摘要
To improve the anti-noise performance of the time-domain Bregman iterative algorithm,an adaptive frequency-domain Bregman sparse-spike deconvolution algorithm is proposed.By solving the Bregman algorithm in the frequency domain,the influence of Gaussian as well as outlier noise on the convergence of the algorithm is effectively avoided.In other words,the proposed algorithm avoids data noise effects by implementing the calculations in the frequency domain.Moreover,the computational efficiency is greatly improved compared with the conventional method.Generalized cross validation is introduced in the solving process to optimize the regularization parameter and thus the algorithm is equipped with strong self-adaptation.Different theoretical models are built and solved using the algorithms in both time and frequency domains.Finally,the proposed and the conventional methods are both used to process actual seismic data.The comparison of the results confirms the superiority of the proposed algorithm due to its noise resistance and self-adaptation capability.
为解决时间域Bregman迭代算法计算效率低、抗噪能力不强的问题,提出了一种高效、自适应的频率域Bregman稀疏脉冲反褶积算法。通过对传统时间域Brgman算法进行频率域推导,得到了一种基于频率域计算的Bregman求解算法。在频率域进行Bregman算法的求解,有效避免了高斯噪音和离群噪音对算法收敛性的影响,并且通过在主频带范围计算,算法较时间域求解效率大幅提高。在求解过程中,引入了广义交叉验证(Generalized Cross Validation,GCV)的方法优选正则化参数,使算法具有了自适应参数选择的能力。通过建立不同的模型,分别使用时间域和频率域Bregman算法进行求解,验证了改进算法在抗噪音、计算效率和自适应方面的优势。最后,将改进方法与常规时间域Bregman算法分别应用于吐哈盆地某实际资料,处理结果表明改进方法较传统算法有更优异的表现。
基金
supported by the National Natural Science Foundation of China(No.NSFC 41204101)
Open Projects Fund of the State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(No.PLN201733)
Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.2015051)
Open Projects Fund of the Natural Gas and Geology Key Laboratory of Sichuan Province(No.2015trqdz03)
