It is known that an increase in the volume of production in any sphere of production as a consequence increases the intensity of anthropogenic impact on the environment, including the atmosphere. This problem is especially typical for oil refineries. On the one hand, this is due to the complexity of oil refining processes and the release of various hydrocarbon compounds into the atmosphere during processing. Therefore, when implementing sustainable ecological and economic development in the Azerbaijani regions that are associated with oil refining, an increase in the volume of products should not create an increase in environmental impact. This problem is considered one of the factors directly affecting the economic situation of the enterprise, as well as creating certain environmental, social and economic problems for society as a whole. The purpose is to study the possibility of using the correlation-regression method in solving the problem of determining the presence of the decapling effect. The relationship between the volume of petroleum products produced and the amount of pollutants released into the atmosphere is random and is characterized by stochastic and statistical dependence. At the same time, on the basis of a mutual comparison of the methods of correlation and regression analysis and the method of production function, the effectiveness of correlation and regression analysis is determined. The methodological basis of the work was the scientific works of scientists-economists, mathematicians providing the definition of the decoupling effect at industrial enterprises. In the presented methodology, the obtained estimates of the performed in real time vary depending on the values of the set parameter. When developing the presented methodology, the STATISTIKA software package was used. This program was developed by StatSoft. Based on the obtained and experimentally verified data, the equation of linear regression dependence is determined. During the research, it was found that in some cases it is not possible to evaluate the statistical characteristics of a random variable or it is accompanied by serious errors. Therefore, when processing data, instead of mathematical expectations and variances, we used selective mathematical expectations and variances. The analysis of the ecological and economic situation of oil refineries based on correlation and regression analysis allows us to determine the presence of the decapling effect. The obtained correlation coefficient between the volume of production oil products and the volume of emissions into the atmosphere shows that there is no statistically significant relationship between these parameters. Thus, there is an achievement of the decoupling effect between the production of petroleum products and the volume of emissions of pollutants into the atmosphere.