-    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

-    How work is transformed through new/different workflows in the digital and what that means out for the work front.
-    Change management and new ways to do work.
-    The skills emerging and the overlap between engineering and computer science and how that enables transformations in the digital twin space – both for development as well as for its use.
-    Core skills required for developing and sustaining the digital twin – visualization and virtualization as well as data science.
-    Putting context to digital twin use cases – introducing a level index to describe a range of digital twins and corresponding business value.
 

-    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.

-    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

In the most recent Mandiant cybersecurity and detection response analysis, it was found that more than 95% of attacks began with an intrusion into IT systems that lead to attackers pivoting into the IoT environment, costing billions of dollars in lost productivity and recovery expenses. This presentation will focus on practices and a 62443 based mechanism to protect IoT systems from untargeted, highly-damaging threats.  

-    Information Management overview and where cybersecurity fits in 
-    The gravity of the cybersecurity problem in major national infrastructure 
-    Best practices for cybersecurity lifecycle in oil and gas to protect multiple attack vectors  
-    IT/OT integration 
-    Unmanaged devices - how they’re protected, and other operational security issues for consideration 

-    Defining real-time versus checklist or periodic cybersecurity 
-    Describing activities that can be done in real-time  
-    Technologies supporting real-time and possible roadblocks 
-    How real-time cybersecurity aligns to the NIST Cybersecurity Framework 
-    Where to start the real-time cybersecurity journey

-    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.

•    Validated patterns in IT automation remove bottlenecks and delivery harmony to integrated IT and operations workflows.
•    Reduce the complexity required to maintain secure and compliant operations through an automated IT/OT collaboration.
 

•    Deploying machine learning on edge devices 
•    Improving well data interpretation  
•    Now we have connectivity to Edge, what next? 
•    How does connectivity impact security? 

-    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
 

-    Architectures for IIoT are often based on sensor-to-cloud connectivity that ignores or bypasses the facility’s industrial control system.
-    Instead of separate, non-interacting data paths for process control and IIoT functions, an integrated architecture is preferred to enable the most cost-effective use of the data.
-    A new architecture for industrial control systems based on the emerging Open Process Automation Standard (O-PASTM) provides an integrated process control / IIoT functional capability.
-    With O-PAS based systems, edge computing can be for both deterministic, real-time control as well as for data collection and on-prem analysis. Furthermore, O-PAS conformant edge computing enables more cost-effective solutions compared to currently available PLC/SCADA/DCS systems 
 

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

-    Identification of immediate ROI from IIOT project investment 
-    Simple and efficient deployment of sensors on legacy/existing physical assets 
-    Deploying scalable networks 
-    Device management at scale 
-    Versatile data integration with existing architecture  
-    Specific applications - Manual Valve Positioning and Tank Level Monitoring 
-    Edge AI analytics enabling real-time notifications to increase security and reduce risk 

-    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

-    Needs in the Oil & Gas Industry for IoT 
-    Trends in Telecommunications 
-    Emergence of mmWave offerings 
-    Spacebased LEO, MEO, and GEO (Ubiquity of coverage, latency, and bandwidth) 
-    Point-point terrestrial systems and spectrum sharing 
-    5G Deployment and an early view of where 6G may be heading 
-    Offerings and deployments 

•    Main drivers for Oil & Gas companies for Digitization initiatives – why some of these fail and others succeed.  How can digitization be accelerated, securely, and with minimal disruption? 
•    Deeper dive on Industrial IoT (IIoT) solutions that brings machines, connectivity, cloud computing, analytics, and people together to improve the performance and productivity of industrial processes. How cloud-based IIoT initiatives are playing a major role for Oil & Gas companies to deliver value across a variety of use cases including predictive quality and maintenance analytics, asset condition monitoring, and process optimization. 
•    Listen to customers like Hilcorp as they embark on a major Industrial IoT initiative to modernize their data infrastructure with cloud-native services.