Tech Expert on Challenges of IIoT in Oil and Gas



Tech Expert on Challenges of IIoT in Oil and Gas
According to one technology expert, security is just one of several challenges facing oil and gas companies deploying IIoT strategies.

As the oil and gas industry opens itself to newer technologies to make operations more efficient, roadblocks are par for the course.

Rigzone recently spoke with John Fryer, senior director, industry solutions, for Stratus Technologies about the adoption and deployment of the Industrial Internet of Things (IIoT) in oil and gas, as well as related challenges and success stories.

Rigzone: What are some of the biggest challenges facing oil and gas companies in adopting IIoT technologies?

John Fryer
John Fryer, Senior Director of Industry Solutions, Stratus Technologies
Senior Director of Industry Solutions, Stratus Technologies

Fryer: I think security is a main concern for oil and gas, given the nature of the business can lead to catastrophic events when control systems are hacked. Another issue is the remote nature of many locations, which makes reliable connectivity more challenging to achieve. There is also the challenge of addressing IIoT system failures at these remote locations and ensuring reliable data collection when connectivity is interrupted. Finally, it is often quite easy to develop and deploy a pilot but moving from a pilot to something at scale is where many companies fail.

Rigzone: What specific benefits can come from deploying more IIoT technologies? What success stories have you seen in oil and gas?

Fryer: Perhaps the best case we have to-date is Columbia Pipeline Group, now a part of Trans Canada. Beginning in the 2014 timeframe, they upgraded their entire gas pipeline infrastructure and deployed predictive analytics (using GE Predix) to reduce maintenance costs and unplanned downtime. The last presentation I saw stated they had saved millions in the first two years of operation. A key aspect of their deployment was to ensure they did not lose any data collected from sensors attached to their compression turbines as this would throw off the machine learning analytics deployed in GE Predix.

Rigzone: Do you feel that the realized benefits of deploying IIoT has caused some oil and gas companies to jump the gun in adding these technologies without fully understanding how to deploy them?

Fryer: We have seen many people look to deploy pilots and then either abandon them or fail in full-scale deployment. There are a number of key factors that need to be established. For both a pilot and a full-scale deployment, the business objectives need to be clearly identified and analyzed. There is often a disconnect here where Operational Technology (OT) is really concerned with the technical implementation but is not fully aware of the business objectives. On the flipside, the business function is not fully aware of the technology challenges. It is why new functions such as hybrid OT (a cross between OT and IT) and chief digital officer (someone who understands both the technology and business goals) are increasingly critical as we move to IIoT implementations.

There are three technical elements that must be thought through for success:

  • Get connected – Make sure you have the connectivity and data protection necessary to successfully capture and save your data.
  • Re-think your infrastructure – Ensure that it is simple, protected and that it can operate autonomously (particularly in remote locations).
  • Develop an architectural model – This should think through four layers: execution, data capture, process control and cloud strategy. 
    • Execution: Filtering and standardization of the device/actuator/control and edge computing elements of your system.
    • Data capture/filtering: Whether you should take a fully cloud approach vs. a hybrid edge/cloud approach.
    • Control: Involve process control, data normalization, real-time analytics and cybersecurity.
    • Could strategy: Involve passive analytics, aggregation from multiple locations and various forms of artificial intelligence.


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