Artificial Intelligence Applications in Natural Gas Industry: A Literature Review
Siddhartha Nuthakki1, Chinmay Shripad Kulkarni2, Suraj Kumar3, Satish Kathiriya4, Yudhisthir Nuthakki5
1Siddhartha Nuthakki, Senior Data Scientist, First Object Inc, TX, USA.
2Chinmay Shripad Kulkarni, Data Scientist, CA, USA.
3Suraj Kumar, Lead Data Scientist, CA, USA.
4Satish Kathiriya, Software Engineer, CA, USA.
5Yudhisthir Nuthakki, Software Engineer, NJ,
Manuscript received on 30 January 2024 | Revised Manuscript received on 06 February 2024 | Manuscript Accepted on 15 February 2024 | Manuscript published on 28 February 2024 | PP: 64-70 | Volume-13 Issue-3, February 2024 | Retrieval Number: 100.1/ijeat.C438313030224 | DOI: 10.35940/ijeat.C4383.13030224
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of the more controversial uses of artificial intelligence (AI) in the petroleum industry has been in technological advancement. The gas business generates data on a constant basis from several operational procedures. The gas sector is now very concerned about recording these data and using them appropriately. Making decisions based on inferential and predictive data analytics facilitates timely and accurate decision-making. The gas business is seeing a significant increase in the use of data analytics for decision making despite numerous obstacles. Considerable progress has been made in the aforementioned field of study. With the use of artificial intelligence (AI) and machine learning (ML) techniques, many complicated issues may now be resolved with ease. This study, which looks at artificial intelligence applications in the natural gas sector, collected its data from numerous sources between 2005 and 2023. The current work might offer a technical framework for selecting pertinent technologies that will enable efficient information extraction from the massive amount of data produced by the gas industry.
Keywords: Artificial Intelligence, Applications, Gas Industry, Machine Learning Models, Natural Gas
Scope of the Article: Machine Learning