Industrial Automatic Control Systems and Controllers Annotation << Back Machine Learning as a Novel Approach to Process Automation and Production Cost Reduction in Oil and Gas Industry D.A. Baybarov This study proposes automating technological processes using modern machine learning methods to explore the location of new wells, increase oil recovery, reduce production costs, and improve forecasting oil production in the field. As optimization parameters, specific mechanical energy to quantify drilling efficiency and mechanical drilling rate were taken. The paper presents methods for predict ing and optimizing drilling performance based on specific mechanical energy technologies and with account taken of the advantages and disadvantages’ evaluation. Apart from this, it provides a comparative analysis of the drilling rate prediction under two existing machine learning models with actual data given. Keywords: machine learning; random forest method; support vector method; mechanical drilling speed; specific mechanical energy. DOI: 10.25791/asu.9.2021.1308 Pp. 10-18.