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通常认为,假频是由于采样使尼奎斯特以上的频率与尼奎斯特以下的频率不可恢复地“混合”而产生的。因此,防止信号假频这种不言而喻的要求在限制可利用的信号带宽中起着主要的作用。然而,在多道地震数据中,假频出现的证据常常是似有似无、自相矛盾的,这暗示着假频更大的可能性是表面的而不是真实的。一种简捷、精确的样点变换方法——随机采样间隔成像法,可以克服目前地震数据成像处理中的许多假频。这种稳健的处理技术在合成记录和实际数据上,可恢复大大高于尼奎斯特频率(1-D采样原理预测的极限频率)的频率成分的宽频带信号。当信号轨迹被2-D或多维采样网格不规则地截断时,该方法也是适用的。结果征明,空间域和时间域的信号假频可以通过该对策同时得到解决。
It is generally assumed that aliasing is caused by the non-recoverable “mixing ” of the sampling above Nyquist and the Nyquist frequency. Therefore, the self-evident requirement of preventing signal aliasing plays a major role in limiting the available signal bandwidth. However, in multi-channel seismic data, evidence of frequent occurrence is often plausible and self-contradictory, suggesting that the possibility of larger aliasing is superficial rather than real. A simple and accurate method of transforming samples - random sampling interval imaging method can overcome many of the aliasing in seismic data processing. This robust processing technique can recover wideband signals at frequencies well above the Nyquist frequency (the limiting frequency predicted by the 1-D sampling principle), both on synthetic records and on actual data. This method is also applicable when signal traces are irregularly truncated by 2-D or multi-dimensional sampling grids. The result shows that the signal aliasing in the space domain and the time domain can be solved simultaneously by the countermeasure.