Real-time monitoring and predictive analytics are transforming digital twin & smart oilfields for sustainable operations, improving efficiency and reducing environmental impact. Digital twin technology integrates AI, IoT, and cloud computing to create virtual replicas of oilfield assets, enabling predictive maintenance and optimized production planning. Smart oilfields utilize automated data collection from sensors and drones to enhance safety and reduce downtime. AI-driven analytics are identifying energy savings and emission reduction opportunities. The increasing reliance on real-time data and machine learning is streamlining decision-making. By enhancing asset performance and minimizing operational risks, digitalization is ensuring the long-term sustainability of hydrocarbon production.
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 : Enhancing LPG capacity at Rabigh bulk plant: A case study on flow optimization and operational efficiency
Fahad Almehmadi, Saudi Aramco, Saudi Arabia
Title : Unlocking field development through infill well success delivering 3,000 BOPD via integrated dynamic analysis and seismic reprocessing: Lima field, PHE ONWJ
Indra Sanjaya, PHE ONWJ, Indonesia
Title : Reservoir screening and feasibility assessment for underground natural gas storage in upper Assam basin
Ashutosh Ranjan, Oil India Limited, India
Title : Proportional application technologies for urea removal in aqueous waste effluents, and recommended technologies for varies industrial waste water.
Hossam Ahmed Aly Moustafa Teama, Abu Qir Fertilizers And Chemical Industries Company, Egypt
Title : Enhancing refinery operational excellence: An AI-powered approach to digital operations management
Ganesh Markad, Proclink Consulting, India