Lab of Data Analysis and Machine Learning in the oil and gas industry
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Faculty of Computer Science and Engineering

Laboratory of Data Analysis and Machine Learning in Oil and Gas Industry

At the present time, the largest oil fields in Russia are characterized by significant depletion of petroleum reserves and high water content in extracted products. Therefore, oil fields of complex structure (e.g., fractured-porous collectors contained bottom water) saturated with hard-to-recover non-Newton oil are increasingly involved in oil production. As the share of them grows constantly, the problems of oil recovery from such oil reservoirs and the choice of a rational regime of their operation are of particular relevance. 


Laboratory Activities

Research areas: 


— Underground hydromechanics 

— Mechanics of multiphase media 

— Nonlinear differential equations 

— Numerical methods 

— Parallel computing technologies 

— Scientific visualizations 

— 3D modeling / prototyping 

— Programming for microcontrollers and embedded devices


Projects

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01

Computer simulation of heat-mass transfer during the commissioning oil producing weill equipped with electric centrifugal pumping unit

With the use of method of computational experiment this software allows us to study the characteristics of the transient modes of well operating and the cyclic development of fractured-porous reservoir saturated with non-Newtonian oil in the presence of bottom water

02

The interactive 3D-plant of the oil producing well surface equipment

Сan be used for demonstration of the methods and approaches to the optimal control such a development process with the simultaneous visualization of the heat-mass transfer in all its parts. This feature may be utilized for organization of trainings for the specialists of oil-and-gas service companies providing the possibilities to develop their skills without the risks of damaging expensive real equipment

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