Automated methodology for calculating key production indicators of oil field development for business planning model

Background: In order to secure the stable and efficient operations of oil-producing companies, it is essential to forecast the profitability and ROI of the enterprise, as well as to regulate development for the next 5 years. Accurate forecasts facilitate more informed planning and decision-making, directly influencing the economic sustainability and competitiveness of the enterprise. Aim: The purpose of this study is to develop an innovative approach to automate the methodology for calculating key development indicators in a business planning model. Materials and methods: The study utilizes methods for collecting and analyzing production and geological data, empirical forecasting models, and statistical analysis techniques to enchance the accuracy and reliability of forecasts. This approach employs modern algorithms and technologies to process large volumes of data, which allows for more accurate and reasonable forecasts of key production indicators of the field development. Results: This methodology can be applied to forecast a five-year business plan and evaluate its expected implementation. It is integrated into the ‘Production planning and monitoring’ of the ABAI information system, which allows direct data export from the database, automates the monthly monitoring of production indicators, and generate reports for further export. Conclusion: The proposed method for automated planning of key production indicators of the development enhances the accuracy and efficiency of forecasting, thereby improving the quality of planning and evaluating the implementation of the business plan. This contributes to more informed and strategically validated management of oil production processes. Automation of planning processes reduces the labor costs traditionally associated with manual analysis and calculations, freeing up resources for more strategic purposes. This enables rapid responses to changes in production conditions and prompt adjustments of plans. As a result, managers can allocate resources more efficiently, minimize risks, and increase the overall productivity of oil production operations.