The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on t...The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on the fast and modified parabolic Radon transform presented by Abbad. The introduction of a new variable 2 makes the transform operator frequency-independent. Thus, we need to calculate the transform operator and its inverse operator only once, which greatly improves the computational efficiency. Besides, because the primaries and multiples are distributed on straight lines with different slopes in the 2-fdomain, we can easily choose the filtering operator to suppress the multiples. At the same time, the proposed method offers the advantage of high-resolution Radon transform, which can greatly improve the precision of attenuating the multiples. Numerical experiments suggest that the multiples are well suppressed and the amplitude versus offset characteristics of the primaries are well maintained. Real data processing results further verify the effectiveness and feasibility of the method.展开更多
Radon transform is to use the speed difference between primary wave and multiple wave to focus the difference on different"points"or"lines"in Radon domain,so as to suppress multiple wave.However,th...Radon transform is to use the speed difference between primary wave and multiple wave to focus the difference on different"points"or"lines"in Radon domain,so as to suppress multiple wave.However,the limited migration aperture,discrete sampling,and AVO characteristics of seismic data all will weaken the focusing characteristics of Radon transform.In addition,the traditional Radon transform does not take into account the AVO characteristics of seismic data,and uses L1 Norm,the approximate form of L0 Norm,to improve the focusing characteristics of Radon domain,which requires a lot of computation.In this paper,we combine orthogonal polynomials with the parabolic Radon transform(PRT)and find that the AVO characteristics of seismic data can be fitted with orthogonal polynomial coefficients.This allows the problem to be transformed into the frequency domain by Fourier transform and introduces a new variable,lambda,combining frequency and curvature.Through overall sampling of lambda,the PRT operator only needs to be calculated once for each frequency,yielding higher computational efficiency.The sparse solution of PRT under the constraints of the smoothed L0 Norm(SL0)obtained by the steepest descent method and the gradient projection principle.Synthetic and real examples are given to demonstrate that the proposed method has This method has advantages in improving the Radon focusing characteristics than does the PRT based on L1 norm.展开更多
基金sponsored by the National 973 Program(No.2011CB202402)the National Natural Science Foundation of China(No.41104069)the Fundamental Research Funds for the Central Universities(No.14CX06017A)
文摘The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on the fast and modified parabolic Radon transform presented by Abbad. The introduction of a new variable 2 makes the transform operator frequency-independent. Thus, we need to calculate the transform operator and its inverse operator only once, which greatly improves the computational efficiency. Besides, because the primaries and multiples are distributed on straight lines with different slopes in the 2-fdomain, we can easily choose the filtering operator to suppress the multiples. At the same time, the proposed method offers the advantage of high-resolution Radon transform, which can greatly improve the precision of attenuating the multiples. Numerical experiments suggest that the multiples are well suppressed and the amplitude versus offset characteristics of the primaries are well maintained. Real data processing results further verify the effectiveness and feasibility of the method.
基金funded by the Basic Research and Strategic Reserve Technology Research Fund Project of CNPC (2019D-500803)the national oil and gas project (2016zx05007-006)。
基金funded by the National Natural Science Foundation of China(No.41774133)major national science and technology projects(No.2016ZX05024-003 and 2016ZX05026-002-002)the talent introduction project of China University of Petroleum(East China)(No.20180041)
文摘Radon transform is to use the speed difference between primary wave and multiple wave to focus the difference on different"points"or"lines"in Radon domain,so as to suppress multiple wave.However,the limited migration aperture,discrete sampling,and AVO characteristics of seismic data all will weaken the focusing characteristics of Radon transform.In addition,the traditional Radon transform does not take into account the AVO characteristics of seismic data,and uses L1 Norm,the approximate form of L0 Norm,to improve the focusing characteristics of Radon domain,which requires a lot of computation.In this paper,we combine orthogonal polynomials with the parabolic Radon transform(PRT)and find that the AVO characteristics of seismic data can be fitted with orthogonal polynomial coefficients.This allows the problem to be transformed into the frequency domain by Fourier transform and introduces a new variable,lambda,combining frequency and curvature.Through overall sampling of lambda,the PRT operator only needs to be calculated once for each frequency,yielding higher computational efficiency.The sparse solution of PRT under the constraints of the smoothed L0 Norm(SL0)obtained by the steepest descent method and the gradient projection principle.Synthetic and real examples are given to demonstrate that the proposed method has This method has advantages in improving the Radon focusing characteristics than does the PRT based on L1 norm.
