What question did this study set out to answer?

Investigate systemic failures in process safety in the refining sector due to recent global disruptions.

June 5, 2026Open Access

The Need for Rigorous Process Safety Audits in the Global Refining and Petrochemical Sector (20242026) Is Crucial to Reduce Volatility

Key Points

Investigate systemic failures in process safety in the refining sector due to recent global disruptions.
Analyzed case studies of significant fires and explosions in oil refining and petrochemical facilities.
Employed qualitative comparative analysis and systems engineering evaluation to identify failures.
Developed an Advanced Process Safety Performance Framework for dynamic risk assessment.
Identified that historical fire incidents increased by 1,800% compared to previous averages.
Revealed inadequacies in current compliance checklists to address complex risk interactions.
Proposed the APSPF for enhancing safety through machine learning, AI, and safety culture quantification.

Abstract

The global energy sector faced significant disruption in the first few months of 2026, resulting in over 45 major fires at oil refineries and power plants. The disruption was caused by heightened geopolitical tensions and macroeconomic supply challenges.. The historical average of 9 to 10 isolated fires per year is almost 1,800% higher than this statistic, as revealed by a review of events in energy sector databases worldwide. This problem is a multifaceted one that includes countries such as India, China, and Indonesia, driven by varying geopolitical factors, increasing throughput requirements, or outdated infrastructure. Through high-consequence case studies, such as the HPCL Rajasthan Refinery (HRRL) Crude Distillation Unit fire, the Valero Port Arthur blast, and the fatal Vedanta Athena boiler explosion, this research examines the underlying systemic failures that are responsible for these events. Through the use of qualitative comparative analysis, systems engineering evaluation, and regulatory frameworks, this study investigated how basic mechanical components can fail during tier-1 process safety events. The findings, along with the systemic gaps identified in the case studies, suggest that current prescriptive compliance checklists are inadequate for dealing with dynamic risk profiles and complex interactions in real-world operations. In reaction, this paper presents an Advanced Process Safety Performance Framework (APSPF). By replacing static compliance with three structural contributions, the framework enables: (1) Machine learning-based dynamic risk assessment; (2) Cognitive artificial intelligence designed to remove human and system isolation barriers; and (3) Analytical hierarchy-driven quantification of corporate safety culture. According to the study, the deployment of a sophisticated framework through independent third-party validation is essential for optimizing modern safety performance metrics and preserving high-value global energy assets.

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