The relevance of the researched problem based on the need of digitalization of elements in the production chain, implemented in oil companies. The purpose of this process is to obtain benefits in the formation of digital models of physical and economic processes underlies on the application of modern approaches to data processing, that includes the usage of both high-performance computing systems and machine learning. The article presents the method of forming the long - term investment program for the effective development of oilfields. The leading approach to the study of this problem is the use of modern mathematical methods to maximize the automation of this process. The article presents the main guidelines for the automated formation of the investment program methodology, to determine the most efficient geological and engineering activities for the oilfield reserves. It also performs automatic generation of many scenarios with different distribution of the proposed geological and engineering activity numbers by years; calculates the technical and economic indicators of oilfield development for each possible scenario formed and uses high - performance calculations to cover the most complete set of different investment planning options. The developed methodology allows planning investments for the development of all oil fields of an oil producing company using optimization methods and machine learning in the long term.

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