Investigating the dependence of shear wave velocity on petrophysical parameters

The dependence of the shear wave velocity (Vs) of water-saturated reservoir rocks on petrophysical parameters was investigated. Two general regression neural network (GRNN) models were developed to predict Vs of sandstones, shaly sands, and carbonate rocks as a function of the compressional velocity (Vp), grain density (ρg), clay content, porosity (ϕ), permeability (k), and the cementation exponent (m) at a fixed effective stress and frequency. A set of 59 sample measurements of clean and dirty sandstones and carbonate rocks was used to train and test the GRNN models.