The foundation of hydrocarbon production lies in the precision and reliability of drilling and well construction. Drilling Engineering & Well Construction leverage cutting-edge technologies to improve wellbore stability, optimize drilling efficiency, and minimize environmental impact. Innovations such as rotary steerable systems, automated drilling rigs, and smart completions have significantly enhanced accuracy and safety. Advanced materials and real-time monitoring systems ensure well integrity, reducing risks associated with high-pressure formations. The integration of AI-driven predictive analytics is further refining drilling strategies, lowering costs and improving recovery rates. As exploration moves into deeper and more complex reservoirs, continuous advancements in drilling engineering remain essential for sustainable energy production.
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