The main part of hydrocarbon production in Russia is represented by old oil and gas producing regions. Such areas are characterized by a significant decrease in well productivity due to high water cut and faster production of the most productive facilities. An important role for such deposits is played by stabilization of production and increase of mobile reserves by improving the development system. This is facilitated by various geological and technical measures. Today, an urgent problem is to increase the reliability of the forecast of technological and economic efficiency when planning various geological and technical measures. This is due to the difficulty in selecting candidate wells under the conditions of the old stock, the large volume of planned activities, the reduction in the profitability of measures, the lack of a comprehensive methodology for assessing the potential of wells for the short and long term. Currently, there are several methods to evaluate the effectiveness of geological and technical measures: forecast based on geological and field analysis, statistical forecast, machine learning, hydrodynamic modeling. However, each of them has its own shortcomings and assumptions. The authors propose a methodology for predicting the effectiveness of geological and technical measures, which allows one to combine the main methods at different stages of evaluating the effectiveness and to predict the increase in fluid and oil production rates, additional production, changes in the dynamics of reservoir pressure and the rate of watering of well production.

The article describes the original technique of predicting the effectiveness of hydrochloric acid treatment of the bottom hole zone of a carbonate reservoir. The technique consists in determining the technological effectiveness of the oil recovery stimulation procedure at productive wells using hydrodynamic simulation based on the calculated value of skin factor change. In the course of the study, a number of parameters affecting the intensity of flow coefficient decline in the near-wellbore zone during acid treatment have been established. The paper presents a comparison of data on the actual change of the skin factor after acidizing jobs at the fields of Perm Krai (Russian Federation) and the calculated values obtained using the presented technique. This scientific research includes an example of practical application of the proposed technique for the target well of the Kokuyskoye oil field in Perm Krai, its results with a minor deviation coinciding with the actual values of the flow rate. In the conclusion to the study, it is noted that using the proposed technique, recommendations can be provided on the selection of acid composition and technology of its injection into formation for the preliminary evaluation of the cost effectiveness of the designed procedure.

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This study presents a methodological approach to forecasting the efficiency of radial drilling technology under various geological and physical conditions. The approach is based upon the integration of mathematical statistical methods and building machine learning models to forecast the liquid production rate increment, as well as to forecast technological indexes using a hydrodynamic model. This paper reviewed the global practice of radial drilling and well intervention efficiency modeling. The efficiency of the technology in question was analyzed on the oil deposits of the Perm Territory. Mathematical statistical methods were used to determine the geological and technological parameters of the efficient technology use. Based on the determined parameters, machine learning models were built, allowing us to forecast the oil and liquid production rate. A script was developed to integrate machine learning methods into a hydrodynamic simulator. When the method was tested, the deviations in the difference between the actual and the forecast cumulative oil production did not exceed 10%, which proves the reliability of the method. At the same time, the hydrodynamic model allows for taking into account the mutual influence of oil wells, the dynamics of water cut, and reservoir pressure.