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多震源混合地震数据分离方法(英文)

Separation method for multi-source blended seismic data
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摘要 多震源地震技术是一种高效的地震数据采集方法技术,但它得到的地震记录是多震源波场叠加的混合地震数据,因此需要对其进行分离以得到各个震源所对应的地震波场数据。在数学上,多震源波场的分离表现为一个线性反演问题,根据多震源地震数据采集中的激发次数和震源个数之间的关系,它可分为比较容易求解的适定或超定线性反演问题和难以求解的欠定线性反演问题。对于欠定型的多震源波场分离问题,本文提出了利用波场的最稀疏性约束的最优化求解方法,即把待分离波场的最稀疏性作为正则化约束,建立反演的目标函数,然后应用迭代阈值法进行求解。对于最极端欠定型的一次激发的多震源波场分离问题,本文提出了伪分离加随机噪音滤波方法,即首先对波场分离的线性反演问题进行伪求解,得到近似共炮道集,然后再把得到近似共炮道集分选成共检波点道集,使来自其他震源的波场表现为随机噪音,最后利用滤波方法去噪。把本文提出的多震源波场分离方法应用于数值模拟的多震源混合地震数据,在无噪音、含随机噪音以及含线性规则噪音的混合地震记录的分离试验中都得到了理想的结果,特别是对于一次激发情况的分离问题压噪效果尤为显著,表明本文方法适用于含噪多震源混合数据的分离问题,从而证明了本文方法的正确性与有效性。 Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.
出处 《Applied Geophysics》 SCIE CSCD 2013年第3期251-264,357,共15页 应用地球物理(英文版)
关键词 多震源 数据分离 线性反问题 最稀疏约束 伪分离 滤波 Multi-source, data separation, linear inverse problem, sparsest constraint, pseudo-deblending, filtering
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参考文献26

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