Seismic ambient noise is increasingly important in estimating velocity and attenuation structures, as well as understanding parameter variations. However, gaps in recorded time series create challenges in processing ambient noise. This study introduces a novel technique that fills these gaps by using time series with suitable frequency content. To achieve this, a gap was intentionally applied into a continuous time series, and a similar time series, of the same length as the gap, is selected as the primary signal. A moving periodogram, incorporating various windows, was applied to the time series before and after the gap. Stacking these periodograms creates a reference periodogram that indicates the frequency content of the gap. This reference periodogram was then used to improve the frequency content of the primary signal. The study shows promising results with a significant improvement in correlation between the primary signal and the gap through the modification of frequency content. Increasing the number of periodograms used in the stacking process improves the estimation of frequency
content, and optimal window lengths have a significant impact on outcomes. This methodology ensures accurate recovery of high powers through modification operations. By addressing data gaps in seismic ambient noise, this advanced technique contributes to continuous progress in this field.
