AI AND ML IN THE OIL & GAS INDUSTRY: 10 REAL-WORLD USE CASES
DESPITE THE WIDESPREAD DIFFUSION OF RENEWABLE ENERGY TECHNOLOGIES, OIL AND GAS ARE AMONG THE MOST HIGHLY VALUED COMMODITIES IN THE ENERGY SECTOR. HOWEVER, IN THE AGE OF GLOBAL WARMING, MANY ARE WORRIED ABOUT THE TREMENDOUS ENVIRONMENTAL IMPACT OF LESS-GREEN ENERGY SOURCES. NEWER TECHNOLOGIES ARE HIGHLY SOUGHT BY OIL & GAS COMPANIES, WHO ARE ACTIVELY TRYING TO ENHANCE AND OPTIMIZE THE CONSUMPTION AND PRODUCTION OF THESE RESOURCES TO ALWAYS STAY AHEAD OF THE CURVE. NOUMAN AHMAD, CEO OF VALIDERE EXPLAINED, “OIL AND GAS DEVELOPMENT INCREASINGLY RESEMBLES A MANUFACTURING APPROACH, WHERE SPECIFIC MARGIN ENHANCEMENT INITIATIVES ARE THE KEY DIFFERENTIATORS BETWEEN PEERS.”
3 Artificial intelligence (AI) is pretty much the first in line as the key technology with all the potential to unlock a productivity revolution in the oil & gas industry. The AI market in this industry has been predicted to grow to $2.85 billion by 2022 at a compound annual growth rate of 12.66%. North America represents the leading and most advanced market – most of the top AI players in the oil & gas industry are based in this region, with names such as Google, IBM, Microsoft and Oracle. The applications of AI and machine learning (ML) in the oil & gas industry are many, and some of them can really make the difference in a sector that is seeking to renew itself. Just by leveraging the potential of predictive analytics , big data and ML in upstream oil & gas activities alone, costs could be cut by $50 billion . We can only imagine what the future may hold for this sector after this fruitful marriage between titanic machines and smart computer intelligence is celebrated. Let’s have a look at some of the most interesting current use cases and applications of AI and ML in the oil & gas industry, and how they’ve already started to make a change.
4 PREDICTIVE ASSETS MAINTENANCE Unplanned downtime represents one of the primary causes of loss for oil & gas companies. Just 3.65 days of unplanned downtime a year can cost $5.037 million, and as the average offshore company experiences roughly 27 days of unplanned downtime a year, the losses quickly mount up to a whopping $38 million. To mitigate the risk of unexpected equipment failures, predictive maintenance solutions represent the current answer across all three segments of the oil and gas industry: upstream, midstream and downstream. Expected to grow into the largest segment in AI in the oil & gas market, predictive maintenance solutions are currently the principal application of this technology. They help operators improve operational safety and turn higher profit margins at the same time. AI models that can predict equipment failure are available across all the streams of the oil & gas industry as they reduce the risk of costly accidents, minimize operating expenses by reducing downtime, and improve compliance to safety standards. All the 2.5 million miles of pipelines that distribute oil and gas across the United States come packed with industrial internet of things
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- Fall '19