This publication presents the part of the research results and practical results obtained by the authors regarding the hybrid use of economic-mathematical modelling, knowledge-oriented decision support technology of an oil and gas production company using fuzzy logical inference. The purpose of this research is the development of theoretical provisions of modelling and knowledge-oriented decision support means at the macro level of oil and gas production companies. The purpose of the work determined the solution of the following tasks: -development of science-based recommendations regarding the architecture of a knowledge-oriented DSS of an oil and gas company, the basic model of knowledge presentation, features of the logical conclusion mechanism, etc.; -development of a complex system of economic and mathematical support for decision-making at the macro level of an oil and gas production company in modern economic conditions. The object of the study is the oil and gas production industry. The subject of the research is information processes, economic-mathematical models and knowledge-oriented methods and means of supporting the adoption of management decisions at the strategic level on economic and production issues of the domestic oil and gas production project. Methods/Approach: Economic and mathematical methods, methods of artificial intelligence, methods of logical generalization, expert evaluations and situational approach are used to solve the tasks set in the work. Results:The main scientific result of the work consists in the creation of the concept that allows creating a hybrid DSS of an oil and gas company on the basis of the developed systems of economic and mathematical decision-making support at the macro level of an oil and gas production company, focused on knowledge of technology and intelligent technologies. Conclusions: The scientific, theoretical and applied practical solutions proposed in this publication are universal for implementation by both state and private oil and gas resident and non-resident companies for emerging markets, however, in order for a specific oil and gas company to obtain special additional competitive advantages over others, additional industry-specific Big Data Analysis of collected and stored heuristics, expertise and project development are required.

The following factors were studied and taken into account in the process of economic and mathematical modeling of an oil and gas company as a

During the last years, in most countries of Eastern Europe (and Ukraine in particular), even a simple reproduction of onshore hydrocarbon reserves was not ensured. Achieving the possible level of self-sufficiency in fuel and energy resources is a fundamental task of national economies, without which the successful implementation of economic, scientific, technical and social programs aimed at ensuring state independence and stability in Europe is impossible. However, the onshore oil and gas industry of the countries of Eastern Europe with significant volumes of unexplored oil and gas resources, with the cost of oil and gas several times lower than world prices, the presence of a significant number of oil and gas industries, drilling and geophysical enterprises, oil refineries, and an extensive network of oil and gas pipelines , highly qualified production teams allows, with their effective use, not only to stabilize, but also to significantly increase the production of oil, gas and condensate in the future. An important reason for the drop in oil and gas production volumes is insufficient management efficiency of the cycle of parallel business processes of the oil and gas company: field exploration, their arrangement and development, production and sale of oil and gas. The solution is the application of effective economic-mathematical modeling at the strategic level of management and the use of knowledge-oriented decision-making support tools as an integral component of the complex information system of an oil and gas company. Objectives: Therefore, the issues of: development of a complex system of economic and mathematical support for making fair and timely investment decisions at the macro level of an oil and gas production company, effective application of knowledge-oriented hybrid methods and technologies are becoming particularly relevant. Methods/Approach: The paper uses a mathematical apparatus of the method of fuzzy logic, decision trees, data mining, knowledge-oriented decision support, theory of investment management and expertise in the field of management of oil&gas exploration and production local and international investment projects. Results: first proposed the decision tree diagram of the effective investment management process of a oil and gas company in the search for hydrocarbons in modern economic conditions is proposed; received further development of the principles of hybrid application of intelligent technologies and knowledge-oriented basis and the problem of handling uncertainty while supporting investment decisions of an oil and gas company; first proposed two related prognostic models are proposed: the seismic impact model and a drilling impact model; first proposed two algorithms/models based on economic-mathematical modeling with elements of fuzzy knowledge to support decision-making of the tender&controlling committee of oil&gas production company. Conclusions: Based on the foregoing, it can be concluded that it is efficient to use developed by authors hybrid, knowledge-oriented inves...

Oil and gas companies in order to maintain their efficiency in the conditions of: liberalization of markets, globalization, increased competition, reduction of consumer loyalty, constant variation in oil and gas prices, further development of Industry 4.0 and the Big Data factor, growing costs for drilling and completion – must have a flexible environment of information technologies that enables seamless and efficient sharing of knowledge throughout the company and along the entire value chain. One of the elements of this task is the effective use of hybrid knowledge-oriented decision support systems (DSS). This, in particular, determines the future stage of complex author's research – the development of a complex perforating knowledge management policy of an oil and gas company, the key tool for the implementation of which will be the hybrid, knowledge-oriented DSS considered in this publication.The form of knowledge representation has a significant impact on the characteristics and properties of a knowledge-oriented system. Therefore, based on the specifics of the exploration and development of oil and gas fields and the main advantages of the rule-oriented model of the DSS knowledge base, it is possible to conclude that it is necessary to use the KB rule-oriented basis for the DSS of an oil and gas production company. The rule-oriented subsystem is the main one in the knowledge-oriented DSS of an oil and gas production company, in fact, other subsystems provide it with analyses, assessments, and knowledge. Namely, the final product of the system: recommendations for making management decisions is carried out by a rule-oriented subsystem. In general, scientifically based conclusions were obtained regarding the knowledge-oriented architecture of the intellectual DSS of an oil and gas company, the basic model of knowledge presentation (production), the features of the mechanism of logical conclusion (direct logical conclusion), the conflict resolution procedure (a method of ordering products), etc. In the oil and gas industry, DSS built according to a hybrid approach have the greatest application potential – which are a powerful tool for solving complex specific problems of an oil and gas company. Therefore, in this work, the principles of hybrid application of intelligent technologies and the knowledge-oriented basis of DSS of an oil and gas company were further developed.