The heterogeneity of rock fabric and fluid distribution induce Wave-induced Fluid Flow (WIFF), a mechanism that significantly affects the velocity dispersion and energy attenuation of seismic waves. We integrate pore structure (intralayer) and fluid saturation (inter-layer) heterogeneity into a unified framework to establish a layered double-porosity patchy-saturated (LDPPS) porous model and obtain the potential, kinetic and dissipation functions via the generalized Biot theory. Based on Hamilton’s principle, we derive the new governing equations for the LDPPS model. Five P-waves and one S-wave are achieved through plane wave analysis. We investigate the properties of fast P-wave and S-wave through changing relevant rock parameters. The results show that there are three attenuation peaks for fast P-wave in the whole frequency band, corresponding to mesoscopic fluid flow (fluid heterogeneity), microscopic fluid flow (fabric heterogeneity) and macroscopic fluid flow (Biot flow). Furthermore, it is found that the model exhibits strong sensitivity to water saturation, permeability, fluid viscosity and heterogeneity scale. Finally, we compare the dispersion and attenuation predicted by our theory with experimental data, and the results show that the theoretical predictions are consistent with reality. Since our proposed theory can account for multiscale fluid flow in the whole frequency band, it is of great significance for fluid evaluation in reservoirs.

As an effective time-frequency (TF) analysis method, S transform (ST) has an extensive application in signal processing. However, for broad-band seismic signals, the peaks of the frequency distribution in the TF spectrum of ST biases the actual Fourier spectrum. Besides, the TF resolution of ST is affected by the relatively fixed window function and the Heisenberg uncertainty principle. In order to correct the frequency bias and improve the TF resolution of ST, and at the same time, to increase the flexibility of the window function, we propose a new TF analysis method, called the deconvolutive frequency corrected three-parameter S transform (DFC-TPST). The DFC-TPST includes two steps: modifying the window function to achieve the frequency corrected three-parameter S transform (FC-TPST) and deconvoluting FC-TPST to achieve DFC-TPST. The synthetic example proves the superiority of the method in characterizing seismic signals. Through comparison of field data testing, we find that the proposed method can be well applied to the hydrocarbon detection in tight sandstone reservoir.

Time-frequency (TF) analysis is an important tool for seismic signal analysis, and traditional methods are difficult to achieve high TF resolution and energy aggregation. In this letter, we propose the adaptive time-synchroextracting S transform (ATSEST) for seismic data processing and interpretation. The method first calculates the scale parameter of the window function through the Fourier spectrum of the signal to obtain the adaptive S transform spectrum. After that, the final result is obtained by extracting the TF coefficients at the group delay and removing a large amount of fuzzy energy in the TF spectrum. The results of the synthetic example TF analysis show that the method can improve the localization ability of transient features of seismic signals. We apply the method to the fault identification of field data, and the results show that the coherent attribute slices extracted by using ATSEST can well characterize the fault.