A fast and effective grouping and linear-fitting method for suppressing single-frequency interference in seismic data

Abstract Industrial electrical interference in seismic data shows the characteristic of single-frequency, the suppression of which is an important step in the seismic data processing. As the efficiency of seismic acquisition operation is becoming higher and higher, the amount of seismic data acquired is also increasing. To attenuate the single-frequency interference effectively and efficiently, a method that can suppress single-frequency interference accurately and rapidly is proposed. A resampling strategy is presented to divide the original seismic data into several groups, whose resampling interval is equal to the period of single-frequency interference. By using least-squares method for linear fitting, an estimated single-frequency interference model can be built. The estimate is then subtracted from each data group. In the end, all the samples from all divided groups are merged and sorted by time, so that the single-frequency suppressed seismic data can be obtained. The effectiveness of this method in suppressing single-frequency interference is verified by testing it on synthetic and field data and by comparing the results with some existing methods. Synthetic and real data examples indicate that the method is efficient computationally very applicable to land seismic data.