Business AI for Oil and Gas: Unlocking Efficiency Across the Value Chain

Authors

  • Rajeshwar Guggilla Energy Transfer Partners LLC, USA Author

DOI:

https://doi.org/10.32628/CSEIT241051072

Keywords:

Artificial Intelligence, Oil and Gas Industry, Generative AI, Refinery Optimization, Operational Efficiency

Abstract

This article explores the transformative impact of artificial intelligence (AI) on the oil and gas industry, focusing on its applications across the value chain from exploration to end-user delivery. It examines the potential of AI, particularly generative AI, to optimize various aspects of the sector, including exploration, development, production, transportation, refining, and sales. The article discusses specific AI applications in refinery processes. It highlights the significant benefits of AI implementation, such as improved operational efficiency, reduced downtime, enhanced decision-making, cost reduction, and increased safety. Drawing on industry studies and research, the article presents quantitative data on the potential cost savings, productivity improvements, and value creation that AI technologies can bring to the oil and gas sector.

Downloads

Download data is not yet available.

References

McKinsey & Company, "The next frontier for digital technologies in oil and gas," Aug. 2016. [Online]. Available: https://www.mckinsey.com/industries/oil-and-gas/our-insights/the-next-frontier-for-digital-technologies-in-oil-and-gas

MarketsandMarkets, "AI in Oil and Gas Market," 2022. [Online]. Available: https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-oil-gas-market-87246288.html

EY, "How can artificial intelligence lead the way for oil and gas?," 2020. [Online]. Available: https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/oil-and-gas/ey-ai-in-oil-and-gas.pdf

Grand View Research, "AI In Oil And Gas Market Size, Share & Trends Analysis Report By Application (Upstream, Downstream, Midstream), By Function, By Region, And Segment Forecasts, 2023 - 2030," 2023. [Online]. Available: https://www.grandviewresearch.com/industry-analysis/ai-oil-gas-market-report

Kaar Technologies, "Digital Transformation in Downstream Oil and Gas," 2023. [Online]. Available: https://www.kaartech.com/blogs/digital-transformation-in-downstream-oil-and-gas/

Aidan Fuller, Zhong Fan, Charles Day, and Chris Barlow, "Digital Twin: Enabling Technologies, Challenges and Open Research," in IEEE Access, vol. 9, pp. 108952-108971, 2021, doi: 10.1109/ACCESS.2021.3100551. [Online]. Available: https://ieeexplore.ieee.org/document/9103025 DOI: https://doi.org/10.1109/ACCESS.2020.2998358

Wood Mackenzie, "Digitalisation in upstream: show me the money," 2023. [Online]. Available: https://www.woodmac.com/reports/upstream-oil-and-gas-digitalisation-in-upstream-show-me-the-money-28229/

Deloitte, "From bytes to barrels: The digital transformation in upstream oil and gas," 2022. [Online]. Available: https://www2.deloitte.com/content/dam/Deloitte/ch/Documents/energy-resources/ch-er-digital-transformation-oil-gas.pdf

Downloads

Published

01-11-2024

Issue

Section

Research Articles

How to Cite

[1]
Rajeshwar Guggilla, “Business AI for Oil and Gas: Unlocking Efficiency Across the Value Chain”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 10, no. 5, pp. 822–828, Nov. 2024, doi: 10.32628/CSEIT241051072.

Similar Articles

1-10 of 268

You may also start an advanced similarity search for this article.