 Hybrid application of decision trees, fuzzy logic and production rules for supporting investment decision making (on the example of an oil and gas producing company)Maxim Krasnyuk (),
Iryna Hrashchenko (),
Svitlana Goncharenko () and
Svitlana Krasniuk ()
Access Journal, 2022, vol. 3, issue 3, 278-291 Abstract: 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 investment decision support for oil and gas production projects in Ukraine and other countries of Eastern Europe. Keywords: investment project; oil&gas exploration and production; decision tree; production rules; fuzzy inference (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:aip:access:v:3:y:2022:i:3:p:278-291 DOI: 10.46656/access.2022.3.3(7) Access Statistics for this article More articles in Access Journal from Access Press Publishing House |
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