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Summary The article reviews the development and implementation of a digital twin for one of the large fields of LUKOIL-West Siberia LLC. The project team has developed an integrated asset model (IAM) of an oil field at a late stage of its development, which is used both for making managerial decisions and in the operational work of the engineering and technical service. The IAM includes simplified models of reservoirs, models of wells and gathering systems, as well as simplified models of plants. The resulting model can produce short-term assumptions regarding production levels (up to 1 year) and is highly sustainable, which is confirmed by the examples given in this article as to the application of IAM for various production tasks. The developed automated tools allow making prompt decisions to optimize well stock operation, as well as to reveal deviations in the process parameters of downhole pumping equipment and metering facilities. The use of IAM tools enable production functions to perform many application tasks related to forecasting well operation modes and evaluating the existing production capacities of the field. The cases presented in this paper serve as a good practice for application of the IM by assets in their activities and can be implemented for similar brownfields.

As part of the LUKOIL smart-field project, the company develops and implements integrated modeling solutions in all its assets. LUKOIL-West Siberia, a subsidiary company that is LUKOIL's leading hydrocarbon producer, has chosen two pilot assets in Yamal to implement such technology solutions. This paper describes the creation and implementation of two integrated models, as well as model of gas transportation system from a group of fields located in the Yamal and the Krasnoyarsk region. Each integrated model includes the following components: reservoir – well – gathering system – processing. The results of the project implementation allowed to increase production performance and economic viability of the operator company and provided technology that enabled to forecast production rates with high accuracy.