Lignocellulose, a complex organic compound found abundantly in plant biomass, holds significant promise in the realm of sustainable energy and resource production. Comprising cellulose, hemicellulose, and lignin, lignocellulose represents a valuable renewable feedstock for the production of biofuels, biochemicals, and biomaterials. Through advanced biorefinery processes, lignocellulosic biomass can be efficiently converted into various valuable products, contributing to the diversification and sustainability of the energy sector.
Furthermore, research and innovation in lignocellulose utilization are integral to addressing environmental challenges and advancing the transition towards a low-carbon economy. By harnessing the potential of lignocellulosic feedstocks, the International Conference on Oil, Gas, and Petroleum Engineering aims to foster interdisciplinary discussions, share cutting-edge research findings, and explore novel technologies and strategies for the sustainable utilization of biomass resources. Through collaboration and knowledge exchange, the conference endeavors to drive forward the development of innovative solutions that optimize lignocellulose valorization and contribute to the advancement of the global energy landscape.
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