Frequency information extraction based on time-frequency ridges for characterizing thin sand bodies

Abstract

Abstract Time-frequency analysis (TFA) is a widely used reservoir prediction technology. During the identification of sand bodies using TFA, abnormally high values in the high-frequency portion of the spectrum usually indicate the presence of thin sand bodies. However, owing to the complexity of the depositional environment, the spatial distribution of thin sand bodies is often variable, and multiple phases of sand bodies—superimposed on each other—can occur with uneven thicknesses. A frequency information extraction technique based on time-frequency ridges (TFRs) is proposed in this study to identify stable TFRs in the time-frequency spectrum of a rearranged smooth pseudo-Wigner–Ville distribution with high energy aggregation, as well as to extract the main- and high-frequency energy contents relative to them. To enhance the ability of these energy components to detect thin sand bodies, a frequency-energy weighting factor is computed. By performing the aforementioned steps, information about each frequency band can be obtained and a comprehensive depiction of sand bodies with different thicknesses achieved. It is concluded that by using the proposed method thin sand bodies such as small riverbeds can be effectively characterized using seismic data.