Neural network modeling of a bituminous reservoirs heating and research of different factors influence
UDC: 004.855.5:004.942
DOI: 10.33285/2782-604X-2022-9(590)-13-17
Authors:
MUKHUTDINOV AGLYAM R.
1,
EFIMOV MAXIM G.1,
VAKHIDOVA ZULFIYA R.2
1 Kazan National Research Technological University, Kazan, Russia
2 "TISBY" University of Management, Kazan, Russia
Keywords: artificial neural network, modeling, bituminous reservoir, software module, heating, energy-saturated material, distance, mass
Annotation:
It is known that thermal methods of a productive formation treatment are widely used to stimulate oil production in operating wells. Thermal impact is one of oil production main stages when developing bituminous reservoirs. Overcoming the low mobility of bituminous oil and increasing the efficiency of a reservoir downhole treatment method is possible through the use of the universal computing capabilities of modern software tools that have the broadest possibilities of modeling such systems. They allow, based on empirical experience alone, to build neural network models that facilitate the extraction of knowledge from data, identify features and actively use them to solve specific practical problems. The article studies and presents the possibility of neural network modeling of the process of a bituminous reservoir heating using the developed universal express method for creating a neural network model on a small number of examples with a low forecast error. The results of the study of the influence of various factors on the heating process are presented.
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