Making big data meaningful to energy companies

 In News

Energy and oil & gas companies collect a massive amount of data that has the potential to significantly reduce costs. However, without proper analysis and implementation in decision-making, it’s all just numbers. Here’s what the industry needs to be doing to make the most out of big data.

Making big data meaningful

The Accenture and Microsoft Digital Energy Trends Survey 2016 found that the majority of oil and gas companies are now investing in digital technologies to reduce costs. 38 per cent of companies surveyed were also expected to invest more in big data and analytics over the next three to five years in a bid to increase efficiencies and reduce costs.

While digital technology and the collection of operational data are not new concepts for these industries, the idea of using data in future decision-making is something that hasn’t been fully realised, but is essential for the industry’s future.

Associate Professor of Technology Management and Strategy at Queensland University of Technology, Robert Perrons, said energy industries haven’t really thought about data being an asset itself.

“People used to think revenue only comes from oil and gas moving through pipes, and that the ‘asset’ is only a physical thing,” Assoc Prof Perrons said.

“So the industry collects more data than they actually use, and either throw a lot of it away, or mothball it so that it’s all but useless.

“But this data is going to be mission-critical moving forward.”

Weaving data into decisions

Of the myriad sources of data in the upstream oil and gas industry two types are of particular interest by energy companies: operational, and health and safety. Operational data is production information that can be measured in the field and in wells – things that ensure equipment continues to run. Health and safety combines production and personal data to assess if there are ways to make operations safer.

Assoc Prof Perrons said while it’s easy to talk about data as a figurative concept, one practical solution companies can implement to start monetising their data is to create the role of a “data scientist”.

A data scientist is someone with specialised knowledge of the industry – control systems, how data is physically collected, etc – in addition to a strong background in the kinds of mathematics and statistics that allow them to understand what the data is telling them. Their role is to be the bridge between the raw data and the company’s decision-makers.

“The data scientist speaks the language of data. They know how to take all this complex information and put it in front of non-math people and say, ‘Here’s what this means’.

“Most oil and gas companies have nothing that resembles this data scientist profile at the moment. However, companies that are doing big data well have learned that this role is key.

“I’m pretty confident that, in the long-term, data scientists will be widespread, and will play a material role in companies that successfully learn how to survive the current market shakeout,” Assoc Prof Perrons said.

Low price environment calls for analysis

Wade Elofson, founder of Powered, an Australian energy and resource-focused business development company, said current economic conditions have forced the oil and gas industry to think smarter about their operations and find new ways to cut costs, with analysis of this data being one of the key ways to do this.

“Margins are lower which has created this collective awareness that we’re going to have to get a lot smarter about how we operate,” Mr Elofson said.

“For example, Australian information management company Mipela GeoSolutions’ X-Info Service Suite is allowing users to not only collect operational data but also distribute the information to the appropriate people in the company.

“If a worker discovers something in the field that could impact production or pose a safety risk, they can use X-info Service Suite which is installed on their handhelds to capture information and transmit it instantly to the manager in charge.

“This sort of technology is not only collecting data, but making informed decisions based on this data, to either help production or eliminate a safety risk.”

The industry has a significant amount of data available to it, and Assoc Prof Perrons said that this information now has to be applied to the decision-making process in order to make operations more efficient. These efficiencies will ultimately save companies money.

“We’re knee deep in ones and zeroes, but it’s currently not helping us make better choices, because the data is not finding its way into the fabric of our decision making,” Assoc Prof Perrons said.

“We need to bring about a cultural change where we are materially changing how we make decisions on the back of that data.”

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