Well-logging constrained direct inversion of pre-stack seismic data for reservoir porosity prediction

Porosity serves as a crucial reservoir parameter for hydrocarbon exploration. This study constructed a mathematical model integrating Gassmann's equation and Eshelby-Walsh theory. Using this model, an objective function was derived and established for direct porosity inversion relying on the inverted high-precision pre-stack elastic parameters from pre-stack seismic data with a high signal-to-noise ratio, thereby enabling the direct calculation of formation rock porosity. Within the framework of generalized linear inversion theory, using the precise Zoeppritz equation as the theoretical foundation, this study achieved the direct inversion of reservoir porosity by introducing well-logging data as constraints. Conventional porosity estimation methods rely on the indirect porosity estimation using parameters such as P- and S-wave velocities and density, resulting in multi-step error accumulation. To overcome this limitation, this proposed method allows direct input of seismic gathers and well-logging data. In addition, grounded on the theoretical advantages of the exact Zoeppritz equation in describing wavefield propagation, this method yielded inverted porosity results with higher resolution and accuracy compared to those obtained using conventional methods based on three-parameter empirical conversions. Application in actual data shows that the porosity data obtained from the well-logging constrained direct inversion of pre-stack elastic parameters align well with actual logging curves, demonstrating higher accuracy and resolution. The high-precision porosity data provide critical theoretical value and practical guidance for detailed reservoir prediction, well placement optimization, and the design of fracturing production schemes.