استفاده از تکنیک برنامه ریزی ژنتیکی برای پیش بینی قدرت فشرده سازی یکسانی با استفاده از خواص شبیه سازی مخزن

In this study, we developed a relationship for Uniaxial Compressive Strength (UCS) based on total formation porosity, bulk density and water saturation using Genetic Programming (GP). The numerical values of these parameters, which offered rock UCS, were obtained by analyzing various logs including sonic, neutron, gamma ray and electric logs. The elastic moduli were calculated by analyzing compressional and shear sonic logs and using mathematical correlations. The rock UCS was then analytically calculated using the empirical Wang and Plumb correlations (Plumb R.A. 1994). In order to predict UCS of the formation rock using the GP technique, approximately 5000 data points associated with 3 different wells in one of the Iranian oil fields were collected and analyzed. The data points associated with one of the wells were used to structure the GP model after being calibrated with some UCS data derived from core analysis while the other two sets of the data points were employed to test the accuracy of model's predictions. The predicted UCS values using GP model were consistent and in very good agreement with the corresponding values calculated analytically using well log data.