Abstract In actual data processing, the parabolic Radon transform is a commonly used method to suppress multiples. However, it is difficult to suppress those multiples whose curvatures are very similar to that of the primaries using the conventional Radon transform. This paper gives a multiple-suppression method with curvature amplification to improve the multiple-suppression effect. By studying the parameters that affect the curvature of the event, it is found that compressing the offset or increasing the time difference can amplify the difference between the curvatures of the multiples and primaries, and the separation degrees of the multiples and primaries in the Radon domain are increased, so the multiple-suppression ability is improved. To improve the computational efficiency and accuracy of the Radon transform, the λ–f domain high-resolution parabolic Radon transform is used to eliminate the frequency dependence of the conventional Radon transform operator by introducing a new variable λ. Because the new transform operator and its inverse operator need to be calculated
only once, the computational efficiency is significantly improved. The theoretical model data and the actual data processing show that the method can suppress the surface multiples well, and it also has a certain ability to suppress the internal multiples that have a particular curvature difference from the primaries.
Fund: this research is funded by the Basic Research and Strategic Reserve Technology Research Fund Project
of CNPC (2019D-500803) and the national oil and gas project (2016zx05007-006).
About author: Xie Jun-fa obtained his Ph.D. degree from the China University of Petroleum (Huadong) in 2016. He is currently working in the Research Institute of Petroleum Exploration and Development Northwest Branch, CNPC. He is committed to research on seismic data processing, seismic data regularization, and multiple suppression.
Cite this article:
. Multiple-suppression method using the λ―f domain high-resolution parabolic Radon transform with curvature magnification[J]. APPLIED GEOPHYSICS, 2024, 21(1): 169-178.
2024, Vol. 21 
