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针对目前匹配追踪算法计算效率低的缺点,以Ricker子波作为母函数,提出了指数追踪地震信号分解算法.通过在地震振幅包络极值点处利用指数分布函数进行拟合,求取匹配子波峰值频率,然后利用阻尼最小二乘法求出匹配子波的复振幅,最终将地震信号分解为一系列匹配子波的线性组合.结果表明:相对于复数域快速匹配追踪算法,基于Ricker子波的指数追踪算法在保持地震数据分解精度的前提下,计算效率进一步提高;对于时间采样点数为201的地震剖面,指数追踪算法的计算效率是复数域快速匹配追踪算法的13倍;对于时间采样点数为1 501的地震剖面,计算效率是复数域快速匹配追踪算法的24倍.
Aiming at the shortcomings of low efficiency of matching pursuit algorithm, an exponential tracking seismic signal decomposition algorithm is proposed based on the Ricker wavelet as the parent function. By fitting the exponential distribution function at the extreme point of the amplitude envelope of the earthquake, Wave peak frequency, and then use the damping least square method to find the complex amplitude of the matched wavelet and finally decompose the seismic signal into a linear combination of a series of matched wavelets.The results show that compared with the complex-domain fast matching pursuit algorithm, based on Ricker wavelet The exponential tracking algorithm can further improve the computational efficiency while maintaining the accuracy of the seismic data decomposition. For the seismic section with the time sampling point of 201, the computational efficiency of the exponential tracking algorithm is 13 times that of the complex-domain fast matching pursuit algorithm. For the time sampling points For a seismic section of 1 501, the computational efficiency is 24 times faster than the complex-domain fast matching pursuit algorithm.