1 Department of Electrical Engineering, Faculty of Engineering, Institute of Engineering, Technology and Innovation Management (METI), Centre for Engineering, Technology Management (CETM), Nigeria.
2 Department of Petroleum and Gas, Faculty of Engineering, University of Port Harcourt, Port Harcourt, Nigeria.
3 Department of Electrical Engineering, Faculty of Engineering, University of Port Harcourt, Port Harcourt, Nigeria.
International Journal of Science and Research Archive, 2025, 15(02), 1366–1380
Article DOI: 10.30574/ijsra.2025.15.2.1487
Received on 30 March 2025; revised on 16 May 2025; accepted on 19 May 2025
The integration of digital technologies in the oil and gas sector is reshaping the sustainability and efficiency of well construction operations. This review critically examines the role of technologies such as artificial intelligence (AI), machine learning, cloud computing, digital twins, and the Internet of Things (IoT) in optimizing planning, drilling, and completion processes. By leveraging these technologies, companies can enhance resource utilization, improve decision-making, and align operations with sustainability goals. The study identifies significant challenges to adoption, including high implementation costs, regulatory uncertainties, and workforce upskilling requirements. Drawing on case studies and current literature, the findings reveal that digital transformation not only boosts operational efficiency but also supports environmental stewardship and economic resilience. This paper provides actionable insights for industry stakeholders seeking to achieve sustainable well construction through strategic digital technology integration.
Digital Technology Adoption; Internet of Things; Well Construction; Artificial Intelligence; Machine Learning
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Bolaji Bartholomew Okogbe, Elizabeth Chinyerem Ndubuisi and Eseosa Omorogiuwa. Digital technology adoption, sustainability, and well construction delivery in oil and gas industry: Critical review of digital technology. International Journal of Science and Research Archive, 2025, 15(02), 1366–1380. Article DOI: https://doi.org/10.30574/ijsra.2025.15.2.1487.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0







