Suppressing residual low-frequency noise in VSP reverse time migration by combining wavefield decomposition imaging condition with Poynting vector filtering

Zhang, Lele; Liu, Yang; Jia, Wanli; Wang, Jing

doi:10.1080/08123985.2020.1804298

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…To mitigate the artefacts in the inverted model, Equation ( 2) is modified by taking derivatives of the source u s (x, t ) and receiver wavefields F * [δs] with respect to the spatial coordinates (x, z). This modification reduces the effects of the arrivals with large incident angles as described by Yu and Liu (2021) and Zhang et al (2020). From the initial model (Fig.…”

Section: Overthrust Modelmentioning

confidence: 99%

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Full‐waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory

Liu

2022

Geophysical Prospecting

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Full‐waveform inversion has become a useful tool to construct the details of the geological structure. However, due to the strong nonlinearity of the inverse problem and inaccuracy of the initial model, full‐waveform inversion often faces severe cycle‐skipping problems and thus may exhibit poor inversion results. The optimal transport‐based full‐waveform inversion can mitigate the cycle‐skipping problem. For that, transformations of oscillatory seismic data to distributions need to satisfy positive and mass conservation conditions. In this work, we introduce a new data normalization method based on the Sigmoid function. The convexity of the objective function is improved compared to the traditional L2 norm by setting appropriate parameters. Combined with the adaptive quadratic Wasserstein distance, our approach presents strong adaptability to a poor initial model and can reduce cycle skipping. Numerical examples are provided to validate the method in a reverse vertical seismic profiling geometry, and the inverted models obtained by different normalization methods are also compared.

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Section: Overthrust Modelmentioning

confidence: 99%

“…This modification reduces the effects of the arrivals with large incident angles as described by Yu and Liu (2021) and Zhang et al . (2020). From the initial model (Fig.…”

Section: Numerical Examplesmentioning

confidence: 99%

Full‐waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory

Liu

2022

Geophysical Prospecting

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“…The decomposed wavefields of both sources and receivers in the opposite direction are selected for imaging separately to avoid migration artifacts (Chen and He, 2014), using the following: 11) where I op (x, z) is the optimal stack section. However, in fact, the migration artifacts are mainly distributed in the large-angle region (Yoon and Marfurt, 2006;Zhang et al, 2014;Zhang et al, 2020). Although the method of selecting the wavefields in the opposite direction for imaging can reduce the migration artifacts of 180 °or close to 180 °, the suppression effect on the migration artifacts coming from other large-angle regions is weak.…”

Section: Angle-weighted Rtm Imaging Based On the Optical Flow Vectormentioning

confidence: 99%

Angle-Weighted Reverse Time Migration With Wavefield Decomposition Based on the Optical Flow Vector

Xie

Song

et al. 2021

Front. Earth Sci.

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Reverse time migration (RTM) is based on the two-way wave equation, so its imaging results obtained by conventional zero-lag cross-correlation imaging conditions contain a lot of low-wavenumber noises. So far, the wavefield decomposition method based on the Poynting vector has been developed to suppress these noises; however, this method also has some problems, such as unstable calculation of the Poynting vector, low accuracy of wavefield decomposition, and poor effect of large-angle migration artifacts suppression. This article introduces the optical flow vector method to RTM to realize high-precision wavefield decomposition for both the source and receiver wavefields and obtains four directions of wavefields: up-, down-, left-, and right-going. Then, the cross-correlation imaging sections of one-way propagation components of forward- and back-propagated wavefields are optimized and stacked. On this basis, the reflection angle of each imaging point is calculated based on the optical flow vector, and an attenuation factor related to the reflection angle is introduced as the weight to generate the optimal stack images. The tests of theoretical model and field marine seismic data illustrate that compared with the conventional RTM with wavefield decomposition based on the Poynting vector, the angle-weighted RTM with wavefield decomposition based on the optical flow vector proposed in this article can achieve wavefield decomposition for both the source and receiver wavefields and calculate the reflection angle of each imaging point more accurately and stably. Moreover, the proposed method adopts angle weighting processing, which can further eliminate large-angle migration artifacts and effectively improve the imaging accuracy of RTM.

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Deriving a Fast P/S Decoupled Operator From 3-D Anisotropic Christoffel Equation With Its Application in Elastic Reverse Time Migration and Angle-Domain Common-Image Gathers

Zhang,

Zhao,

Liu

et al. 2023

IEEE Trans. Geosci. Remote Sensing

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Suppressing residual low-frequency noise in VSP reverse time migration by combining wavefield decomposition imaging condition with Poynting vector filtering

Cited by 5 publications

References 36 publications

Full‐waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory

Full‐waveform inversion for reverse vertical seismic profiling data based on a variant of the optimal transport theory

Angle-Weighted Reverse Time Migration With Wavefield Decomposition Based on the Optical Flow Vector

Deriving a Fast P/S Decoupled Operator From 3-D Anisotropic Christoffel Equation With Its Application in Elastic Reverse Time Migration and Angle-Domain Common-Image Gathers

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