## 4 Discussion  
Porosity is not the only factor affecting the elastic behavior of tight sandstone with low porosity and permeability. Under the same porosity condition, the change of seismic wave elastic characteristics mainly depends on the structural characteristics of the pores, rather than porosity. If the tight sandstone aspect ratio is assumed to be constant, a large prediction error will be introduced in an area with complex geological conditions. Hence, according to the characteristics of micro-pore structures in tight sandstone, we equated its pore space to the combination of multiple types of pores, based on inclusion theory. Meanwhile, in order to further consider the connectivity between rock pores, the connected pores and isolated pores were added to the rock matrix using logging interpretation data and the MT model. Through comparison with the experimental data, the improved model gave more accurate prediction results, which demonstrates its good applicability to the study area.  
Obviously, dissolution and fracturing contribute to increasing the storage space and the pore connectivity of tight sandstone reservoirs, and further tends to lead to the formation of high-quality reservoirs. By comparing the test data of the tight sandstone samples with the calculation results of the theoretical model, the pore aspect ratio explained the heterogeneity of the tight sandstone, and the fracture density effectively indicated the location of fracture development. Therefore, this model can provide an effective basis for the logging evaluation and seismic quantitative interpretation of tight sandstone reservoirs.  
Although we can obtain accurate microstructure information from micro-CT scanning images of rock samples, the measurement results are often limited by economic costs. Considering the problem of sample representativeness and upscaling in integrating the core and logging data, it is not suggested to use the equivalent aspect ratio of a single rock sample as the initial constraint condition. If there are sufficient core measurement data from the study area, the aspect ratio mean value and variance should be used to represent the statistical normal distribution of pores with varied aspect ratios in the multiple pore aspect ratio model. Doing so will help the improved model achieve better prediction results.  
Since the elastic constants of minerals and fluids used in the modeling process are based on the reference values obtained from previous work, the reference values of different layers and regions vary greatly, which affects the prediction accuracy of the model. Furthermore, the acquisition quality of logging data and the calculation accuracy of reservoir parameters, such as porosity and saturation, also affect the final prediction results of the theoretical model.  
Furthermore, considering that the rock pore space is composed of stiff pores (insensitive to pressure) and micro- fractures (sensitive to pressure) distributed in the rock [51], because the effective aspect ratios of the soft pores and open cracks decrease under increasing pressure, the soft pores and micro-fractures of rock samples observed in lab conditions are different than in high pressure reservoir conditions. Hence, the velocity of rock samples measured under laboratory conditions will be biased, which affects the evaluation of the prediction effect of the model. One potentially significant over-simplification was that the pressure dependence of the porosity was ignored in our modeling process, and more work is required to develop a proper effective model in the future.