Why oil and gas companies are not always ready to implement digital twins

28.08.2026       

The technology requires a ready-made production infrastructure

Digital twins are used in the oil and gas industry to model technological processes, monitor equipment, analyze deviations, and predict possible failures. However, the introduction of such technology does not begin with the choice of a software platform. The company needs reliable production data, measuring instruments and automation systems that allow it to regularly receive information about the actual condition of equipment and processes. Experts note that it is the quality of data and the digital maturity of the enterprise that remain one of the main limitations for the large-scale implementation of digital twins.

The equipment must provide the necessary data

For a digital model, data on the operating parameters of technological equipment and production processes is important. At existing facilities, some of the equipment may be equipped with outdated measuring instruments or lack the necessary data transmission interfaces. As a result, the company has to additionally install sensors, modernize monitoring systems, or address issues of compatibility of old equipment with modern information solutions. Such tasks directly affect the cost and timing of the project.

Integration of production systems is needed

Another task is to combine data from different information systems. Automated process control systems, SCADA, MES, dispatch control systems and other solutions can be used simultaneously at an oil and gas enterprise. If they work separately, and the data has different formats and sources, preparing information for a digital twin requires additional integration and processing. Therefore, the digital twin should be considered as part of the digital production infrastructure, and not as an isolated software solution.

You can start the implementation with a specific object.

A step—by-step implementation may be a practical option for an enterprise - from a separate equipment or technological process to a larger-scale model. This approach allows you to check the quality of the source data, the operation of integration systems and the ability to obtain a measurable production effect. According to market participants, local projects related to a specific expensive production task have a more predictable economy than creating a digital twin of a large production complex. Read more about the development of the digital twins market in the Kommersant article


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