medium. Q inversion in anisotropic media is mostly used to predict fracture (Chen & Innanen, 2018; Pan et al., 2019, 2020, 2021). In addition, the approximate form of the reflection coefficient in a viscoelastic anisotropic medium is complex, and there are many parameters to be inverted (Yang et al., 2021; Zong et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Characterization and analysis of attenuation anisotropy in viscoelastic vertical transverse isotropic media

Xi,

Yin

2024

Geophysical Prospecting

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Due to the intrinsic attenuation of the earth, the study of wave propagation characteristics, considering seismic attenuation plays an important role in high‐precision reservoir prediction. Therefore, we investigate the propagation and reflection characteristics of seismic waves in viscoelastic vertical transverse isotropic media in the complex frequency domain. Specifically, we analyse the response characteristics of velocity, propagation vector and attenuation vector with respect to viscosity media with different attenuation intensities. Furthermore, based on the quasi‐Zoeppritz equation, the variation of reflection coefficient amplitude with offset at different attenuation angles and different attenuation intensities is studied. We also compare the trends in the amplitude variation of reflection coefficients with offset in elastic isotropic, elastic anisotropic and viscoelastic anisotropic media. Due to the complexity of the exact reflection coefficient expression, we first propose the approximate expression of the attenuation–anisotropy parameters and then derive the approximate expression of the reflection coefficient. The numerical simulation results show that the approximate expression of the reflection coefficient is still accurate, even in media with strong anisotropy. Finally, the accuracy evaluations of the reflection coefficient formulas using four typical theory models demonstrate that the approximate reflection coefficient formulas are highly accurate in both weak and strong anisotropic media.

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Section: Introductionmentioning

confidence: 99%

Characterization and analysis of attenuation anisotropy in viscoelastic vertical transverse isotropic media

Xi,

Yin

2024

Geophysical Prospecting

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“…This method can effectively reduce the nonlinearity of the inverse problem and avoid the solution falling into local minima. Some scholars use the Hamming window, Wiener filter and wavelet transform to perform multi-scale decomposition of seismic data for full waveform inversion, which improves both the global convergence of the inversion and the resolution of the predicted subsurface parameters effectively [28][29][30][31]. Inspired by this, we introduce the multi-scale inversion strategy into deep learning-based seismic impedance inversion.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Seismic Impedance Inversion Based on Multi-Scale Strategy

Zhu

Chen

et al. 2022

Remote Sensing

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Seismic impedance inversion is one of the most commonly used techniques for reservoir characterization. High accuracy and high resolution seismic impedance is a prerequisite for subsequent reservoir interpretation. The data-driven approach offers the opportunity for accurate impedance prediction by establishing a nonlinear mapping between seismic data and impedance. However, existing data-driven methods take the raw seismic data directly as input, making it difficult for the network to learn high frequency weak signal information and resulting in low resolution inversion results. In order to mitigate the above issues, a data-driven seismic impedance inversion method based on multi-scale strategy is proposed. The method first obtains seismic data at different scales using frequency division techniques and do normalization on the extracted multi-scale data to ensure the consistency of the seismic signal energy in different frequency bands. The multi-scale seismic data will then be fed into the network, which helps the network to learn the high frequency information features more easily, and ultimately obtain higher resolution inversion results. We use the most commonly used convolutional neural network (CNN) as an example to demonstrate that the proposed multi-scale data-driven seismic impedance inversion method can improve the resolution of the inversion results. In addition, since the above seismic impedance inversion method is executed trace-by-trace, the f-x prediction filtering technique is introduced to improve the lateral continuity of the inversion results and obtain more geologically reliable impedance profiles. The validity of the proposed method is verified in the application of synthetic model data as well as an actual data set.

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High-resolution seismic inversion method based on joint data-driven in the time-frequency domain

Liu,

Miao

2024

Artificial Intelligence in Geosciences

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Multiscale frequency-domain seismic inversion for fracture weakness

Cited by 15 publications

References 34 publications

Characterization and analysis of attenuation anisotropy in viscoelastic vertical transverse isotropic media

Characterization and analysis of attenuation anisotropy in viscoelastic vertical transverse isotropic media

Data-Driven Seismic Impedance Inversion Based on Multi-Scale Strategy

High-resolution seismic inversion method based on joint data-driven in the time-frequency domain

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