Modeling of reservoir oil viscosity distribution in Permocarbon oil reservoir of Usinskoye oilfield using machine learning technology
UDC: 539.3+532.546+550.832.7+004.8
DOI: 10.33285/2073-9028-2023-3(312)-43-55
Authors:
POTEKHIN DENIS V.
1,2,
PLOTNIKOV ANDREY V.2,
YUZHAKOV ALEXEY L.2,
GALKIN SERGEY V.1
1 Perm National Research Polytechnic University, Perm, Russian Federation
2 PermNIPIneft, Perm, Russian Federation
Keywords: Usinskoye oilfield, Permocarbon deposit, oil viscosity, neural network, geological model, correlation coefficient, electrical resistivity, hydrophobicity of reservoir rocks, oil oxidation, clean water mirror
Annotation:
The object of this study is the Permocarbon deposit of the Usinsk oil field, which is characterized by the presence of highly viscous oil, complex geological structure and a unique amount of reserves of oil. The article discusses the main reasons for the occurrence of high-viscosity oils, using a neural network forecasting device for dynamic viscosity for more than 800 wells to take into account the distribution of the parameter when constructing a three-dimensional geological model. The influence of redox reactions is described, the hydrogeological component and the chemical composition of the underlying waters are taken into account. The processes contributing to hydrophobization of reservoirs are considered, the viscosity changes along the area by building a three-dimensional geological model and along the section is are analyzed. In the analysis of changes along the section of dynamic viscosity and accumulated correlation coefficients of specific electric resistance and water saturation coefficient, the zones of limiting saturation, mark of clean water mirror, the level of paleocontact location (oil – water) and the borders of cycles of hydrocarbon migration are highlighted and described.
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