Recently, Silviu Livescu, SPE’s technical director for data science and engineering analytics, and Birol Dindoruk, recent technical director for management and information, sat down with SPE’s Nils Kaageson-Loe to discuss the state of the oil and gas industry’s digital transformation, where the industry needs to go, and how it can get there.
“Everything is proprietary, and everybody is trying to keep their data as a differentiator,” Livescu said. “So, how does the data fit in that business model? Is data something different? Should we treat it different? Or is it the way we use the data that should be different? This is a very open discussion.”
The oil and gas industry has been around for more than a century, and, during that time, the technology used has evolved. This technological evolution necessarily has led to some growing pains. “When data is generated over decades, technologies change,” Dindoruk said. “What we do in our industry often is that we look at the differentials of this data. What is different from one piece of data we got in the past vs. today? So, how much of this is because of technology and how much of this is because of real changes in the reservoir?”
He added that these data differentials could be related also to the quality of the data captured. “How much of this change is because of quality-related issues? So, quality becomes extremely important.”
While quality is important, quantity is also a concern. “We have to come up with innovations, actually, to find the balance between quality and quantity,” Livescu said. “And then we have to interpret that data. We have to find the value in it. … The time scale for this process is quite large.”
The oil and gas industry is not alone in facing the quality-vs.-quantity challenge. “We can learn, actually, from other industries because they are ahead of us,” Livescu said, adding that the oil and gas industry does have some data challenges unique to it. “In terms of subsurface data, we have to find our own way,” he said. “That’s something we really have to find to collaborate with other industries, learn from what they are doing, how they are doing it, and bring our flavor to that.”
Livescu suggested the industry rethink its approach to digital transformation. “We, as an industry, lack understanding of what data can do for us and what digital transformation means,” he said. “So, we need to start from scratch. We need actually to all of us get together and start discussing all the basic topics first and then focus on what we have done in the past and what can we do better than we did.”
“That doesn’t necessarily mean we don’t know what we’re doing,” he added, “but shows that, actually, we learn from what we know.”
Dindoruk also said the industry could benefit from an adjustment of perspective. “Things are changing fast, and we need to prioritize our focus,” he said. “But, at the end of the day, we need to look at what programs are supporting our business. And we need to be even more specific than that. We need to look at the use cases. Use cases are the building blocks for these programs that will support our strategy.”
Watch the entire discussion above.
Visit SPE’s Data Science and Engineering technical section here.
