3rd TAGRA

During the final stage of field exploitation, a decline in oil production is observed due to reservoir energy depletion, changes in the pressure regime, reservoir rock heterogeneity, increasing water cut, and the clogging of pore channels.Significant volumes of residual oil reserves remain in such reservoirs.Accurately assessing the current state of the reservoir-well system and forecasting the outcomes of the technological measures to be implemented are of great importance for the efficient recovery of these reserves. The aim of the study is to forecast the dynamics of changes in oil production based on mathematical models following the application of a nanotechnology-based method to the productive reservoir of an oil field at the final stage of exploitation.To this end, a fourth-degree polynomial regression model, and the Segmented (Modified) Arps model were applied to evaluate the production dynamics of the selected well. The polynomial regression model made it possible to determine the trend in the actual production data.The model results have shown that production does not exhibit a consistent trend over the years, with sharp increases and decreases observed during certain periods.Arps model makes it possible to account not only for the classic production decline phase but also for the phases of increase and stabilization that occur following technological intervention.Such an approach more accurately represents the actual production dynamics in long-term forecasting. Nanotechnology-based treatment of the reservoir–well system has also been considered promising for recovering residual oil reserves.The application of nanosystems makes it possible to improve the flow of residual oil from the reservoir to the wellbore and increase current oil production.The results of the study indicate that an integrated mathematical and hydrodynamic modeling approach enables the assessment of future production dynamics, the selection of optimal parameters for technological interventions.