Intelligent oil and gas field based on artificial intelligence technology
Интеллектуальное нефтегазовое месторождение на основе технологий искусственного интеллекта
2022-12-30
SCID: 54.1/uqpa9rc8
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artificial intelligenceenhanced oil recoveryneural networksproduction forecastingsmart oilfield
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Abstract (AI)
Artificial Intelligence (AI) is a system that simulates the thinking process. AI involves a simple structural approach to the development of complex decision-making systems, allowing the user to set and solve problems of varying degrees of complexity. Today, AI technologies are increasingly being used in many areas of human activity, and the oil and gas industry is no exception. Application of AI in oil and gas industry is rapidly developing and gradually being introduced in various areas such as: smart drilling, smart pipeline, smart refinery, etc. Based on AI, it is possible to create an ecosystem in which coordination and cooperation of all levels, sectors and areas can be implemented to extend the life cycle of the oil field, improve efficiency and quality of decision-making, reduce costs and increase economic benefits. Keywords: Artificial Intelligence; neural network; enhanced oil recovery; production forecast; support vector machines; genetic algorithm.
Key Findings
1
AI can support an integrated oilfield ecosystem coordinating multiple operational levels and sectors throughout the field life cycle.
2
Applying AI is expected to improve decision-making efficiency and quality while reducing costs and increasing economic benefits.
3
Artificial intelligence is increasingly being applied across the oil and gas industry, including smart drilling, pipelines, and refineries.
4
The abstract identifies neural networks, enhanced oil recovery, production forecasting, support vector machines, and genetic algorithms as relevant AI applications or methods.
Research Object
oil and gas fields and their operational systems, including drilling, pipelines, and refineries
Research Subject
AI-enabled coordination and optimization of field life-cycle management, production forecasting, enhanced oil recovery, and decision-making efficiency
Publication Details
Publication Date
2022-12-30
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