Effects of periodically varying codes on separation of multisource blended data

Current exploration needs are satisfied by multisource technology, which offers low cost, high efficiency, and high precision. The delay time, which determines the separation effects of the multisource blended data, is one of the most crucial parameters in the acquisition and separation of multisource data. This study uses the deblending method of multisource data based on a periodically varying cosine code and analyses the effects of the two parameters, namely, the period amplitude and period length, used in this method on the separation of the multisource blended data. Meanwhile, the obtained coherence data is used to prove the correlation between the separation of multisource data and the two parameters. Examples of synthetic and field data are adopted to demonstrate that from a qualitative perspective, increasing the amplitude of the periodic code improves the separation effect within a reasonable delay time range. When the period length varies in a suitable range, the secondary noise becomes relatively incoherent, resulting in the separation result with a higher signal-to-noise ratio (SNR). From a quantitative perspective, the significant values (Sig.) of the period amplitude and length on the SNRs are less than 0.05, verifying the correlation between the separation of multisource data and the two parameters.