-    Value of asset centric fleet management
-    Analyzing the importance of digital twin lifecycle management
-    Evaluating architecture considerations

-    Understanding what a Knowledge Graph is and why is it a powerful digital twin model technology
-    Using a knowledge graph digital twin model to automate a process verification workflow, with a massive impact in team efficiency
-    How the same digital twin structure is applicable to other typical problems in oil and gas
-    How the process can be extended to trigger Power Automate workflows, unravelling endless possibilities to accelerate communication, decision making and action

-    What are the practical steps to build a plant digital twin? 
-    What are the fundamental concepts and best practices to follow?
-    What are the characteristics of an engineering platform for building a plant digital twin?
-    Analog to a real field for a real plant, prerequisite of building a Plant Digital Twin is a versatile and robust engineering platform for core engineering disciplines.  
 

-    Human Centric vs System Centric - The twins are different
-    Integrated Twins - making twins work like one
-    The real twins - Human and Machine
-    Control Systems, Monitoring Systems, and Autonomous Systems
-    Family Planning - Giving Birth to your Twins

If you can't measure it, you can't manage it, or improve it.” This variation on a famous quote by management guru Peter Drucker has been a driving force in managing people and processes in the most successful companies over the last century. When it comes to everything else, you need IoT to measure it and digital twins to manage and improve it. The drive toward net-zero emissions is an all-hands-on-deck imperative requiring new levels of innovation throughout the oil and gas industry. Join Rob as he shows you how digital technologies like digital twins and IoT have an important role to play in this transition.

Compression of functionality defined in the Purdue Model changes the value of IoT endpoint devices to attackers as well as how they are leveraged in attacks.  How do IoT devices change the attack surface exposure of a target network?  What needs to be considered for secure architecture, incident response, or threat detection?

-    What are the latest threats facing oil and gas infrastructure 
-    What threat prevention tools and mechanisms should operators be evaluating
-    How can you futureproof your operations

-    Advances in sensor, real-time, and edge data - unlocking the potential of unprecedented data 
-    With great power comes great responsibility -  ensuring that you’re equipped and able to drive insights from this data is truly next frontier in digital advances

This presentation will discuss the role of engineering, cultural enablers, data governance, and architecture in ensuring that you and your teams are poised to leverage your great influx of data.

-    Deploying machine learning on edge devices
-    Improving well data interpretation 

-    Frequency drive architecture with advanced security features and the ability to operate as a network device with DAQ front end.  
-    Using MatLab Simulink to create new embedded IP and digital twins of real world physical loads
 

-    Logical capabilities and physical location for computation and data
-    Expectations that decisions depend on the industry vertical
-    Patterns for starting architectural design

-    Evaluating the latest connectivity technology and solutions  
-    Exploring potential future vulnerabilities  
-    Understanding the technical challenges that are the biggest blockers for energy companies aiming to achieve autonomous fields of the future. 
-    Outlining some real-world examples

• IoT deployment demands more than a dumb pipe
• From cellular to Sigfox, the right architecture drives speed to market and success at scale
• Case studies and lessons learned from 1M+ IoT connections in oil & gas