Technical Session 2: Digital Twin
Digital Twin can bridge the gap between the physical and digital worlds. For asset-intensive industries, such as energy a digital twin can be used to mirror an entire asset lifecycle from design to testing, to construction and commissioning, to maintenance and operations, to end of life.
By leveraging digital twins, organisations can reduce downtime, improve asset performance, and increase productivity. Digital Twins can also help organisations optimise their maintenance schedules, minimise the risk of equipment failure, and improve safety.
Meanwhile, Digital Twins technology currently faces shared challenges in parallel with AI and IoT technologies. Those include data standardisation, data management, and data security, as well as barriers to its implementation and legacy system transformation. As well, the high fixed cost and the complex infrastructure is affecting the deployment of Digital Twin technologies.
In this symposium, we would like to highlight the innovations that can solve those the challenges and share the benefits of this technology impacting Safety, Sustainability, and Production.
| Primary | 11:00 – 11:30 | Real-Time Data-Driven Digital Twins: Transforming Intelligent Well Management Zac Arackakudiyil, Halliburton |
| Primary | 11:30 – 12:00 | Advanced Water Injection Management in Waterflooded Reservoirs Using a Hybrid Data-driven Approach Davud Davudov, Resermine |
| Primary | 12:00 – 12:30 | Maximizing Reservoir Potential: Real-Time Well Productivity Index Optimization in Underbalance Drilling Ali Alhashim, SLB |
| Alternate / ePoster | TBC | Optimizing CO₂ Injection in Carbon Storage Operations via Graph Neural Surrogate Models with GHG Accounting and 45Q Tax Credit Maximization Haoyu Tang, University of Pittsburgh |
| Alternate / ePoster | TBC | Physics – Informed Graph Neural Network (PIGNN) for Waterflooded Reservoir Characterization and Optimization. Billal Aslam, KAUST |
| Alternate / ePoster | TBC | Harnessing AI for Next-Gen Carbon Storage: Innovative Solutions in Capacity, Injectivity, and Containment for CCS/CCUS Shripad Biniwale, SLB |
| Alternate / ePoster | TBC | Artificial Intelligence approach for Performance Optimization and Predictive Maintenance of Electrical Submersible Pump (ESP): Discharge Pressure and Flow Rate Analysis Omama Basbar, University of Khartoum |
