Prediction of drilling rate using artificial neural networks in oil field

Today, cost and time are very important, Drilling industry is also one of the most expensive industries, so it is necessary to save time and cost of Drilling and also consider solutions for it. In Drilling operations, by choosing the right tools used and also accurate and timely forecasting of parameters and possible problems, this operation can be performed in less time and cost. In this study, for estimating the accuracy and efficiency of predictive models of penetration rate, coefficient of determination (R۲) and Root Mean Square Error (RMSE) have been used. The database was then analyzed through Artificial Neural Network (ANN) to generate an optimum predictive model. Results showed that there is a close relation between actual (measured) data and predicted data with R۲=۰.۹۸ and RMSE=۰.۰۲

کلیدواژه ها:

Drilling ، coefficient of determination ، Root Mean Square Error ، Artificial Neural Network