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The development of the oil industry is accompanied by a technogenic impact on the environment. According to various estimates, annual losses of hydrocarbons can reach 15% of the produced volumes at the transportation stage alone. These losses are accompanied by the formation of more than 510 million tons of contaminated soil. Emergency situations, which are difficult to predict, may arise at oil production and oil refining enterprises. That situations also lead to environmental pollution. The remediation of groundwater from dissolved petroleum products is one of the difficult tasks. There are two main approaches to remediation of oil pollution: ex situ , i.e. at special sites, and in situ , i.e. at the site of contamination. Using in situ techniques can be significantly cheaper and more effective. The applying of in situ techniques should be based on a well-developed strategy for implementing environmental protection measures. Mathematical modeling allows one to reliably determine and justify hydrogeological studies and to obtain parameters for the development of designed solutions. This article studies the possibility of mathematical modeling methods applying for the biotechnological process of groundwater remediation used a dosed supply of oxygen into a contaminated aquifer. The results of field observations and model data were compared. During the research, it was established that the developed geomigration model, which uses a package of instantaneous aerobic degradation of hydrocarbons, adequately describes the dynamics of pollutant reduction in groundwater when compared with field measurements. To assess the effectiveness of the measures taken, forecast calculations were additionally performed on the model with different numbers of treatment wells and the distance between them. The data obtained allowed us to conclude that the development of mathematical modeling at the preliminary stage makes it possible to select the most optimal scheme for groundwater treatment even before the construction of the technological complex, which can significantly reduce costs when implementing such projects.
Максимович et al. (Mon,) studied this question.