This article is a compilation of interdisciplinary studies aimed at ensuring the environmental, political, and economic sustainability of oil and gas-producing countries with a focus on areas with many years of permafrost. One of the main concepts adopted in this research was the desire to show that confronting various energy lobbies is not mandatory and that it is necessary to find compromises by finding and introducing innovative technologies for integrated development for the benefit of society, industry, and the state. This is particularly relevant due to the increasing share of hard-to-recover hydrocarbon reserves, widely represented in the fields of the Eastern Siberian Arctic, and because Russia is the leader in flare emissions. We thus present the relevance of using these gases as industrial waste while reducing the carbon footprint. The technology of biofuel production based on the use of supercritical liquid extraction in a well extractor is presented as a result of the development of the presented experimental devices representing the investigation of the processes of extraction in wells and reactors for the distillation of hydrocarbons from heavy oil components. The obtained yield of the desired product (hydrogen) of the thermocatalytic pyrolysis of the test extract was in the range of 44 to 118 L/h, depending on the catalyst. This information can help inform the direction of future ecological engineering activities in the Eastern Siberian Arctic region.

The present study is focused on improving the technology for deep oil sludge processing by pyrolysis methods, considered to be the most promising technology for their environmentally friendly utilization, in which a significant yield of fuel products is expected. The technology developed by the authors of this study is a two-stage process. The first stage, pyrolysis of oil sludge, was investigated in previous papers. A significant yield of non-condensable gases was obtained. This paper presents a study of the second stage of complex deep processing technology—pyrolysis of non-condensable gases (purified propane) using a stirrer with the help of the developed experimental setup. The expected benefit of using the stirrer is improved heat transfer due to circumferential and radial-axial circulation of the gas flow. The effect of a stirrer on the yield of final target decomposition products—H₂-containing mixtures and H₂ generated during non-catalytic (medium-temperature) and catalytic pyrolysis of non-condensable gases obtained by pyrolysis of oil sludge are estimated. Ni catalyst was used for catalytic pyrolysis. The study shows that the application of the stirrer leads to increasing in H₂-containing mixtures and H₂ concentrations. In particular, during the whole reaction time (10 h), the average H₂ concentration in pyrolysis gas during catalytic pyrolysis increased by ~5.3%. In this case, the optimum reaction time to produce H₂ was 4 h. The peak H₂ concentration in the pyrolysis gas at reaction temperature 590 ± 10 °C was: 66.5 vol. % with the stirrer versus 62 vol. % without the stirrer with an error of ±0.4 %. A further increase in reaction time is cost-effective in order to obtain H₂-containing mixtures.

In this paper, the pyrolysis method of dealing with oil waste (oil sludge) is considered. Presented the mechanism of thermal destruction of hydrocarbons. The conducted study of the processes of non-catalytic pyrolysis of oily waste. At pyrolysis of oil slimes an exit of hydrocarbons was observed C1–C4.

One of the most effective technologies for recycling organic waste is its thermal destruction by pyrolysis methods to produce valuable products such as hydrogen and mixtures containing hydrogen. Increasing the thermal power of the flow helps to reduce the formation of secondary reactions, making the non-condensable hydrocarbon gas in the pyrolysis process cleaner, which simplifies further technology for the production of hydrogen and hydrogen-containing mixtures. In addition, the economic viability of pyrolysis depends on the energy costs required to decompose the organic feedstock. Using passive intensifiers in the form of discrete rough surfaces in heat exchanging channels is a widely used method of increasing heat transfer. This paper presents the results of numerical and experimental studies of heat transfer and hydraulic resistance in a channel with and without hemispherical protrusions applied to the heat transfer surface. The investigations were carried out for a reactor channel 150 mm long and 31 mm in diameter, with a constant pitch of the protrusions along the channels of 20 mm and protrusion heights h of 1 to 4 mm for 419 ≤ Re ≤ 2795. Compared to a smooth channel, a channel with protrusions increases heat transfer by an average of 2.23 times. By comparing the heat exchange parameters and the hydraulic resistance of the heat exchange channels, it was determined that h = 2 mm and 838 < Re < 1223 is the combination of parameters providing the best energetic mode of reactor operation. In general, an increase in h and coolant flow rate resulted in an uneven increase in heat transfer intensity. However, as h increases, the dead zone effect behind the protrusions increases and the rough channel working area decreases. Furthermore, increasing Re > 1223 is not advisable due to the increased cost of maintaining high coolant velocity and the reduced heat transfer capacity of the channel.

В рамках проекта по созданию гибридного цифрового двойника (PI-ML) для управления процессом замедленного коксования критически важным является переход от классификации типа продукта к количественному прогнозу его ключевых потребительских свойств. Данная работа посвящена сравнительному анализу эффективности методов машинного обучения для решения задачи множественной регрессии четырех критически важных свойств нефтяного кокса: пористости, содержания серы, прочности и истинной плотности. На основе исторических промышленных данных, включающих параметры сырья и технологического режима, были обучены, настроены и протестированы три модели: искусственная нейронная сеть – многослойный персептрон, метод опорных векторов для регрессии и градиентный бустинг. Результаты, полученные на независимой тестовой выборке, показали, что нейросетевая модель превосходит остальные, обеспечивая средний коэффициент детерминации равный 0,93. Все методы продемонстрировали высокую практическую пригодность, подтвердив наличие устойчивых статистических закономерностей. Разработанные модели формируют ключевой интеллектуальный модуль прогнозного контроля качества в архитектуре цифрового двойника, обеспечивая основу для систем предиктивного управления и оптимизации технологического режима.