HOUSTON ─ Data collection and analytics, which have typically been utilized by upstream operators, are beginning to enter the midstream. Louis Fabbi, senior data scientist with SAS, emphasized the importance of incorporating analytics into midstream operations at the recent SAS Energy Analytics Forum in Houston.
According to Fabbi, the energy industry is in a period of extreme uncertainty related to upstream supply, the economics or break-even prices of different shales, and the cost of midstream development.
Analytics can help solve planning problems created by the uncertainty, Fabbi said.
“That’s what we’re addressing in particular through the oilfield production forecasting, simulation, data mining and creating the supply envelope with statistical certainty associated with it,” he told Hart Energy. “Once you’ve done that, you can say you have statistical confidence.”
“So that’s what we’re bringing to the table now and we’re actually implementing right now with a midstream operator.”
Traditionally there has been a gap between the strategic planning of upper management and the actual engineering or building work, Fabbi said. Data science fills that gap by modeling assets and business statistically, using mathematical representations to give insight into strategic and capital planning.
The prospect of launching a data collection or analytics program can be daunting to company leadership, but doesn’t need to be. According to Fabbi, smaller companies can benefit from easily applied, strategic data analysis, and relatively simple implementation can return big results.
Analytics for small companies are “just as important [as for large companies], just on a smaller scale,” he said. “It doesn’t have to be a $10 million implementation; it can be something more affordable for a smaller operator.”
Those smaller operators can benefit from doing their own analyses of third-party data, he said. The International Energy Agency and U.S. Energy Information Administration can be useful sources for data companies, as well as vendors like IHS, for detailed well data, he said.
“Leverage that data,” Fabbi said. “It’s there. Use it, and you could build a whole lot more confidence into what you’re trying to understand as far as risk of your capital.”
Company leadership worried about a potential investment while prices remain low should understand “that doing analytics is achievable for them,” he said. “They don't need a team of PhDs.”
A small, high-functioning analytics team can provide some quick wins with some fairly simple analysis, Fabbi said. One such quick win relates to actually knowing how much pipeline capacity isn’t being utilized.
“Understand that, and understand why you’re not using that capacity,” he said.