Renewable Energy
Renewable energy comes from naturally renewing but flow-limited sources; renewable resources are nearly limitless in terms of length but have a finite amount of energy per unit of time. Renewable energy is derived from sources that can be regenerated or replenished spontaneously. Electricity is generated using all renewable energy sources. When it comes to greenhouse gas emissions, renewable energy sources are classified as zero (wind, solar, and water), low (geothermal), or neutral (biomass). In the future decades, renewable energy will play a critical role in decarbonizing our energy systems.
- Biomass (biofuel and biopower)
- Geothermal (power and heating)
- Solar (power and hot water)
- Water (hydropower and hydrokinetic)
- Wind
Committee Members
Selim Sanad Shaker
Geopressure Analysis Services, United States
Saim Memon
Sanyou London Pvt Ltd, United Kingdom
Cleveland M Jones
Fronteira Energia Ltda, Brazil GOPE 2026 Speakers
Jia Min Jin
Shanghai Research Institute of Materials, China
Matthew Godfrey
Enventure Global Technology, United States
Javier Garrigos
Tecnicas Reunidas, Spain
Rukiye Oztekin
Dokuz Eylül University, TurkeySubmit 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