2018 Winner: Outstanding Achievement in Energy and Environmental Innovation sponsored by Syncrude Canada Ltd.
Pipeline integrity technology focuses on the last 20 per cent of risk
OneBridge transforms pipeline integrity management through development of its enterprise SaaS-based solution, Cognitive Integrity Management. CIM uses machine learning to assist pipeline operators and regulators to achieve their stated objective of predicting oil and gas pipeline failures, to save lives, reduce costs and save the environment.
What problem or opportunity did you see the need to address and how did you go about developing your solution?
Tim Edward, President: We focused on the foundational elements of integrity management in the oil and gas industry, getting those in-line inspections to line up. That was fundamental to every practice that has followed.
Brandon Taylor, CTO: When Tim and I were at the Microsoft Accelerator, we interviewed pipeline operators and asked them, what is the industry problem that they’d like help to solve with data science and machine learning. They specifically said, “We’ve been running pigs for decades. We just need help aligning these over runs.” From the time when we started running the pigs to today, our first algorithm that we built was to help operators align their runs. That’s really the core feature and functionality that we have within the application: you can literally drag and drop inline inspection filing that came from the tool and instantly know your growth, where your threats are on your pipe, etcetera. That’s really the fundamental problem.
What has been the impact?
Tim: Some of the early adopters have fundamentally changed their business processes to focus on using the technology. Before, they would do all this work in Excel spreadsheets. It was a tremendously time consuming, labour intensive task. Now they’re rapidly progressing through that sphere of the operation, moving directly into integrity. We’re seeing a fundamental shift in their integrity operation, and the positive impact to their business
Brandon: We’re reducing a lot of the manual efficiencies, but probably the bigger thing is that we’re showing them things that they don’t know. That’s the fundamental thing that we’re doing with data science and machine learning. We have operators with very sophisticated in–house systems that they spent a lot of money building. They’re giving those systems up now and finding information in our solution that they didn’t find in their previous solutions.
Has being in Alberta helped you find success?
Brandon: We had the opportunity to take a clean sheet of paper and start the design work from the ground up. That’s been well received by the American operators who are under a much more prescriptive regulatory environment than Canadian operators. However, we’re modifying the app for that and having a Canadian perspective on design and build has really helped us achieve the results we’re getting in the U.S.
Who have been your major supporters?
Brandon: We do have a private preview going on with three operators. We have multiple pilots going on and we just kicked off a pilot with the super major in the U.S. We have academic support in Canada, specifically in western Alberta. Worley Parsons is a strategic partner of ours. In fact, they found us, did a pilot with us, proved out that technology and then we signed a collaborative agreement with them earlier this year. Now we’re going in and engaging with their customers to help optimize and increase efficiencies in Canada.
Tim: In the economic downturn in 2008, WorleyParsons a significant percentage of their engineers. They are starting through their digital transformation and building opportunities within their organization using machine learning technologies such as ours. We’re playing a pivotal role in their growth.
What are the plans for the future?
Brandon: Our mission statement is to predict pipeline failures to save lives and protect the environment. That’s what we’re working for. We think industry does a great job with general corrosion, running tools and excavating. We’re focusing on the last 20 percent of threats that are unknown, that humans aren’t going to catch. We’re using technology to find those threats to say in this spot, on this timeframe, this is where our failure is going to happen and we want to prevent it.
How does it feel to be an ASTech Finalist?
Tim: We’re excited about the opportunity. It’s nice to be recognized. Here we are after two years of hard work and diligence by the team and we’re kind of an overnight success story that took two years to happen.