Zhi RUipeng (Tomsk Polytechnic University )
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This article is dedicated to the study of the application of intelligent management systems based on deep learning in the oil and gas industry. The relevance of the topic is driven by the rapid development of artificial intelligence technologies and their active implementation in various industrial sectors. The purpose of the work is a comprehensive analysis of the potential and limitations of using deep learning to optimize the processes of extraction, transportation, and processing of hydrocarbons. The study employed methods of systematic literature review, comparative analysis, expert surveys, and mathematical modeling. The empirical basis consisted of data from implemented AI projects in oil and gas companies for the period 2018-2023. The obtained results indicate a significant improvement in the efficiency of key production processes (on average by 15-20%) and a reduction in operating costs (by 10-15%) through the application of intelligent management systems. At the same time, risks associated with ensuring cybersecurity and insufficient technological maturity of certain solutions were identified. It was concluded that further interdisciplinary research is needed to unlock the full potential of deep learning in the oil and gas industry.
Keywords:oil and gas industry, intelligent control systems, deep learning, artificial intelligence, digital transformation
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Citation link:
Zhi R. RESEARCH ON THE APPLICATION OF INTELLIGENT CONTROL SYSTEMS BASED ON DEEP LEARNING IN THE OIL AND GAS INDUSTRY // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№02. -С. 154-158 DOI 10.37882/2223-2966.2025.02.37 |
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