Study on the 3D Sedimentary Characteristics of Sandstone Type Uranium Reservoir Based on 3D Seismic Attribute

Tight sandstone gas is an important unconventional hydrocarbon resource. In Sichuan Basin, tight sandstone gas is generally stored in channel sandstone reservoirs. Previous studies have shown that the sandstone reservoirs have complex sedimentary features characterized by overlapping multi-stage channel sandstone and large lateral variations. However, it is challenging for conventional inversion methods to adapt to this strong variation. This hinders the accurate construction of the reservoir structural features. A prestack seismic inversion method constrained by a dynamic representation of sedimentary structural features was used to predict the properties of a tight sandstone reservoir. First, an initial feature library (a set of structural features) was extracted from the well log data. Second, reliable inversion results were obtained using prestack inversion near the well logs. Meanwhile, using the reliable inversion results as training samples, an online learning algorithm was introduced to dynamically update the feature library in real-time. Finally, the sedimentary structural features were gradually and stably extended to areas far from the well logs. The results demonstrated that the structural features of multi-stage channel sandstones were inverted accurately using a dynamic representation method. Combined with petrophysical analysis, the density was used to predict the distribution of sandstone thickness. In addition, based on the reliable prestack inversion results, we predicted the gas-bearing properties of sandstone using Poisson’s ratio. The prediction results indicateed the effective size of the reservoir. This provides important information for deploying horizontal wells.

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Using seismic petrophysical modeling and prestack simultaneous inversion to provide insights into the physical properties of uranium-bearing reservoirs: Implications for favorable sites of sandstone-hosted uranium deposits

Wu,

Wang,

Huang

et al. 2024

GEOPHYSICS

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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.

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Study on the 3D Sedimentary Characteristics of Sandstone Type Uranium Reservoir Based on 3D Seismic Attribute

Cited by 6 publications

References 26 publications

Combination of seismic attributes using clustering and neural networks to identify environments with sandstone-type uranium mineralization

Combination of seismic attributes using clustering and neural networks to identify environments with sandstone-type uranium mineralization

Using a dynamic representation of sedimentary structural features in prestack inversion: A case study in a tight sandstone in the Sichuan Basin

Using seismic petrophysical modeling and prestack simultaneous inversion to provide insights into the physical properties of uranium-bearing reservoirs: Implications for favorable sites of sandstone-hosted uranium deposits

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