Methodology for optimizing high-viscosity oil production using a nature-inspired algorithm

To maintain reservoir pressure above the saturation pressure of oil with gas and effectively displace oil from the reservoir, flooding remains an established operating practice in the fields of the Russian Federation. In recent years, theoretical and practical research into this method of operation has been actively developing. Thus, the low efficiency of oil displacement by flooding has been established in conditions of low oil mobility compared to water, which is especially evident in heterogeneous reservoirs. The highest reduction in the efficiency of the process of replacing oil with water is observed during the development of highly viscous oil fields. For these difficult conditions, polymer flooding technology is especially promising, because the polymer, thickening the water, increases its viscosity, increasing the displacing ability of water. However, for the practical application of polymer flooding, it is necessary to optimize the process by justifying technological parameters (polymer concentration, injection rate) to achieve maximum efficiency. For this purpose, the paper presents a methodological approach based on the use of a nature-inspired optimization algorithm ‒ a flock of migratory birds, used to solve a number of practical nonlinear optimization problems. Keywords: flooding; polymer compositions; mathematical modeling; optimization objective function; nature-inspired algorithms; migrating bird algorithm; net present value.