Lithology discrimination based on direct inversion of Poisson impedance for deep tight-sandstone reservoirs

Lithology discrimination plays an important role in characterizing deep-hydrocarbon reservoirs, particularly for tight sandstones with special petrophysical properties. Stable prediction of lithological-sensitive parameters for deep tight sandstones is a significant challenge. In this paper, a direct inversion method of elastic impedance is developed to estimate lithological-sensitive parameters from pre-stack seismic data to improve the stability of the inversion. Elastic and physical parameter models extracted from actual wells are used to analyze the influence of petrophysical parameters on amplitude variation with offset characteristics. Cross-plots and sensitivity analysis of elastic parameters illustrate that the elastic-sensitive parameter Poisson impedance (PI) can distinguish gas-bearing sandstone and abnormal limestone in deep tight-sandstone reservoirs. In addition, a pragmatic elastic impedance direct inversion under the framework of Bayesian theory is implemented for the lithology indicator PI from pre-stack seismic data. And the Cauchy regularization and low-frequency regularization constraints are used to construct the objective function for improving the robustness of inversion. Field data examples show that the inversion results are in good agreement with the well logging interpretation results, and validate the feasibility and stability of the proposed method in the estimation of inverted parameters. Finally, we can conclude that this method has great application potential in the lithology discrimination of deep tight-sandstone reservoirs.