The oil industry, it seems, has gone all-in on digital technology, having
gotten an early taste of how much various solutions can influence its cost
discipline and bottom lines. Last month, Oilprice wrote
how some in the digital tech field expected artificial intelligence for the
oil and gas industry to pass from theory into reality this year. But there’s
another segment of digital technology that is already making a splash, and
the ripples from this splash will continue to multiply this year: predictive
analytics.
Knowing what to expect from the future in terms of oil fundamentals and
prices, but also the environmental impact of their operations, has become
vital for oil and gas companies--and data analytics service providers are
only too happy to help.
“The oil and gas industry may have emerged from its last downturn, but the
pressure on companies to find new capital and operating efficiencies remains
unrelenting,” the chief technology officer of Lloyd’s Register told
Forbes’ Mark Venables. “As in other industries, demands also grow stronger
from regulators and other stakeholders to improve environmental performance
and safety. Advanced data technologies such as predictive analytics offer oil
and gas companies a means to navigate this increasingly complex landscape.”
Data analytics can also optimize production in the field by predicting
supply and demand with a view to adjusting production, but also by predicting
equipment maintenance needs that help streamlining operations and reducing
costs further, according to Emerj,
an AI-focused research company.
At the moment, oil and gas companies utilize two types of predictive
analytics solutions: predictive maintenance ones and business intelligence
ones, writes Emerj author Ayn de Jesus. The former type has to do with
anything from equipment maintenance predictions to energy consumption
optimization and solving particular problems such as pump failures. The
latter, business intelligence, comprises solutions that help oil and gas
companies set, for example, production standards, and checking if these standards
can be reached and how. Business intelligence software also provides insight
into the future of the industry and emerging trends by analyzing heaps of
structured and unstructured data. Related:
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Three years ago, research
from Bain and Company suggested that oil and gas producers could boost field
and refinery performance by between 6 and 8 percent by utilizing data
analytics technology. At the time, however, the researchers warned few
companies were taking advantage of all that data that analytics could offer.
Now the numbers must be growing as the benefits become evident. The growth of
the Internet of Things is fueling this shift as more and more devices get
connected to business networks across industries.
It looks like now that predictive analytics is gaining ground in oil and
gas, producers and refiners are moving closer to the next big step:
prescriptive analytics. Predicting when a piece of equipment will need
downtime for maintenance is good. Knowing why it will need maintenance at
this precise moment is better.
Prescriptive analytics, as one software industry insider put it in an
article for Offshore Technology, “tells the operator the root cause of the
problem.” AspenTech’s energy industry marketing director Ron Beck goes on to
explain that “It can inform them not only that the compressor is going to
fail but also that its impending failure is directly linked to the leakage of
liquid into the gas lines at a certain concentration or even just a slow
change in the pressure recorded.”
And yet the oil and gas industry has a long way to go to realize all these
potential benefits. As Forbes’ Venables notes, although over half of the 100
biggest oil industry players have demonstrated they use predictive analytics
in their operations, this leaves 43 percent that have yet to do this.
By Irina Slav for Oilprice.com
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