Виктор Геннадьевич Аковецкий
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Алексей Викторович Афанасьев
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Анжела Асхатовна Ильченко
Оценка геоэкологических рисков на объектах нефтегазового комплекса непосредственно связана с обеспечением безопасности территорий, на которых они расположены. Особенно тяжелые последствия воздействия на экологическое состояние территорий оказывают аварийные разливы нефти и нефтепродуктов. Решение данного класса задач требует оценки уровня аварийного разлива и его классификации с позиций возникновения чрезвычайной ситуации. В статье рассмотрена возможность замены традиционных визуальных методов оценки разливов на разработанные автоматизированные и автоматические способы, использующие для решения задач классификации материалов аэрокосмических съемок. Приведены результаты автоматической классификации изображений мониторинговых наблюдений, которые имели место при аварийном разливе дизельного топлива в г. Норильске, аварии танкера на морской акватории о. Маврикий и аварии сухопутного нефтепровода. Полученные результаты показали работоспособность разработанных методов и возможность их использования в задачах инвентаризации и паспортизации аварийных разливов нефти на суше и акваториях.
Purpose. The aim of this work is to ensure the environmental safety of the territories where the accidental spills of oil and oil products have occurred. They have a significant negative impact on the environment of land and water areas. To minimize their impact and eliminate the consequences, an “emergency” regime is introduced in Russia. Depending on the level of the oil spill, it may cover both the territory of a separate facility and a region, and the entire state as a whole. Methods. Traditionally, an estimate of the level of a spill is determined based on the mass of the spilled oil through visual observations from aircraft or ground measurements at selected points. This approach does not allow an accurate assessment of the total area of pollution, the nature of pollution inside the oil slick, as well as the dynamics of its spread over time. To eliminate these limitations, it is proposed to use systems of aerospace monitoring observations and automatic measurements of oil slick parameters: area, composition and mass. To solve this problem, the method of “comparison with the reference standard” was used. Here, samples of color gradations of oil and oil product spill spots proposed in the Bonn Agreement of 2004 were prepared as reference standards. Results. The method was implemented using the experimental software complex AGIR-TM (Aerospace, Geoinformatics, Research, Risks-Technological Modules) which was developed at the Department of Geoecology of the Gubkin Russian State University of Oil and Gas (NRU). During the experimental testing of this method, the work was carried out to assess the accidental spill in the following cases diesel fuel in Norilsk (2020), oil on a tanker in the water area of Mauritius (2020) and oil in an oil pipeline (2012, 2017). The method provides the localization of the area spills along with the color correction (normalization), classification of the composition of oil and oil products and the through account of the investigated processes. The work results in determination for the area of the oil and oil products spill, its composition and weight. Conclusions. The article shows the relevance of solving problems related to the problem of liquidation of emergency spills of oil and oil products at the facilities of the oil and gas complex. The main approaches to aerospace monitoring observations and automatic interpretation of spill parameters are considered. The proposed approach is based on the use of “digital twins” that implement the transition from manual (visual) to automated and automatic modes for determining the parameters of an oil spill: area, composition and mass. The results presented in the article showed the efficiency of the proposed method and the possibility of its use in the tasks of assessing geoecological risks associated with accidental spills of oil and oil products on land and in water areas.
Design of Optimal Rainfall Monitoring Network Using Radar and Road Networks
