Improved synchrosqueezing matching pursuit incorporating w-transform
Chaohe Wang, Zhaoyun Zong · 2024
The time-frequency analysis approach is a powerful tool for describing the correlation between the time and frequency of seismic signals. Precise time-frequency results help to better delineate subsurface geological structures. Matching pursuit algorithm can adaptively decompose the signal according to its own signatures. Chakraborty then applied matching pursuit to seismic signal analysis. Then many scholars have carried out a lot of research in application and improvement of this algorithm. Meanwhile, synchros queezing matching pursuit (SSMP) algorithm proposed by Xu is one of them. Although the spectrum energy of SSMP can be gathered to the center time and frequency of the selected matching wavelet. However, there will be a phenomenon of over-compression. A lot of effective formation information will be eliminated, resulting in unreal results and false energy with high resolution, which can not reasonably reflect the formation information. In order to overcome this phenomenon, an improved SSMP incorporating W transform(SSMP-WT) decomposition method is proposed to estimate the well-concentrated time frequency distribution. It decomposes the seismic signal into a series of matched wavelets selected from an over-complete dictionary initially. Furthermore, the whole time-frequency distribution of the signal is generated by superposition of each wavelet’s WT coefficients. The proposed method helps to avoid false information caused by over-compression. Besides, the application of reservoir exploration demonstrates the feasibility of the algorithm.