Predictive deconvolution is an effective way to suppress multiple reflections, especially short path multiples, in seismic data. However, the effectiveness of the predictive deconvolution decreases with increasing offset for the shot data. The design and application of the predictive deconvolution filter are based on two significant parameters, prediction lag and operator length, which are generally used as constant along the offset in the application of conventional predictive deconvolution (CPD). In addition to the effect of the wavelet characteristics of the input seismic data, the operator length is related to the performance of the predictive deconvolution filter while the prediction lag controls the temporal resolution of the input trace. If these parameters are determined by considering near offsets on the autocorrelation window, the primary reflections at far offsets will be attenuated. Conversely, if considering far offsets, then the performance of the predictive deconvolution filter reduces in the elimination of the multiples. In this study, to overcome this trade-off between the near and far offsets, these two parameters are used as variable with increasing offset and it is called offset-dependent predictive deconvolution (ODPD). Detailed analyses of this approach were performed on two synthetics including two specific types of short path multiples such as water bottom peg-leg, intrabed and real marine seismic data. It is observed that operator length should be selected long enough to improve the performance of the predictive deconvolution, especially at the nearest offsets. In addition, if the prediction lag is taken longer than second zero crossing of the autocorrelogram, then the reflection amplitudes from particularly deeper layers are better preserved. It is concluded that the use of the offset varying parameters increases the efficiency of the predictive deconvolution filter and preserves reflection amplitudes, leading to a better signal-to-noise ratio (S/N) of the seismic data.

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偏移相关的预测反褶积中的最佳参数选择：多通道海洋地震数据测试

预测反卷积是抑制地震数据中多次反射（尤其是短路径倍数）的有效方法。但是，预测反卷积的效果会随着镜头数据偏移的增加而降低。预测反卷积滤波器的设计和应用基于两个重要参数：预测滞后和算子长度，在常规预测反卷积（CPD）的应用中，它们通常沿偏移量用作常数。除了输入地震数据的小波特征的影响外，算子长度与预测反卷积滤波器的性能有关，而预测滞后控制输入迹线的时间分辨率。如果这些参数是通过考虑自相关窗口上的接近偏移量确定的，远偏移处的主反射将被衰减。相反，如果考虑远偏移，则预测反卷积滤波器的性能会降低倍数。在这项研究中，为了克服近偏移量和远偏移量之间的折衷，将这两个参数用作随偏移量增加的变量，这被称为偏移量相关的预测反卷积（ODPD）。对这两种方法进行了详细的分析，其中包括两种特殊类型的短程倍数，例如水底桩腿，床内和真实的海洋地震数据。可以看出，应该选择足够长的运算符长度，以改善预测反卷积的性能，尤其是在最近的偏移处。此外，如果预测滞后时间比自相关图的第二个零交叉时间长，则可以更好地保留来自特别深的层的反射幅度。结论是，偏移量变化参数的使用提高了预测反卷积滤波器的效率并保留了反射幅度，从而导致地震数据具有更好的信噪比（S / N）。