The article presents a methodology for predicting the behavior of the pressure build-up curve and estimating reservoir pressure for the case of a short-term well stop. Their duration is not enough to measure a build-up curve long enough and its subsequent full interpretation. A regression analysis method was used in order to identify the most accurately predictive behavior of the pressure buildup curve during a real well test based on various models tested on real well operating data. A C# programming language script was written to optimize the calculation of regression coefficients. Testing and application of the methodology was carried out at the wells of the field named after A. Zhagrin of Gazpromneft-Khantos LLC. A new approach has been obtained for predicting pressure build-up and estimating reservoir pressure, which allows increasing the coverage of wells by testing without conducting additional long-term well testing and, accordingly, losses in production. The proposed approach does not exclude long-term stops of wells to pressure build-up, but allows to understand the energy state of the reservoir in operational activities, as a result, to improve the quality of the decisions made in the process of field development. The results of the algorithm allow us to conclude the effectiveness of the proposed solution and show the importance of these technological stops in understanding the dynamics of reservoir pressure. The advantages of the developed approach are the possibility of implementation in Digital Oil Field monitoring tools, ease of program realization and integration into existing software tools. The accuracy of prediction depends on the quality of input data describing the properties of the reservoir or regions with similar field conditions.
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