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Q&A: What does open AI mean for energy production?

Gain insight into the Open AI Energy Initiative, a first-of-its-kind open ecosystem of AI solutions to help transform the energy industry.

By Dan Jeavons, General Manager – Data Science and Christophe Vaessen, General Manager Commercial – EMEA (EU, Middle East, Africa) on Mar 24, 2021

Refineries and industrial processing plants are adopting data-driven analytics to drive safety and productivity improvements. They face a challenge to implement automated artificial intelligence (AI) workflows based on a standardised data model in a manner that is integrated with standard work processes. The challenge comes in part, from siloed application and data sets within organisations and across the energy industry at large.1

Shell, C3 AI, Baker Hughes and Microsoft recently announced the launch of the Open AI Energy Initiative (OAI), a first-of-its-kind open ecosystem of AI solutions to help transform the energy industry.

To learn more about the vision behind the OAI and its reliability solutions, we spoke with Dan Jeavons, General Manager – Data Science, who has led the initiative’s development, and Christophe Vaessen, General Manager Commercial – EMEA - Eu Middle East Africa, who has led commercialisation efforts of Shell intellectual property (IP) to third parties.

Q: What is the OAI designed to solve that current technologies cannot address?

Christophe Vaessen: Digital technology is a key enabler to facilitate the way we are doing business. As an energy company, we have to adapt to remain at the forefront of this transformation. The three previous industrial revolutions have demonstrated that not only the most advanced industries were successful, but the ones that were able to partner, develop and work together effectively were the ones that often stood out. Today, by bringing this OAI platform to life, we are building an open environment that enables all parties to work together toward a common ambition.

The OAI is an open platform where companies can plug in and commercialise their apps. This includes not only international oil companies but also different sectors, such as cement or mining companies, that are running large operations and looking for digital tools to help with predictive maintenance.

Industrial facilities require robust and supportable applications. We have chosen to work with C3 AI and Microsoft to provide the base platform – the operating system if you will. On top of that, C3 AI provides a series of apps which provide predictive maintenance and reliability capabilities.

Companies like Shell bring deep domain knowledge built up over years of operating these assets. We use our data to develop specific predictive maintenance add-ons, which we offer to others by means of a license on top of the C3 AI platform. The intent here is to enable sharing of IP through fair value exchange – we want to encourage others to bring their solutions to the platform. This is to reduce integration and operating costs for all parties concerned and accelerate digital transformation in the heavy industrial sectors.

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Q: Why is an open ecosystem of AI-based solutions significant for the energy and process industries?

Dan Jeavons: As Shell, we know we don’t have all the answers, but we also recognise that the rich data assets that operators have built up over many years are critical to solving some of the toughest digital problems. We are committed to working as part of an ecosystem – bringing multiple players together to move forward in the AI space because no one company can solve the world’s AI problems. Furthermore, speed is paramount – the energy transition is forcing us to change more quickly and the digital transformation of society is also accelerating. Our view is that alliances are critical to accelerating our progress and enabling AI deployment at scale.

As the founding members of the OAI, we are working hard to develop a curated ecosystem of integrated solutions and creating fair value exchange for the companies that build on top of the platform. The nearest analog to what we’re trying to do with the OAI is to create an Apple App Store for the process industry.

We have a standardised data model based on open standards. We have a platform, which creates consistency, scalability and supportability to drive adoption. And on top of that, we are aiming to build solutions that respect expertise and create fair value exchange.

With the OAI, startups can more easily build their apps in full confidence that the platform provides large customers and scalable deployment opportunities. We also recognise that many other companies have solutions, which are highly relevant to our business that we may want to adopt in a way that’s scalable, supportable and robust, and they are able to offer those solutions as well.

We hope to accelerate the digital transformation of the industry as a whole by breaking down development silos across organisations. We’re integrating capabilities to accelerate adoption and accelerate that value exchange.

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Q: How is the OAI developing a more integrated digital system among energy producers?

Dan Jeavons: The amount of time we all spend building our own proprietary platforms is truly remarkable. Working towards an integrated system is absolutely the idea behind the OAI. Now, the big challenge is that it will only work if you get adoption. So, you can’t do this alone. And that’s why the fair value exchange is so important because it can’t be about one person gaining competitive advantage over the others. It has to be an ecosystem play.

There’s a lot of competition in the industry and it’s getting more competitive by the day. As a result, there’s a lot of concern about sharing and losing IP, because the digital sphere is one of the areas where we want to compete.

But the analogy I would draw is that the tech companies have done a very good job of what is commonly referred to as coopetition. In many areas, they cooperate and in many areas they compete, and they’re able to do so simultaneously. Energy companies should consider adopting that coopetition mindset: in certain areas, it’s in our interest to cooperate for the good of society, whereas in other areas, competition is needed to drive innovation forward.

Progress for the OAI is going to be incremental. Its success will rely on gaining more adopters, but we’re excited by the early traction. We see a lot of people coming along and saying, “We want to be part of this.”

Q: What are you looking most forward to as the OAI gains traction?

Christophe Vaessen: Shell is currently focused on further developing predictive maintenance solutions which can help plant operators take preemptive action to avoid shutdown based on equipment failure. In the medium term, we would like to expand the offer by making it more integrated and include offerings to assist plant optimisation, inspection and sustainability. We want to bring in other elements in the value chain and therefore offer a full ecosystem for plant operations.

Partnership for the OAI will be incentivised by the solutions offered, and today, Shell is providing a first-wave of solutions. As the platform gains more adopters, its offerings will increase over time. Through collaboration and sharing technology, we are aiming to build an ecosystem where adopters will, together, be developing a fully integrated solution.

Dan Jeavons: If we consider Shell’s solutions offered through the OAI as applicable to three goals – reliability, integrity and optimisation – we’d like to expand this initiative’s offering for the latter two categories.

We’ve demonstrated that we can improve reliability for our own assets by using a combination of C3 AI and Microsoft technology on our own IP. We’ve published case studies demonstrating the successes of predictive maintenance around valve and compressor failure, electronics and submersible pumps.

We’d like to expand this initiative to integrity applications, including inspection and corrosion solutions, as well as visual techniques like machine vision to understand where problems are occurring. We’ve also seen results around AI in process optimisation with the goal to drive increases in batch quantity, on-spec cycle time for continuous processes, increased production and debottlenecking.

We’ve applied these solutions in our own business and we’re now bringing some of them and their underlying platform capabilities to the marketplace. I see these solutions as applicable to the new energies business as well, because reliability, integrity and optimisation are as relevant to wind farms, solar farms, battery storage and hydrogen facilities as they are to natural gas plants and refineries.

It is an extremely compelling proposition to create an integrated platform that can help to manage the operations for a variety of energy and industrial processing companies. Our ambition to create an integrated platform is something we’ve been working on with Shell for a while, and we’re excited to see the vision becoming a reality.

Learn more about the Open AI Energy Initiative and its reliability solutions

1 Johnny L. Gipson, “Data drives safety, productivity and quality of life improvements for oil and gas”, 29 April 2019, https://www.forbes.com/sites/teradata/2020/04/29/data-drives-safety-productivity-and-quality-of-life-improvements-for-oil-and-gas/?sh=5034a2006540.

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