Optimization of drilling fluid effectiveness based on fluid mechanics in well drilling process of one of the squares in the southwest of Iran

The speed of drilling operations has a direct effect on drilling costs and various parameters such as drilling fluid properties and hydraulic drilling affect it. Therefore, it is very important to use models with different parameters that have high accuracy. Because the relationship between these parameters is complex, a computational method is needed. Artificial neural network is a new computational method for learning that is used to predict the output responses of complex systems. In this paper, the neural network is used to predict the drill penetration rate by considering the parameters of drilling fluid and multilayer artificial intelligence models and radial base are used to detect and predict drilling speed as output parameters.