It is essential to dtermine petrophysical properties of reservoir rock in exploration and poroduction processes.There are several methods in which predicts such properties  and these methode are evolving every day. BISQ model is a novel model that it’s accuracy in determination of seismic properties of reservoir rock is confirmed by different researchers. This model predicts seismic properties such as p-wave and s-wave velocity and quality factor using some petrophysical and elastic properties of reservoir rock. Because of a high order of non-linearity in the BISQ model, inversion of associated petrophysical properties using conventional linear methods is not feasible. So in this paper we used a global optimization method to detemine petrophysical properties of reservoir rock. Inversion process includes two major step. First one is a physical or petrophysical model in which predicts data. And second one is a mathmatical method in which estimate model parameter through an objective function. Selection of mathmatical method depend on physical or petrophysical modle that pridicts data. In this case the petrophysical model is non-linear so we should select a robust mathmatical method that has capibility of determination global optimum point in a highly non-linear space. We use a hybrid genetic algorithm(HGA) in which employs some self adaptive concepts to enhance search ability , diversity , and quality of answers in comparsion with conventional GAs. Here we first introduce inverse methode then the methode is applied on a synthtic and a real data and the results are analyzed.