Abstract
The Gassmann fluid term, an important attribute for characterizing reservoir fluid variations, is widely used in seismic inversion for reservoir prediction and fluid identification. However, most existing inversion methods rely on first-order linear approximations of the reflection coefficient equation, ignoring nonlinear responses in complex geological settings, thereby limiting the accuracy of inversion results. To address this limitation, this study derives a quadratic reflection coefficient approximation equation that explicitly incorporates the Gassmann fluid term, by combining the Russell approximation with the quadratic PP-wave reflection coefficient equation. Based on this formulation, an inversion framework is developed using the quadratic approximation. The proposed method first uses the arctangent penalty function as a sparsity constraint, which enhances the overall convexity of the objective function. The Hadamard operator is then used to decompose the variables of the quadratic terms and reduce optimization complexity. Finally, the alternating direction method of multipliers (ADMM) algorithm is introduced to decompose the nonlinear optimization problem into multiple single-variable sub-problems, which are solved through alternating iterations. Model tests and field data applications show that the proposed approach enhances the accuracy of reservoir fluid identification and validates the effectiveness of the quadratic approximation strategy.
Paper Information
Lian Zhao, Danping Cao, Yu Xie. Fluid Factor Inversion with Prestack Seismic Data Based on Quadratic Reflectivity Approximation. IEEE Transactions on Geoscience and Remote Sensing, 2025, 63, 3624912. https://ieeexplore.ieee.org/document/11215802
