Аннотация:Eremin, N. A. On the use of artificial intelligence methods for solving problems in the oil and gas industry / N. A. Eremin, D. A. Selenginsky, A.D. Chernikov // Zolotukhin Readings. Oil, Gas and Energy in the Arctic region : Proceedings of the International Scientific and Practical Conference, Arkhangelsk, April 20-21, 2023. – RUS: M.V. Lomonosov Northern (Arctic) Federal University, 2023. – pp. 110-112. – EDN TRBVXJ.Keywords: artificial intelligence, neural networks, organization of production, personnel selection, control of working equipment, anomaly detection, prediction of complications, well drilling, geo-logical and technological information, accident prevention, automated system, well construction, oil production.When forming a modern model of the national economy, digital development is considered as a key element of expanding competencies based on the introduction of intelligent technologies, where large geodata and the possibility of their prompt receipt and processing for improving technological processes of oil and gas production become the basis for cost reduction and decision-making.The digital cycle of oil and gas production includes: geological/man-made and infrastructural objects multisensory measurements transmission of big data (geodata and process information) processing and systematization formation of scientific knowledge digital twins and models cloud technologies and arrays of information. The technological cycle consists of production blocks: search and exploration of hydrocarbons drilling development production transportation storage processing oil and gas chemistry logistics of raw materials and products. The innovation cycle combines: the formation of a number of requirements for the creation of new samples of technologies and equipment: the formation of requirements sources of development experimental equipment pilot operation serial production certification market launch large-scale implementation of product samples and controls created in the process of investment. Artificial intelligence technologies" contribute to the early detection of complications, deviations from the technological regime, leaks. The scientific and technological revolution in fiber-optic sensors has made it possible to collect, transmit, store and process giant arrays of poorly structured geodata.The use of artificial intelligence is an open question, since it touches on topics such as brain architecture and human intelligence, which are still unknown in full. Neural networks are commonly used in computer systems using programs with appropriate computing equipment. Therefore, from the side of amateurs, it usually looks like a scientific illusion.Artificial intelligence research is divided into two main categories: neural networks and classical artificial intelligence [1].Recent developments and research prove that artificial intelligence can increase productivity and is useful at all stages of oil production. In recent years, the artificial neural network has developed very rapidly. Its principle is based on the human biological system. Artificial neural networks are used as a tool for determining the probability of complications, for example, "hijacking" and accidents [2].An artificial intelligence component, such as the PC "Indication of the forecast of complications and emergencies during drilling and construction of wells", can be used to solve problems of the oil and gas industry. It is capable of predicting possible complications and emergencies during drilling and construction of wells in real time, as well as providing recommendations for preventing the consequences of predicted complications. To do this, the PC uses neural network forecasting models that process geological and technological information (GTI) data obtained in real time. The results of predicting the probability of complications of three types ("Seizure", "Absorption", "GNVP") are displayed on the screen, and also stored in the data warehouse for further analysis [3].However, the key in the application of such a system for predicting complications is the availability of a database of real data, parameters for training artificial intelligence [4]. The data from the birthplace of Volve are publicly available, on which such a software package as "Indication of the forecast of complications and emergencies during drilling and construction of wells" was trained. But for the further development of prediction technologies, data from other deposits will be required, where there have been cases of complications, such as capture and absorption. Whether oil companies are ready to provide their data for the development of the software package and its further application is an open question.The use of artificial intelligence tools, such as fuzzy logic and neural networks, is developing with the development of oil production technologies and science in