Thermodynamics and Phase Behavior
The complicated interaction between physically distinct, separable sections of matter termed phases that are in contact with each other is described by phase behavior. Solids, liquids, and vapors are the most common phases. In many petroleum applications, phase behavior is critical. Thermodynamics is the study of energy and its changes, which is crucial to understanding phase behavior. We can follow the energy changes that occur during phase transitions and anticipate the result of a process using thermodynamics. The goal of phase-equilibrium thermodynamics is to find properties like temperature, pressure, and phase compositions that emerge once all potential for further change has disappeared.
- Compositional Simulation
- Enhanced Oil Recovery
- Environmental Cleanup
- Geochemical Behavior
- Geothermal Energy
- Multiphase Flow in Wellbores and Pipes
- Wellbore Stability
Committee Members
Selim Sanad Shaker
Geopressure Analysis Services, United States
Saim Memon
Sanyou London Pvt Ltd, United Kingdom
Nur Hassan
Central Queensland University, Australia GOPE 2026 Speakers
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
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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