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 : Salt basins exploration risks: The good, bad and ugly
Selim Sanad Shaker, Geopressure Analysis Services, United States
Title : Unlocking GHG reduction potential and enhanced oil recovery with direct contact steam generation technology: A case study in Lloydminster, Canada
Amr Hassan, General Energy Recovery Inc. (GERI), Canada
Title : Transforming waste plastic into renewable hydrogen: A review of progress, challenges and future directions through pyrolysis, distillation and hydrotreatment process
Nur Hassan, Central Queensland University, Australia
Title : Advancements in vacuum insulated technologies for energy efficiency and sustainable temperature sensitive logistics
Saim Memon, Sanyou London Pvt Ltd, United Kingdom
Title : Green hydrogen pathway to decarbonize oil refining
John W Sheffield, Purdue University, United States
Title : New exploration technologies to keep the O&G industry competitive
Cleveland M Jones, Fronteira Energia Ltda, Brazil