Artificial Neural Networks and the Oil and Gas Industry: Bibliometric Analysis (2020-2024)
DOI:
https://doi.org/10.29019/enfoqueute.1106Keywords:
Artificial Intelligence, Artificial Neural Networks, Petroleum Operations, Predictions, Natural Gas, BibliometricsAbstract
In the oil and gas industry, applying prediction and estimation methodologies such as Artificial Neural Networks has represented a valuable tool in the whole petroleum system. The review’s objective was to analyze, from a bibliometric perspective, the scientific production of the last five years on the use of Artificial Neural Networks in this industry. The Scopus database was used to filter the information by time, subject, type of documents, and origin. A search equation was used with the keywords artificial neural network and oil and gas industry. The information was processed using LibreOffice Clac, JASP, and VOSviewer software. A total of 267 documents were obtained, with 59.9% original scientific articles, 56.0% published in scientific journals, China as the country with the highest production, the main authors were from Saudi Arabia, 69.8% of the research was in the Energy sub-area, 67.1% of the research was affiliated to oil companies and the application areas were, in addition to the traditional exploration, drilling, production and reservoir, flow analysis, artificial lift, emissions, anomaly detection, automation, corrosion, and carbon dioxide detection. It is concluded that in the last five years, research on the use of ANNs in the oil and gas industry has deepened, especially in production prediction, reserves, and reservoir studies.
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