The removal of sinusoidal interference is an important step in seismic data processing, especially for data with low signal-to-noise ratios. The intermittent character of sinusoidal interference makes it challenging to identify and attenuate. To address this issue, we have developed a method to accurately identify sinusoidal interference and rapidly estimate its frequencies. A spectrum-generation strategy is presented to generate an amplitude spectrum with noticeable sinusoidal interference. An initial estimate of the affected frequencies is found using a frequency-search technique based on the amplitude spectrum. The estimate is then refined by an iterative frequency estimation algorithm, which includes fast frequency estimation and normalized crosscorrelation calculation. After modeling the noise using the precise frequency estimation, the sinusoidal interference in seismic data can then be suppressed by adaptively subtracting the estimated noise from the raw seismic data. The effectiveness of our method in identifying sinusoidal interference is verified by testing it on synthetic and field data and by comparing the results with those from existing methods. Synthetic and real data examples indicate that the method is most applicable to land seismic data.

中文翻译：

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地震数据中正弦干涉的有效频率估计方法

去除正弦干扰是地震数据处理的重要步骤，特别是对于低信噪比的数据。正弦干扰的间歇特性使得识别和衰减具有挑战性。为了解决这个问题，我们开发了一种方法来准确识别正弦干扰并快速估计其频率。提出了一种频谱生成策略来生成具有明显正弦干扰的幅度谱。使用基于幅度谱的频率搜索技术找到受影响频率的初始估计。然后通过迭代频率估计算法对估计进行细化，该算法包括快速频率估计和归一化互相关计算。在使用精确的频率估计对噪声进行建模后，然后可以通过从原始地震数据中自适应地减去估计噪声来抑制地震数据中的正弦干扰。通过在合成和现场数据上对其进行测试并将结果与​​现有方法的结果进行比较，验证了我们的方法在识别正弦干扰方面的有效性。合成和真实数据实例表明该方法最适用于陆地地震数据。