Wave propagation characteristics and parameter sensitivity analysis of Longmaxi shale in deep oil and gas reservoirs under multiple dissipation mechanisms

Longmaxi Formation shale is widely distributed and resource rich, making it one of the key target formations for shale gas exploration and development in China. This shale is typically characterized by low porosity and low permeability, representing a typical dense unconventional oil and gas reservoir. In practical oil and gas exploration, fluctuation response signals are extensively used for reservoir parameter identification and structural analysis. The traditional Biot model provides a preliminary description of wave propagation behavior in porous media from the perspective of energy conservation; however, it often underestimates energy dissipation and wave attenuation, which limits its accuracy when applied to complex shale reservoir conditions. To establish a propagation model that accurately captures the wave dissipation mechanisms in deep shale reservoirs, a frequency-dependent dynamic tortuosity analysis method based on energy conservation and mass invariance is proposed, taking into account the effects of irregularities in mineral particles and pore channels on tortuosity in actual reservoir shales. Additionally, time-varying correlated nonlinear viscoelastic constitutive relations are introduced to characterize the mechanical behavior of the solid skeleton, enabling the construction of wave field equations applicable to fluid–pore media systems under different frequency conditions. On this basis, the Biot model is improved by refining the mechanisms of frictional dissipation, internal dissipation, and relaxation dissipation in the wave field equations, resulting in the development of a wave propagation model—the WMDM model (Wave propagation model under Multiple Dissipation Mechanisms), which is suitable for a multiband frequency range. Comparative analysis of the numerical calculations and wave velocity test results of the Longmaxi shale model reveals that the WMDM model significantly improves the prediction accuracy of the shale wave velocity dispersion and attenuation characteristics in the low-frequency range and clearly reveals three distinct dispersion zones and attenuation peaks across the full frequency band. Through sensitivity parameter analysis, it is revealed that liquid saturation, fluid type, and porosity influence the wave propagation process by modulating the effective density, modulus, and coupling relationship between fluid flow and the solid matrix. Moreover, a hybrid SSA-GA inversion method that combines the sparrow search algorithm (SSA) and genetic algorithm (GA) is proposed to address the challenge that the model's viscoelastic parameters are difficult to measure directly. A comparison of the inversion results obtained by different algorithms demonstrates that the hybrid algorithm outperforms traditional methods in terms of global search capability, inversion accuracy, and computational efficiency and successfully captures the frequency-dependent behavior of the actual wave velocity.