Optimization of flooding of Srednebotuobinskoye NGKM based on hydrodynamic modeling of flow lines

Currently, the problem of reducing the efficiency of reservoir pressure maintenance systems at late stages of field development with highly heterogeneous reservoirs is a serious one for the oil and gas industry. This paper considers the Srednebotuobinskoye oil and gas condensate field (SBNGKM), which is characterized by highly heterogeneous reservoir, water cut in some wells exceeding 95%, and low water injection efficiency. In this paper, waterflooding optimization using the streamline method was applied for the first time for the conditions of one of the largest fields in Yakutia – SBNGKM. The objective of the work was to increase the efficiency of reservoir pressure maintenance by redistributing injection between injection wells using hydrodynamic modeling of streamlines. The research materials included a three-dimensional hydrodynamic model of the Bt formation of the SBNGKM central block in the tNavigator software, historical data on 37 production and 15 injection wells for the period 2010-2021. An algorithm for redistributing injection with an increase in volumes in highly efficient wells by 20-30% and a decrease in low-efficiency wells by 15–40% was implemented. The results showed an increase in average injection efficiency by 41%, a decrease in water cut by 3.2% and an increase in cumulative oil production by 65,414 tons over a 10-year forecast period. Practical significance is confirmed by an increased ultimate oil recovery factor by 1.7% without capital expenditures. The prospects of the study are associated with the development of adaptive algorithms for automatic optimization based on machine learning and the integration of real monitoring systems for filtration parameters. The implementation of the proposed methodology can significantly increase the economic efficiency of developing complex reservoirs at a late stage of operation due to the rational use of the existing well infrastructure and water resources.