Abstract
Rate of penetration is one of the most significant drilling parameters for optimizing the cost of drilling geothermal wells. Many drilling variables affect the rate of penetration. Several correlations have been introduced to predict rate of penetration by involving some of the variables. In this study, a new empirical correlation based on an optimized nonlinear regression model was developed to predict ROP. Several drilling variables i.e. weight on bit, rotation-per minute, compressed air flowrate, true vertical depth, hole diameter, and foam flowrate were included into the correlation. SPSS (Statistical Product and Service Solutions) Software was applied to generate eight equations. The most appropriate equation was selected by comparing the calculated and measured ROP. The selected equation has average percentage difference of 14.6%. In addition, the procedure can be applied to estimate the effect of drilling variables on the accuracy of the model.
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