Uploaded by Арсен Ибраимов

thesis AI in oil and gas

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Leveraging artificial intelligence to enhance supply chain, predict demand and drive business
success in the oil and gas industry.
Ibraimov Arsen Ruslanovich
Student
Branch of the Russian State University of Oil and Gas (NRU)
named after I.M. Gubkin inTashkent
Scientific supervisor: docent Bobokhujaev Sh.I.
Language consultant: lecturer Razikova D.S.
ABSTRACT
This paper discusses the use of artificial intelligence (AI) in the oil and gas industry to
improve supply chain management, predict demand for products, and make more informed
business decisions. The article highlights the benefits of AI in analyzing large amounts of data
related to supply chain operations, demand patterns, financial data, and customer behavior, and
how this analysis can help companies make more informed decisions, improve their customer
relationships, and reduce the risk of disruptions. The article concludes by emphasizing the
potential for AI to revolutionize the oil and gas industry and improve overall business outcomes.
KEYWORDS
Artificial intelligence (AI), supply chain management, demand forecasting, business
decisions, customer relationships, large amounts of data, customer behavior.
The oil and gas industry is grappling with the increasing demand for energy and the need
for more efficient supply chain management. To address these challenges, companies are turning
to the power of artificial intelligence (AI). With AI, the industry can improve supply chain
operations, accurately forecast demand for products, and make better-informed business
decisions.
AI algorithms can analyze vast amounts of data related to the industry's supply chain,
uncovering bottlenecks, inefficiencies, and areas for improvement. For example, AI can evaluate
supplier performance and identify the suppliers who consistently deliver high-quality products
on time. This information can help companies minimize the risk of supply chain disruptions.
Demand forecasting is another area where AI is proving to be a valuable tool. The
unpredictable nature of the oil and gas industry makes it difficult for companies to estimate
future demand for their products. AI can analyze data on sales and customer behavior, allowing
companies to make more accurate predictions about demand. This information can help
companies make informed decisions about production levels and timing.
In addition to improving supply chain management and demand forecasting, AI can help
companies make better business decisions. The massive amounts of data available can be
overwhelming, but AI algorithms can identify the most relevant information, allowing
companies to make informed choices. For example, AI can analyze financial data and highlight
trends in spending, revenue, and profits, helping companies make sound investment and
budgeting decisions.
Finally, AI has the potential to revolutionize the way companies in the oil and gas
industry interact with their customers. With a vast customer base, it can be difficult for
companies to provide personalized customer service. AI can analyze customer data, uncovering
the most critical customer needs and preferences. This information can help companies improve
customer engagement and satisfaction, critical factors in the long-term success of any business.
In conclusion, AI has enormous potential to transform the oil and gas industry. From
improving supply chain management and demand forecasting to better business decisions and
customer relationships, AI is a game-changer that will continue to shape the industry in the
coming years.
REFERENCE:
1. «How AI is transforming the oil and gas industry». [Internet-source]. URL:
https://www.azena.com/insights/how-ai-is-transforming-the-oil-and-gas
(date
of
access
7.02.2023).
2. «AI for oil and gas». [Internet-source]. URL: https://www.aspentech.com/en/apmresources/ai-for-oil-and-gas (date of access 7.02.2023).
3. MIT Technology Review. Transforming the energy industry with AI. 2021. URL:
https://www.technologyreview.com/2021/01/21/1016460/transforming-the-energy-industrywith-ai/ (date of access 7.02.2023).
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