An integrated methodological approach to substantiating the properties of high-viscosity oils using the example of the Karazhanbas oil field

Abstract

Rationale: A characteristic feature of the modern stage of oil field development is the increase in the share of hard-to-recover oils, which mainly include heavy, highly viscous oils. This is due to changes in the structure of oil, an increase in the water cut of produced oil, geological and geophysical characteristics and conditions of oil occurrence that are unfavorable for extraction. The reserves of such oil significantly exceed the reserves of light and low-viscosity oil and, according to experts, they amount to at least 1 trillion tons. In industrialized countries they are considered not so much as a reserve for oil production, but as the main basis for its development in the coming years. The peculiarity of heavy oil is explained by its composition and PVT properties, which have a fairly serious impact on production.
 Target: Application of an integrated approach to substantiating the properties of high-viscosity oil and tools for mathematical modeling of the phase state of fluids in order to increase the reliability of reserve calculations and the efficiency of the oil field development.
 Materials and methods: The scientific work was based on the results of geochemical studies (fingerprinting and biomarker analysis), experimental data from rheological studies and the results of modeling the phase state of fluids.
 Results: It is proposed to use an integrated approach to data interpretation and compositional calculations, which make it possible to narrow the range of uncertainty and explain the huge variation in the values of physicochemical parameters across samples.
 Conclusion: An integrated approach to analyzing the results of PVT experiments, together with geological and field data and the results of geochemical studies, provides high-quality data that allows you to make strategic decisions on the oil field development, conduct accurate resource assessments and predict hydrocarbon production.