Time-domain hyperbolic Radon transform for separation of P-P and P-SV wavefields

Jiang, Xiaoxue; Fan, Zheng; Jia, Haiqing; Lin, Jun; Yang, Hao-Jan

doi:10.1007/s11200-015-0735-y

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…Therefore, frequency-domain high-resolution LRT can, in theory, sparsely represent surface waves. Reflections are approximated by hyperbolas, and time-domain high-resolution HRT can sparsely represent reflections with the assumptions that velocities change little horizontally and reflection interfaces are almost horizontal [26]. We choose frequency-domain high-resolution LRT and time-domain high-resolution HRT to represent surface waves and reflections, respectively.…”

Section: New Method: Sparse Representations Of Wavefields Based On Mcamentioning

confidence: 99%

“…What causes this phenomenon, "mode kissing", is the non-negligible effect of the reflections within this range of frequencies and velocities. The picked dispersion curves based on the amplitude and the continuity of dispersive energy are shown in Figure 5c, where the second higher mode of frequencies of [25][26][27] Hz is misidentified as the third higher mode. However, the surface-wave dispersive energy on Z-component seismic data is not severely influenced by the reflections from the deep reflectors according to Hu et al [19].…”

Section: Distortion Of Surface-wave Dispersive Energy Caused By Reflementioning

confidence: 99%

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Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Qiu

Wang

et al. 2018

Applied Sciences

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It is essential to extract high-fidelity surface waves in surface-wave surveys. Because reflections usually interfere with surface waves on X components in multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. To make matters worse, the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between surface waves and reflections. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections, respectively. Then, a sparse representation problem based on morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, the results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extraction of accurate dispersion curves.

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Section: New Method: Sparse Representations Of Wavefields Based On Mcamentioning

confidence: 99%

Section: Distortion Of Surface-wave Dispersive Energy Caused By Reflementioning

confidence: 99%

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Qiu

Wang

et al. 2018

Applied Sciences

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“…Reflections are approximated by hyperbolas and time-domain high-resolution HRT can sparsely represent reflections with assumptions that velocities change little horizontally and reflection interfaces are almost horizontal (Jiang et al 2016). We choose…”

Section: Sparse Representation Problem Based On Mcamentioning

confidence: 99%

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Qiu¹,

Wang²,

Lu³

et al. 2018

Preprint

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Extraction of high-resolution surface waves is essential in surface-wave survey. Because reflections usually interfere with surface waves on X-component in a multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. The situation goes more serious when the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between reflections and surface waves. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections respectively. Then, the sparse representation problem based on the morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extracting accurate dispersion curves.

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“…One way to get sparse representations is by using iterative thresholding algorithms with sparsity constraints [8,21]. Popular applications using such representations are seismic data interpolation and wavefield separation [16,23]. Since iterative schemes for computing such representations require the application of the forward and adjoint operators several times, it becomes important to use fast algorithms for the realization of the operators to the limit the total computational cost.…”

Section: Introductionmentioning

confidence: 99%

Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates

Никитин

Андерссон

Carlsson

et al. 2017

Computers & Geosciences

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The hyperbolic Radon transform is a commonly used tool in seismic processing, for instance in seismic velocity analysis, data interpolation and for multiple removal. A direct implementation by summation of traces with different moveouts is computationally expensive for large data sets. In this paper we present a new method for fast computation of the hyperbolic Radon transforms. It is based on using a log-polar sampling with which the main computational parts reduce to computing convolutions. This allows for fast implementations by means of FFT. In addition to the FFT operations, interpolation procedures are required for switching between coordinates in the time-offset; Radon; and log-polar domains. Graphical Processor Units (GPUs) are suitable to use as a computational platform for this purpose, due to the hardware supported interpolation routines as well as optimized routines for FFT. Performance tests show large speed-ups of the proposed algorithm. Hence, it is suitable to use in iterative methods, and we provide examples for data interpolation and multiple removal using this approach.

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Time-domain hyperbolic Radon transform for separation of P-P and P-SV wavefields

Cited by 10 publications

References 19 publications

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates

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