Abstract
Fluid identification is vital to the characterization of gas-bearing reservoirs. From the perspective ofporoelasticity, Russell fluid factor is sensitive to the conventional (sand gas) and unconventional (shale gas, or tight gas) reservoirs. In a saturated isotropic medium, however, most amplitude-variations-with-offset/angle (AVO/AVA) inversion methods based on the approximate formulas affect the estimation of Russell fluid factor due to the low accuracy of the approximations in the range of moderate to large incidence angles. We first introduce a saturated seismic wave velocity associated with Russell fluid factor into the Zoeppritz equations to describe the saturated porous media. Combining perturbation theory and Taylor expansion, we solve the objective function by dealing with the gradients of derived reflection coefficient. Using an iterative reweighted least-squares algorithm, we propose a joint multi-wave Bayesian AVA inversion to estimate Russell fluid factor. Test results of synthetic data with moderate random noises show that the elastic and fluid parameters can be reliably predicted in saturated porous rock. Tests on field data sets verify the robust estimation of Russell fluid factor to realize the fluid identification in a shale gas reservoir. Both of cases indicate that joint multi-wave inversion can improve prediction accuracy of model parameters compared with single PP-wave inversion when the amplitude quality of converted wave data is better.
NSTL