A Review of Smart Monitoring Technologies for Shrinkage Mitigation and Norm Assessment in Condensate and Light Crude Processing in Niger Delta, Nigeria

Abstract

The Niger Delta region remains a critical hub for condensate and light crude oil production, yet operational inefficiencies related to hydrocarbon shrinkage and naturally occurring radioactive material accumulation continue to pose significant technical, economic, and environmental challenges. Shrinkage, driven by phase transitions, flash losses, and temperature-pressure variations during processing and transportation, results in substantial revenue losses and inventory discrepancies. Concurrently, naturally occurring radioactive material deposition in processing equipment and pipelines presents occupational health hazards and environmental contamination risks. Conventional monitoring approaches—manual sampling, periodic inspections, and laboratory-based radiometric analysis—are labor-intensive, time-delayed, and inadequate for real-time decision-making in dynamic operational environments. This review examines the integration of smart monitoring technologies, including Internet of Things sensor networks, artificial intelligence (AI)-driven predictive analytics, unmanned aerial vehicles (UAVs), and digital twin frameworks, as transformative solutions for shrinkage mitigation and assessment. A comparative analysis of these technologies highlights their capabilities in continuous data acquisition, anomaly detection, and predictive maintenance. The application context of the Niger Delta is critically evaluated, addressing region-specific barriers such as infrastructural deficits, power supply instability, cybersecurity vulnerabilities, and socio-political challenges. The review concludes that strategic deployment of smart monitoring systems, supported by capacity building and regulatory frameworks, can enhance operational efficiency, reduce economic losses, and improve environmental and occupational safety in Niger Delta petroleum operations.