遗传算法和正交时频原子相结合的地震记录快速匹配追踪

Seismic trace fast matching pursuit based on genetic algorithm and orthogonal time-frequency atom

针对匹配追踪庞大的计算量造成地震数据处理效率低下的问题,提出一种基于遗传算法和正交原子匹配追踪的快速分解方法,通过遗传算法缩小原子库的搜索范围,减少贪婪迭代的次数,由原子的正交化处理消除冗余分量,加速残差收敛进程。为增加分解的灵活性,采用相邻残差比阈值作为迭代终止条件。合成地震记录和实际地震记录稀疏分解结果表明:本文方法不仅能降低分解的稀疏度,而且运行速度大幅提高,验证了方法的有效性和适用性。

Matching pursuit has become more and more widely used in the seismic exploration area because it can linearly represent seismic trace according to its time-frequency characteristics. However, the amount of calculation is so large that the data processing becomes inefficient. Therefore, this paper proposes a fast matching pursuit method based on genetic algorithm and orthogonal atom. Genetic algorithm could narrow the search range of atom dictionary and reduce the number of greedy iteration. The redundant components could be eliminated by the orthogonalization of atoms and the process of residual convergence is accelerated effectively. In order to increase decomposition flexibility, this paper uses the adjacent residual ratio threshold as the termination condition of iteration. The proposed method is applied to sparse decomposition of synthetic seismic trace and real seismic trace respectively, and the experimental results show that the proposed method could not only reduce the sparsity of decomposition, but also greatly improve the operating speed. © 2016, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.