根据原始地震资料中工业电干扰的单频特点，提出了基于归一化互相关系数自动识别含单频干扰地震道并进行自适应压制的方法。 选择深部位时窗，采用正弦函数和余弦函数的组合形式来表征单频干扰，以此逼近实际地震数据中可能含有的单频干扰，并使目标函数（实际地震数据与单频干扰的平方残差）达到极小值，由此求得单频干扰的振幅、相位和频率；再将该单频干扰与实际地震数据进行归一化互相关系数计算，归一化互相关系数越大，则该实际地震数据中含有单频干扰的可能性越大，反之则不含有单频干扰或含有的单频干扰能量较弱，可以忽略；对归一化互相关系数设置单频干扰的识别门槛值来分选含有单频干扰的实际地震道，并将单频干扰从实际地震数据中减掉，由此实现地震数据中单频干扰的自动识别和自适应压制。 实际地震资料验证了所提方法的准确性和有效性，在单频干扰识别精度和压制效果方面均优于常规带通滤波均方根能量单频识别方法和某工业化软件，为实际地震资料保幅处理提供了一种有效的方法。

Industrial electrical interference in seismic data has the characteristics of single-frequency, which can be expressed with sine or cosine function. Therefore, this paper presented a new method of automatic identification and self-adaptive suppression of the single-frequency interference based on normalized cross correlation coefficient. We combined the sine function and cosine function to depict the single-frequency interference within the deep time-window, which can approximate the single-frequency interference that may be contained within the practical seismic data, and then minimized the square difference target function between the practical seismic data and the predicted single frequency interference, and finally computed the amplitude, frequency and phase of single-frequency interference. We carried out the normalized cross correlation computation between the predicted single-frequency interference and the practical seismic data, the larger the normalized cross correlation coefficient is, the more possibility the seismic data contains the single-frequency interference. On the contrary, this seismic trace does not contain single frequency interference or contains single frequency interference with week amplitude that can be ignored. Consequently, we presented a threshold value which is used to select the seismic trace containing single-frequency interference, which is subtracted from the original seismic data. With above processing stages, we finished the automatic identification and selt-adaptive suppression of single-frequency interference from the seismic data. The practical seismic data verifies the effectiveness and accuracy of the proposed method, which is better than conventional band pass filter square energy identifying method and the industrial software over the identification accuracy and suppression effect. In a summary, the proposed method can provide an effective method for the practical seismic data amplitude-preserved processing.