Seismic Wave Property Of The Vertical Directional Fracture Medium And The Fluid Prediction

When a shear wave transmits in the fracture, it will split into SH wave and SV wave. The split includes the variation of the polarization direction and the energy distribution. The energy is related to the angle between the initial polarization direction of the shear wave and the transmission direction of the shear wave.In the paper, with the relations between the velocities and attenuation coefficient of quasi-longitudinal wave and two quasi-shear waves and the fracture characteristics in the vertical directional fracture medium, we calculate some fracture models, and describe the influence of the velocities and the attenuation coefficients due to fracture density, incident angle and fracture aspect ratio. After that, we analyze the variational rule with the changes of fracture characteristics, discuss and summarize the propagation characteristics of seismic waves in the EDA medium. Therefore, seismic wave velocity and attenuation may be much effective in the fluid prediction.It's one important goal of reservoir prediction to identify the fluid content in the stratum using seismic data. The paper summarizes and classifies the fluid identification factors in the form of the power of parameter dimension, then obtains a generalized function of fluid identification factors. The function is based on the P-wave impedance and the S-wave impedance in order to select different fluid identification factor with the existing impedance information from different demands. From the Gassmann's relation, the paper analyses the impacts of elastic parameters, velocities and impedances to the rock filled with different fluid contents, and confirms which parameter is sensitive, more sensitive or no sensitive to the fluid contents. Based on this, the paper proposes a new high sensitive fluid identification factor (σ hsfif) Taking example for wet sandstone and gas sandstone, the paper compares the fluid sensitivity to different fluid identification factors. The result shows that σ hsfif is more sensitive to the fluid contents than the others. Using the idea and the method of σ hsfif, a new fluid identification factor can be constructed for demand and condition in order to satisfy different task of reservoir prediction.