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The purpose of the article is a systematic analysis of drilling data obtained from geological and technological measurement stations in real time, taking into account the geological characteristics of the area being drilled for further forecasting the possibility of complications and accidents during drilling and construction of oil and gas wells. Comprehensive analysis showed the lack of basic software for the recognition and prevention of complications and emergencies based on data obtained in real time. An equally important problem is the lack of reliable lithological and stratigraphic information on the description of sludge during geological and technological measurements. The list of geological and geophysical data required to solve the problem of preventing complications and accidents during the drilling of oil and gas wells has been determined. Geological and technological parameters along the wellbore depth obtained in real time were classified according to the degree of their applicability in machine learning methods.

This paper is devoted to model-based optimization of smart well controls. Reservoir models are usually far from perfect because of the limited volume and quality of the available raw data, and the methods used to construct them, therefore model-based production optimization is extremely difficult and requires constant improvement of existing as well as the development of new approaches to its solution. The paper considers examples of some important, in our opinion, development tasks and shows possible ways of solving them, as well as a brief analysis of the results obtained with the help of approaches and methods that reflect different points of view on the uncertainty of the initial information and the accuracy of the forecast. Among the tasks considered: 1) separate and combined deployment of a smart injector and an EOR method (hot water injection); 2) use of smart wells to optimize the development of a small offshore oil field. As shown in the paper, the first task proved that quite significant synergy can arise due to the combined deployment of two IOR techniques (hot water injection and a smart injector). It also highlighted that synergy is quite insensitive to the uncertainty impact. The second task showed that the use of smart wells in combination with a proactive development strategy can significantly reduce the impact of uncertainty in the reservoir characterization on the reservoir performance. The economic efficiency of the proactive strategy in the considered example was proven to be 2-4 times higher when compared with the reactive control strategy.

In the global system of division of labor, human capital is the main source of competitive advantages for national economies. Creating conditions for the increment of human capital requires constant adjustment of the stages of reproduction of labor resources to the innovative drivers of the economy. Increasing the efficiency of the process of reproduction of labor resources, designing conditions for the creation, development and accumulation of human capital is a condition for Russia's active participation in the competitive struggle on global markets. The aim of the paper is to identify and implement the subjects of the personnel support system for the sectors of the economy, updating its configuration as the basis for the expanded reproduction of labor resources, development and improvement of methodological approaches related to increasing the efficiency of reproduction in the context of Industry 4.0. As a subject of research, the author considers the personnel system, the coordinated activities of the subjects of which will create conditions for the growth of human capital and ensuring the economic growth of the national economy. The results of the study are intended for designing a system of personnel support for economic sectors.