An Improved Theoretical Nonelectric Water Saturation Method for Organic Shale Reservoirs

Abstract

The saturation of a shale gas reservoir is used to characterize the fluid content within the pores and to calculate the free gas content and reserves of the reservoir. Thus, accurately evaluating the saturation of a shale gas reservoir is of great significance. However, little research has been performed to quantitatively evaluate the saturation relative to other parameters used for evaluating the gas content. Moreover, because the conductive mechanism of shale gas reservoirs is very complex, the existing electric saturation model is insufficient. In this paper, based on the results of our analysis, we postulate that the organic pores in shale gas reservoirs are full of gas; furthermore, clastic pores also contain some gas. Thus, an improved model based on the original petrophysical model and the theory of shale density characteristics is proposed, and a calculation scheme based on the saturation model of shale gas reservoirs is deduced. The simulation results indicate that the improved model is less sensitive than the original model to changes in the total organic carbon content (TOC), and the water saturation calculated when the TOC is equal to 0 can be less than 100%, which is more consistent with the actual geological conditions of shale gas reservoirs. Because the saturation model incorporates an exceedingly large number of parameters, we propose the use of a genetic algorithm to automatically optimize those parameters. An evaluation of the Longmaxi formation-Wufeng formation shale gas reservoir in the Yongchuan block of the southern Sichuan Basin reveals that the optimized parameters are consistent with the geological conditions. The prediction accuracy of the proposed method is also higher than that of the original method, especially for the Wufeng formation, for which the number of samples is very small. Moreover, the absolute error is reduced by nearly 10%, which reflects a high accuracy. The proposed model can enhance accuracy through further improving the determination of shale gas reservoir characteristics and thus has the potential to be improved further. This method can also partially resolve problems by evaluating the saturation of shale gas reservoirs and hence could be helpful for core and well logging evaluations of the saturation, especially in overmature shales.