Implementing Data Science and Intelligent Automation at Equinor
Fakhri Landolsi, COO DIGITAL COE,Head of Data Science North America at Equinor spoke to Oil & Gas IQ about how the company is centralizing all digital efforts in their Digital Centre of Excellence and how they are getting the entire company on board.Add bookmark
Fakhri Landolsi, COO DIGITAL COE, Head of Data Science North America at international energy company, Equinor, will be among the speakers at the upcoming Digital Twins in Oil & Gas ONLINE event - July 7-9.
Ahead of the online event, Fakhri sat down with Oil & Gas IQ to discuss how Equinor is using data to drive intelligent automation, centralizing digital efforts in their Digital Centre of Excellence and how they are getting the entire company on board by gaining employee buy-in through an integrated approach to data use and interpretation.
OGIQ: Can you tell us about Equinor’s COO Digital Centre of Excellence?
Fakhri: The Digital Centre of Excellence was established in mid-2017. It serves as an innovation hub, driving the digital agenda of the company. Centralizing digital efforts helps with exploring emerging technologies, such as Advanced Analytics and AI. The most important thing is to connect these technologies with real business challenges and needs. The DCoE is driving digital opportunities via three technological enablers: robotics, process digitalization, and data science with a focus on expanding the scale of our digital operations.
OGIQ: You have spoken before about how to gain buy-in and fully leverage the power of analytics. Can you elaborate on that?
Fakhri: This is the real challenge that the whole industry is facing. It’s good to develop data science solutions, but really, the value comes from moving from insights to actions. You have to ensure that the business uses these tools in their operations to realize an impact. That might be easy for machines; it’s not that easy for people and processes.
It’s really about a cultural change and emotional intelligence. In a sense, you should start small but think big. We build trust by creating quick MVPs and POVs. As a result, operators are not afraid of making decisions based on those tools. It’s a buy-in with the mindset of collaboration and an understanding of the “as is” and the “to be”.
OGIQ: Can you give us an example of one of the small quick-win projects?
Fakhri: An example is a product that uses Machine Learning to forecast production of unconventional wells. Classically, the problem was approached in a linear way. If I’m planning to forecast the production of the next 10,000 wells, then I will need the same number of reservoir engineers I needed for the first 10,000 wells. ML allows us to automate the process while incorporating subject matter expertise. This saves time for engineers to focus more on what matters and unlock the potential to run multiple “what-if” scenarios for future wells. Building trust on the results of the existing wells ML forecast is the first step. Which should be, really, a quick win, and then you keep scaling, and you build on top of that.
OGIQ: In today’s world, data is a critical asset, so how do you get the entire
organization to view it this way?
Fakhri: Honestly, I think there is a large untapped potential for data across applications and organisational boundaries. The challenge is an integrated approach to interpret and use data. We saw that in different projects. For instance, the moment you match your work orders to your safety incidents records, you unlock a huge potential to learn from previous safety incidents.
OGIQ: How are you overcoming cultural barriers to new technology and creating new ways of working?
Fakhri: Change management is key here and it should be incremental. On the organizational side, it has to be both a top-down and a bottom-up approaches. First of all, the leadership has to empower the people. Then, we need to make sure that we apply the right discipline, solutions, and technology at the right time. As a result, people will adopt these tools in their day-to-day tasks.
OGIQ: What’s next when it comes to data and analytics at Equinor?
Fakhri: It is an exciting time for advanced Data Science in Equinor. The focus now is more and more on automation. Some examples include Data Science solutions for automation & optimization with applications to offshore, onshore and renewable businesses. We should never wait for data to be perfect because that might never happen. At the end, It’s not just about Data Science as an isolated entity; it’s rather about the whole business finding value in data.
BIOGRAPHY: Fakhri has lead transformational end-to-end data science projects in multiple industries; including oil and gas, both service and majors, but also automotive and robotics. Fakhri has worked on several cutting-edge applications: inverse problems, purpose-built robotics, data-driven Diagnostics and Prognostics and Autonomous Vehicles. His focus has always been similar; creating value and leveraging all available data, moving from insights to actions. He is currently the head of Data Science North America in Equinor with exactly that same focus.