Abstract

Summary Historically, the concept of “reservoir drive” aimed to simplify the mathematical modeling in reservoir engineering. Within this framework, the energy of the reservoir, particularly its aquifer, was idealized, leading to classifications such as “partial waterdrive,” “full waterdrive,” “gas cap drive,” and so forth. However, in reality, all existing energy sources interact simultaneously within reservoirs. Accordingly, this study aims to develop a new concept for a more realistic description of reservoir drive mechanisms and evaluation of reservoir energy performance. Numerous computer simulations have revealed a strong correlation between the ratio of relative changes in pore volume to relative changes in reservoir pressure and the reservoir’s energy nature and activity level. Moreover, the noted ratio did not depend on production technology, pressure/volume/temperature properties of hydrocarbon systems, rheological properties of reservoir rocks, or other factors. Based on this correlation, specific parameters termed as Jamalbayli Indexes (JI) have been identified to quantitatively describe reservoir energetic performance. JI consist of two parameters. One of them describes the relative change in pore volume per unit of relative change in reservoir pressure, and the second is the relative change in pore volume per unit of relative change in formation porosity. Here, “relative change” means a change in a parameter relative to its original value. These parameters are dimensionless and can have values around or equal to unity. A new conceptual framework for describing reservoir drive mechanisms based on JI has been formulated. According to this framework, reservoir drive mechanism is determined by comparing the computed JI values with unity rather than relying on subjective assessments of the trend of some functional dependencies. For the first time, it has become possible to express the reservoir drive performance quantitatively and determine the level of energy activity of the reservoirs with the help of JI. Additionally, a technique has been developed to evaluate the numerical values of JI for specific oil (including volatile oil) deposits based on the production data at any stage of production. The proposed methodology was tested using data from the eighth horizon of the Russkiy Khutor field in Russia. The test results not only confirmed the reliability of the obtained model but also demonstrated the adequacy of the proposed concept as a whole. Summarizing the results of other works by the authors, the adequacy of the proposed concept for both oil, gas, and gas condensate deposits has been confirmed. The research findings are expected to contribute to updating the traditional principles used for the mathematical problem statements in fluid flow in porous formations. Additional Key Terms and Phrases Reservoir Drive Mechanism; Early Determination Methods; Reservoir Performance Analysis; Production Data Interpretation; Enhanced Oil Recovery; Reservoir Management; Drive Mechanism Identification; Reservoir Fluid Dynamics; Production Rate Analysis; Reservoir Engineering Techniques; Field Development Planning; Reservoir Simulation; Pressure/Volume/Temperature (PVT) Analysis; Production Monitoring and Evaluation drive mechanisms; production data analysis; volatile oil; Jamalbayli indexes; drive performance indexes

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