Reducing electricity consumption in oil production

The modern world cannot be imagined without oil production and oil refining. Most of the technological processes of oil production and transportation are implemented using electric energy. Moreover, the most energy-intensive industries are mechanized production, maintenance of reservoir pressure, preparation and pumping of oil and gas. The modern oil production process is complicated by the growth of hard-to-recover deposits, increased water cut, product paraffinization, etc. Additional difficulties are associated with the fact that most of the fields are in the late stages of operation, which are characterized by a decrease in oil production due to the extraction the huge amount of the reserves from the bowels. All this leads to an additional increase in electricity consumption. The article considers the problem of reducing electricity consumption in the oil industry in oil production. The use of even the latest types of oil-producing equipment, often does not lead to a reduction in energy consumption. Therefore, a method is proposed for reducing the level of energy consumed by properly adjusting the geological and physical values (characterizing the structure of the deposit) and technological (characterizing the method, production technology, and the effect of interfering injection wells) performance indicators of oil wells, affecting the coefficient of productivity and the coefficient of coverage of the reservoir by water flooding. The regulation of indicator values is achieved through the selection of geological and technical measures based on the developed regression models and the multicriteria optimization method - finding the Pareto set. Even small mistakes and shortcomings in the selection and planning of optimal geological and technical measures can be accompanied by great damage to the oil company. This article presents an acceptance support algorithm to improve the efficiency of oil wells, which allows to select the most effective geological and technical measures for the oil well in question, which increase the productivity coefficient and reduce the value of the coefficient of reservoir coverage by water flooding. The article proposes a structural diagram of a decision support system for specialists and heads of geophysical services, describes in detail the functions of all the modules that make up the decision support system.