Estimation of Bourgoyne and Young Model Coefficients to Predict Optimum Drilling Rates and Bit Weights using Genetic Algorithms – a case study of the Faihaa Oil Field in Iraq

Abstract

Drilling optimization requires maximizing rate of penetration (ROP) by controlling parameters such as bit weight (WOB) and rotary speed (N) to reduce drilling time and cost and to mitigate hole problems. The Bourgoyne and Young model was selected to study the effects of all parameters concerned with oil well drilling (depth, pore pressure, equivalent circulating density, bit weight, rotary speed, bit tooth dullness and jet impact force) based on actual bit records for a well in Faihaa oil field. A multiple regression analysis technique and genetic algorithm procedure were employed to analyze the field data, with the results used to develop a general equation relating rate of penetration to all variables. All the constants of the model were thus determined, and the optimized bit weight calculated for different depths of well to achieve the optimum penetration rate.