How Artificial Intelligence Could Help Transform The Oil Industry

How Artificial Intelligence Could Help Transform The Oil Industry

How Artificial Intelligence Could Help Transform The Oil Industry

While the oil and gas industry has had its share of ups and downs over the past decade, manyfinancial institutions are banking on a very slow growth of oil prices in 2017. Though some believe that the efficiency gains that theoil industry can capture are quickly coming to an end, this sentiment is only capturing hard technology specifically related to oil and gas.

To help bring the O&G industry to the 21 century, technology from other industries needs to be incorporated, using many hard-earned years of expertise and different lines of thinking. Oilprice previously mentioned incorporating food industry technology to increase safety standards when fracking, but incorporating technology from the IT industry is something that the O&G industry as a whole can benefit from. Whether its neural networks, machine learning, fuzzy logic, case-based reasoning or expert systems, AI has the potential to transform the industry.

When remote sensors are connected to wireless networks, data can be collected and centrally analysed from even the most exotic locations. According to the consulting firm McKinsey,there is $50 billion of savings and increased profits in the O&G supply chain to be had by adopting AI. As an example, using AI algorithms to more accurately sift through signals and noise in seismic data can decrease dry wellhead development by 10 percent. This type of technology was brought into the fortune 500 earlier this week when Intel acquired Nervana Systems, an Indian-American San Diego based startup, who was using this technology to increase operational efficiency in oil exploration.  Now with Intel’s muscle, super-majors can look to have this technology implemented across the board.

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Although the O&G industry has been using data to analyse downhole conditions, as the costs of implementation come down, these technologies are being used on smaller and smaller wells. These types of implementations can help provide early warning signals of problems before they happen.

 



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