Offshore Oil Operations: Innovations in Maintenance, Safety, and Asset Integrity Management

Authors

  • Rutvik Patel   Independent Researcher

Keywords:

Offshore oil, Maintenance strategies, Safety management, Predictive maintenance, Technological advancements, Risk assessment.

Abstract

Offshore oil activities are unique in nature and need to have well-articulated plans to achieve equipment integrity, people safety, and environmental responsibility. Severe operational environments, high corrosion risks and the lack of accessible infrastructure create severe difficulties in terms of maintenance, safety, and asset integrity. Traditional maintenance approaches, such as reactive and scheduled preventive maintenance, often lead to operational inefficiencies, unplanned downtimes, and increased costs. To address these challenges, recent advancements in predictive analytics, Industrial Internet of Things (IIoT), artificial intelligence (AI), and digital twins have transformed offshore asset management. As a result of these technological advancements, operational efficiency is enhanced, and risks are decreased via data-driven decision-making, early defect detection, and real-time condition monitoring. Additionally, innovations such as autonomous inspection systems, robotic maintenance, and unmanned aerial vehicles (UAVs) enhance safety by reducing human intervention in hazardous environments. This study explores the latest technological advancements in offshore oil operations, focusing on predictive maintenance, asset integrity, and safety enhancements while evaluating their impact on cost reduction, regulatory compliance, and long-term operational sustainability.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-10-30

Issue

Volume 8, Issue 5, September-October-2022

Section

Research Articles

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How to Cite

[1]
Rutvik Patel , " Offshore Oil Operations: Innovations in Maintenance, Safety, and Asset Integrity Management" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.388-397, September-October-2022.