accepted as one of the most widely available methods for exploring sandstone-hosted uranium deposits (SUD). However, conventional seismic interpretation faces a challenge in the identification and characterization of a uranium reservoir’s complexity. How to characterize in detail a uranium reservoir’s physical complexity and effectively improve uranium reservoir prediction accuracy remain unresolved problems. To address this, we proposed a novel combination of petrophysical modeling and prestack simultaneous inversion to understand in detail the physical properties of uranium-bearing reservoirs and efficiently predict favorable SUD sites. First, we developed a workflow of rock physics modeling for SUD logs using the Xu–White method to calculate the modulus of elasticity of the grain matrix; subsequently, we extended the Walton model for the modulus prediction of the dry rocks and the Gassmann equation for one of the saturated rocks after a massive calculation test; and then we predicted the shear wave data used for the following inversion. Second, we executed a prestack simultaneous inversion to obtain the petrophysical parameters (e.g., P-impedance, density (ρ), shear modulus (μ), Lame coefficient (λ), Young’s modulus, etc.) that can provide insights into the physical properties of a uranium metallogenic environment. Accordingly, we discovered that sites bearing uranium mineralization strongly correspond with areas with low elastic-parameter values (especially μ * ρ and λ * ρ) while nonuranium anomalies occur in high-value sites. It showed that weakened elastic characteristics are caused by the enhancement of the total organic content and total clay mineral volumes of the uranium-bearing layers. In summary, the developed combination approach can yield an effective and accurate characterization of the geologic properties of uranium-bearing formations, and it can provide prediction factors (e.g., parameters related to the shear modulus) for uranium mineralization.
