The safe and efficient transport of hydrocarbons relies on robust pipeline infrastructure and corrosion control. Pipeline engineering, integrity & corrosion management focus on advanced coatings, cathodic protection, and inline inspection technologies to extend pipeline lifespan. Smart pigging and real-time monitoring systems detect anomalies, reducing risks of leaks and failures. Innovations in material science, including composite pipeline construction, enhance durability in extreme environments. AI-driven predictive maintenance strategies optimize integrity assessments, lowering operational costs. As global energy networks expand, maintaining pipeline safety and reliability remains a top priority, ensuring uninterrupted supply and environmental protection.
Selim Sanad Shaker
Geopressure Analysis Services, United States
Saim Memon
Sanyou London Pvt Ltd, United Kingdom
Nur Hassan
Central Queensland University, Australia
Selim Sanad Shaker
Geopressure Analysis Services, United States
Nur Hassan
Central Queensland University, Australia
Matthew Godfrey
Enventure Global Technology, United States
Barbara Diaz
Automa Srl, ItalySubmit your abstract Today
Title : The Vacuum Insulated Heatable Curtain (VIHC): From conceptual invention to market deployment as a cost-effective dual solution for window heat loss reduction and localised radiant comfort
Saim Memon, Sanyou London Pvt Ltd, United Kingdom
Title : Hydrogen production from depleted or unproductive oil and gas reservoirs
Cleveland M Jones, Fronteira Energia Ltda, Brazil
Title : Predicting drilling challenges and hazards due to subsurface pressure’s drifting
Selim Sanad Shaker, Geopressure Analysis Services, United States
Title : Transforming waste plastic into hydrogen: Progress, challenges, and future directions in pyrolysis-based integrated pathways
Nur Hassan, Central Queensland University, Australia
Title : Novel expandable liner hanger platform for advanced liner drilling and reaming
Matthew Godfrey, Enventure Global Technology, United States
Title : From empirical decline to intelligent forecasting: A hybrid deep learning framework embedding arps physics for unconventional tight-gas reservoir production prediction
Emmanuel Chibueze Obasi, University of Wyoming, United States