general. Helps to optimize production and reduce risks. The more actively existing developments are introduced into production, the more noticeable the results will be.The use of artificial intelligence methods in the oil and gas industry makes it possible to build new business models, increase competitiveness and reduce capital costs at all stages of production [5]. Digital modernization using artificial intelligence is aimed at reducing downtime of equipment and wells, as well as reducing operating costs. Artificial intelligence methods are used to predict the relative permeability curve, optimize the operation of personnel and equipment, as well as to create cost-effective and efficient models that can reduce the risks of complications and accidents. The oil and gas industry has already achieved significant success in the application of artificial intelligence in drilling, field development, production and enhanced oil recovery.Bibliographic list1. Gharbi, R.B.C., Mansoori, G.A., 2005. An introduction to artificial intelligence applications in petroleum exploration and production. J. Petrol. Sci. Eng. 49, 93–96. https://doi.org/10.1016/j.petrol.2005.09.0012. Automated system for preventing accidents during the construction of wells / A.N. Dmitrievsky, N.A. Eremin, [et al.], 20213. Dmitrievsky A. N., Stolyarov V. E., Eremin N. A. The role of information in the use of artificial intelligence technologies in the construction of wells for oil and gas fields // Scientific Journal of the Russian Gas Society. No. 3 (26). 2020. pp. 6-21.4. Dmitrievsky A.N., Eremin N. A., Lozhnikov P. S., Klinovenko S. A., Stolyarov V. E., Inivatov D. P. Risk analysis when using artificial intelligence technologies in the oil and gas production complex // Automation, telemechanization and communication in the oil industry", No. 7(576).2021. – pp.17–27., DOI: 10.33285/0132-2222-2021-7(576)-17–27.5. Dmitrievsky A. N., Stolyarov V. E., Eremin N. A. Actual issues and indicators of digital transformation at the final stage of oil and gas production of fields // Scientific and technical journal "SOCAR Proceedings". Scientific works of NIPI Neftegaz SOCAR. SOCAR Proceedings Special Issue No.2 (2021). P 001-013. http://dx.doi.org/10.5510/OGP2021SI200543 .Еремин, Н. А. Об использовании методов искусственного интеллекта для решения задач в нефтегазовой отрасли / Н. А. Еремин, Д. А. Селенгинский, А. Д. Черников // Золотухинские чтения. Нефть, газ и энергетика в Арктическом регионе : Сборник материалов Международной научно-практической конференции, Архангельск, 20–21 апреля 2023 года. – RUS: Северный (Арктический) федеральный университет имени М.В. Ломоносова, 2023. – С. 110-112. – EDN TRBVXJ.Ключевые слова: искусственные интеллект, нейронные сети, организация производства, выбор кадров, контроль рабочей техники, выявление аномалий, прогнозирование осложнений, бурение скважин, геолого-технологическая информация, предотвращение аварий, автоматизированная система, строительство скважин, нефтедобыча.Цифро-вая модернизация с использованием искусственного интеллекта направлена на сокращение времени простоев оборудования и скважин, а также на снижение операционных затрат. Методы искусственного интеллекта используются для предсказания кривой относительной проницаемости, оптимизации работы пер-сонала и техники, а также для создания экономичных и эффективных моделей, способных снизить риски возникновения осложнений и аварий. Нефтяная и га-зовая промышленность уже достигли значительных успехов в применении ис-кусственного интеллекта в бурении, разработке месторождений, добыче и уве-личении нефтеотдачи.Библиографический список1. Gharbi, R.B.C., Mansoori, G.A., 2005. An introduction to artificial intelligence applications in petroleum exploration and production. J. Petrol. Sci. Eng. 49, 93–96. https://doi.org/10.1016/j.petrol.2005.09.0012. Автоматизированная система предотвращения аварий при строительстве скважин / А.Н. Дмитриевский, Н.А. Ерёмин, [и др.], 20213. Дмитриевский А. Н., Столяров В. Е., Еремин Н. А. Роль информации в при-менении технологий искусственного интеллекта при строительстве скважин для нефтегазовых месторождений // Научный Журнал Российского Газового Общества. №3 (26). 2020. С. 6–21.4. Дмитриевский А.Н., Еремин Н. А., Ложников П. С., Клиновенко С. А, Столя-ров В. Е., Иниватов Д. П. Анализ рисков при использовании технологий искусствен-ного интеллекта в нефтегазодобывающем комплексе // Автоматизация, телемеханиза-ция и связь в нефтяной промышленности», №7(576).2021. – С.17–27., DOI: 10.33285/0132-2222-2021-7(576)-17–27.5. Дмитриевский А Н., Столяров В. Е., Еремин Н. А. Актуальные вопросы и индикаторы цифровой трансформации на заключительной стадии нефтегазодобычи промыслов // Научно-технический журнал «SOCAR Proceedings». Научные труды НИПИ Нефтегаз ГНКАР. Спецвыпуск SOCAR Proceedings Special Issue No.2 (2021). Р 001–013. http://dx.doi.org/10.5510/OGP2021SI200543.
