In the ever-evolving landscape of oil and gas exploration, the ability to predict reservoir behavior with precision is paramount. Enter Dmitrii A. Beltiukov, a researcher affiliated with an unknown institution, who has developed a groundbreaking approach that could revolutionize how geologic-hydrodynamic models are adapted to real-world conditions. His work, published in ‘Известия Томского политехнического университета: Инжиниринг георесурсов’ (News of Tomsk Polytechnic University: Engineering of Georesources), focuses on the automatic adjustment of relative phase permeability curves, a critical component in geologic-hydrodynamic modeling.
Beltiukov’s research addresses a longstanding challenge in the industry: the multi-iterative process of adapting geological and hydrodynamic models to the development history of a field. This process is fraught with uncertainty, making it both time-consuming and resource-intensive. The quality of this adaptation directly impacts the reliability of forecast indicators, which in turn influence key design decisions. By optimizing the setting of relative phase permeability curves, Beltiukov’s approach promises to significantly reduce these costs.
The method, implemented as a machine code in Python, has shown promising results in initial testing. Six deposits, including both terrigenous and carbonate reservoir types from the Volga-Ural and Timan-Pechora oil and gas bearing provinces, were used to validate the approach. The results were striking: the actual curves of relative phase permeabilities, adjusted during the multi-iteration adaptation of the hydrodynamic model, showed high convergence with the calculated model curves.
But the real test came with a complex carbonate object featuring high fluid viscosity. Here, the method demonstrated its robustness by adjusting integral parameters of oil production and water cut within a single iteration, achieving a high degree of convergence. This is a game-changer for the industry, particularly for fields with high-viscosity oils, where traditional methods often fall short.
The implications of this research are vast. For energy companies, the ability to quickly and accurately adapt geologic-hydrodynamic models could mean more efficient field development, reduced operational costs, and improved forecasting accuracy. This, in turn, could lead to better resource management and more sustainable practices in the energy sector.
Beltiukov’s approach not only streamlines the adaptation process but also enhances the reliability of the models, which are crucial for making informed decisions. As the industry continues to face challenges such as declining reserves and increasing operational complexities, innovations like this could pave the way for more efficient and effective reservoir management.
The energy sector is on the cusp of a significant shift, and Beltiukov’s work is a testament to the power of innovative thinking and technological advancement. As we look to the future, the automatic adjustment of relative phase permeability curves could become a standard practice, reshaping how we approach geologic-hydrodynamic modeling and ultimately, how we harness our energy resources.
