Applications of time‐domain high‐resolution Radon demultiple

Schonewille, Michel; Aaron, Peter

doi:10.1190/1.2793000

Cited by 18 publications

(4 citation statements)

References 5 publications

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“…Various multiple elimination approaches have been developed in the past few decades that can be classified into three classes in general. The first class is filtering-based methods, such as the predictive deconvolution method relying on the periodicity difference between primaries and multiples (Peacock and Treitel 1969;Taner 1980) and the transformation methods founded on the separability of primaries and multiples in a specific domain (Foster and Mosher 1992;Schonewille and Aaron 2007;Yilmaz 2001). Unlike the first class of techniques, the second class is wave-equation-based methods provided with higher precision and a wider range of applications.…”

Section: Introductionmentioning

confidence: 99%

Seismic forward modeling of acoustic surface-related order-separated multiples

Wang

et al. 2023

Mar Geophys Res

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Seismic surface-related multiples have become a hot topic of great significance due to the buried geological information provided by broader illumination areas than primaries. In recent years, researchers attempt to extract the hidden hint of multiples rather than treating them as noise and eliminating them directly. The elimination methods, e.g., the surface-related multiple elimination (SRME) and the inverse scattering series free-surface multiple elimination (ISS-FSME), may be affected by the overlapping or proximity of primaries and multiples. Typical imaging methods, e.g., the reverse time migration (RTM) and the least-square reverse time migration (LSRTM), suffer severe crosstalk artifacts from multiples of inappropriate order and smooth migration velocities. To study the characteristics of primaries and surface-related multiples, whether for elimination or imaging, we propose a forward modeling method of acoustic surface-related order-separated multiples established on the areal/virtual source assumption. The free surface is replaced with an absorbing surface under the dipole source approximation and the ghost creation approach. We present two reflection operators to approximate the reflection at the free surface and apply them to the areal source to obtain ideal results. Numerical experiments on three models prove the effectiveness of the proposed forward modeling method of acoustic surface-related order-separated multiples.

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Section: Introductionmentioning

confidence: 99%

Seismic forward modeling of acoustic surface-related order-separated multiples

Wang

et al. 2023

Mar Geophys Res

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“…In response to this constraint, the time domain sparse RT (TSRT) was introduced [27], offering a higher level of sparsity in the time domain and thereby achieving enhanced resolution. However, it is worth noting that TSRT comes with a substantial computational cost [28]. Combining the advantages of TSRT and FSRT, a novel RT was developed by Trad et al [6].…”

Section: Introductionmentioning

confidence: 99%

Multiple Elimination Based on Mode Decomposition in the Elastic Half Norm Constrained Radon Domain

Ma,

Song,

et al. 2023

Applied Sciences

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Multiple reflection is a common interference wave in offshore petroleum and gas exploration, and the Radon-based filtering method is a frequently used approach for multiple removal. However, the filtering parameter setting is crucial in multiple suppression and relies heavily on the experience of processors. To reduce the dependence on human intervention, we introduce the geometric mode decomposition (GMD) and develop a novel processing flow that can automatically separate primaries and multiples, and then accomplish the suppression of multiples. GMD leverages the principle of the Wiener filtering to iteratively decompose the data into modes with varying curvature and intercept. By exploiting the differences in curvature, GMD can separate primary modes and multiple modes. Then, we propose a novel sparse Radon transform (RT) constrained with the elastic half (EH) norm. The EH norm contains a l1/2 norm and a scaled l2 norm, which is added to overcome the numerical oscillation problem of the l1/2 norm. With the help of the EH norm, the estimated Radon model can reach a remarkable level of sparsity. To solve the optimization problem of the proposed sparse RT, an efficient alternating multiplier iteration algorithm is employed. Leveraging the high sparsity of the Radon model obtained from the proposed transform, we improve the GMD-based multiple removal framework. The high-sparsity Radon model obtained from the proposed Radon transform can not only simplify the separation of primary and multiple modes but also accelerate the convergence of GMD, thus improving the processing efficiency of the GMD method. The performance of the proposed GMD-based framework in multiple elimination is validated through synthetic and field data tests.

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“…Since Hampson (1986) proposed the least squares RT (LSRT), scholars devote themselves extensively to how to address the sparse inverse problem. From this, two series of RT algorithms are proposed, namely frequency domain algorithms (Sacchi & Ulrych, 1995;Sacchi & Porsani, 1999) and time domain algorithms (Cary, 1998;Schonewille & Aaron, 2007;Fan et al, 2015). However, both frequency and time domain algorithms have their inherent flaws; the former is incapable of improving the resolution along the time direction due to the coupling between frequency and time, while the latter suffers a serious computational burden due to the large matrix inversion (Trad et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

3D high‐order sparse radon transform with L_1–2 minimization for multiple attenuation

Geng

Chen

et al. 2022

Geophysical Prospecting

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Among many multiple attenuation methods, parabolic Radon transform has been widely used due to its efficiency and effectiveness. However, there are two factors that restrict the application of Radon transform: (1) the smearing caused by finite seismic acquisition aperture and discrete sampling of seismic data and (2) the destruction of the amplitude versus offset signature in seismic data. Therefore, a high‐order sparse Radon transform in the mixed frequency–time domain with L1–2 minimization is proposed. The L1–2 metric has been proved an unbiased approximation to L0 norm, which helps improve the sparsity and resolution of the Radon model. By combining the orthogonal polynomial transform, which can fit the amplitude variations of seismic data, the amplitude versus offset signature is also considered. Furthermore, the 2D Radon transform is extended to 3D by modifying the augmented Lagrangian in the alternating direction method of multipliers algorithm. Compared with the 2D algorithm, 3D Radon transform considers seismic wave propagation in three dimensions, which can describe the wavefield more accurately. The proposed method is applied to multiple attenuation examples based on both synthetic and real 3D data examples to demonstrate its effectiveness, compared with some existing high‐resolution techniques and the corresponding 2D algorithm.

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Applications of time‐domain high‐resolution Radon demultiple

Cited by 18 publications

References 5 publications

Seismic forward modeling of acoustic surface-related order-separated multiples

Seismic forward modeling of acoustic surface-related order-separated multiples

Multiple Elimination Based on Mode Decomposition in the Elastic Half Norm Constrained Radon Domain

3D high‐order sparse radon transform with L_1–2 minimization for multiple attenuation

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Applications of time‐domain high‐resolution Radon demultiple

Cited by 18 publications

References 5 publications

Seismic forward modeling of acoustic surface-related order-separated multiples

Seismic forward modeling of acoustic surface-related order-separated multiples

Multiple Elimination Based on Mode Decomposition in the Elastic Half Norm Constrained Radon Domain

3D high‐order sparse radon transform with L1–2 minimization for multiple attenuation

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3D high‐order sparse radon transform with L_1–2 minimization for multiple attenuation