摘要：Due to the finite acquisition aperture and sampling of seismic data, the Radon transform (RT) suffers from a smearing problem which reduces the resolution of the estimated model. In addition, inverting the RT is typically an ill-posed problem. To address these challenges, a sparse RT mixing the l(1) and l(2) norms of the RT coefficients in themixed frequency-time domain is developed, and it is denoted as SRTL1-2. In most conventional sparse RTs, the sparse constraint term often is the l(1) norm of the Radon model. We prove that the sparsity effect of the l(1-2) minimization is better than that of the l(1) norm alone by comparing and analyzing their 2D distribution patterns and threshold functions. The difference of the convex functions algorithm and the alternating direction method of multipliers algorithm are modified by combining the forward and inverse Fourier transforms to solve the corresponding sparse inverse problem in the mixed frequency-time domain. Our method is compared with three RT methods, including a least-squares RT (LSRT), a frequency-domain sparse RT (FSRT), and a time-invariant RT in the mixed frequency-time domain based on an iterative 2D model shrinkage method (SRTIS). Furthermore, wemodify the basis function in SRTL1-2 by including an orthogonal polynomial transform to fit the amplitude-variation-with-offset (AVO) signatures found in seismic data, and we denote this as high-order SRTL1-2. Compared to the SRTL1-2, the high-order SRTL1-2 performs better when processing seismic data with AVO signatures. Synthetic and real data examples indicate that our method has better performance than the LSRT, FSRT, and SRTIS in terms of attenuation of multiples, noise mitigation, and computational efficiency.

ISSN号：0016-8033

卷、期、页：卷: 87期: 5页: V545-V558

发表日期：2022-09-01

影响因子：2.928500

期刊分区（SCI为中科院分区）：三区

收录情况：SCI（科学引文索引印刷版）,地学领域高质量科技期刊分级目录（国外T1）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：GEOPHYSICS

通讯作者：耿伟恒,汤韦,吴凡

第一作者：陈小宏,李景叶,马继涛

论文类型：期刊论文

论文概要：耿伟恒,陈小宏,李景叶,马继涛,汤韦,吴凡，Sparse Radon transform in the mixed frequency-time domain with l(1-2) minimization，GEOPHYSICS，2022，卷: 87期: 5页: V545-V558

论文题目：Sparse Radon transform in the mixed frequency-time domain with l(1-2) minimization