Application of the digital twin of the field to control the development and automation of the assessment of the energy state of the reservoir

Background. The digital twin of the field is a modern and powerful tool for linking various components of the integrated model and field data on the operation of wells. Thanks to deep integration and access to up-to-date online data, this tool allows you not only to automate standard processes for interpreting research data, but also to implement your own for a better understanding of the energy state of the reservoir.

Aim. The purpose of the work is to describe a methodology for predicting the behavior of the pressure recovery curve (CVD) and estimating reservoir pressure in the case of a short-term well shutdown, the duration of which is insufficient for the formation of a full-fledged CVD and its subsequent full-fledged interpretation.

Materials and methods. The initial materials for the work were the measurement data and the results of the interpretation of hydrodynamic studies of wells, data on the operating mode of the well and the geological and physical characteristics of the productive layers of the studied field. To optimize the calculation of regression coefficients, a script has been written in the C# programming language. Testing and implementation of the methodology was carried out at the wells of the field of Gazprom neft companу group.

Results. The technique used in the work does not solve the problem of determining the entire spectrum of filtration parameters and characteristics of reservoir opening perfection, and also does not exclude the conduct of full-fledged CVD. However, it makes it possible to eliminate ambiguity in the interpretation of long-term pressure stabilization curves (CSD) recorded during stable well operation, control reservoir production, increase the coverage of the well fund by research without additional long-term studies, and, accordingly, production losses.

Conclusions. The advantages of the technology include: 1. the ability to operationalize the process of assessing the energy state of a deposit and, as a result, improve the quality of decisions made during field development, 2. the ability to implement digital Oil Field monitoring tools, 3. ease of soft ware implementation and implementation into existing soft ware tools. It was found that the accuracy of forecasting depends on the quality of the initial data describing the filtration and capacitance properties (FEZ) of an operational facility or regions with similar development conditions. The results of the algorithm allow us to conclude about the effectiveness of the proposed solution and show the importance of these technical stops in understanding the dynamics of reservoir pressure.

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