Harnessing Data Insights To Achieve Optimal Energy Consumption
September 28, 2017 Bill Mannel
In an age of ongoing digital advancement, leaders across all industries are seeking new ways to improve workplace productivity, ensure competitive advantage, and facilitate continued growth. Success hinges on their ability to accelerate time to value, and work more efficiently and effectively than the competition. Innovation and sustainability are key.
This is particularly true for the energy, oil, and gas (EOG) sector. As the global economy progressively moves away from fossil fuels in search of renewable resources, EOG companies are challenged to operate faster and smarter than ever before. Many organizations are utilizing high performance computing (HPC) technologies in order to streamline business operations – from analyzing troves of subsurface data and exploring known energy reserves, to discovering new resources and optimizing production. Innovations such as remote visualization tools are reshaping the industry, helping organizations harness the full power of their data to fuel data-driven decisions and establish reliable streams of revenue.
However, these technologies are merely scratching the surface of a new generation of intelligent IT. Today’s organizations need advanced HPC solutions that drive compute performance to new heights, enabling superhuman levels of cognitive computing. Artificial intelligence (AI) is the future.
Real-Time Insights Reshaping The Energy Sector
AI capabilities are rapidly transforming the HPC landscape, and these ground-breaking tools are rapidly increasing the speed, accuracy, and cost-efficiency of energy exploration and discovery (E&D). Emergent AI techniques like machine learning are being used to synthesize data from a variety of sources (i.e. flow rates, seismic vibrations, equipment durability, ocean wave height, and more) to drive optimization to each stage of the E&D and production processes. This allows companies to extract real-time data insights in order to identify patterns, predict critical outcomes, and make more informed business decisions.
In order to succeed, businesses must find ways to enable optimal energy consumption. This means reducing demand when the supply is too low or increasing demand when the supply is too high. With the help of machine learning techniques, EOG companies can assess when and where to allocate fossil fuels or electricity. That is, predictive analytics helps IT departments determine when to use a particular resource – like using an alternative source of electricity to power their equipment when wind turbines are producing a surplus of energy, instead of paying wind farms to turn off. This intelligent approach to energy consumption empowers organizations to operate as quickly and economically as possible.
AI Enabling Optimal Performance
To reap the benefits of AI-driven analytics, savvy business leaders are investing in GPU-accelerated computing, combining the massively parallel architecture of Nvidia GPUs and the optimized serial processing of CPUs to manage data-rich HPC and AI applications. As data volumes continue to rise, companies have the opportunity to harness actionable intelligence, learn, and grow with confidence.
Supported by powerful computing platforms such as the Apollo 6500 System optimized for AI workloads, HPC users can utilize Nvidia GPU accelerators to ramp up data analysis. This allows entities across the EOG sector to optimize workflow, improve the speed and accuracy of reservoir predictions, mitigate risks associated with E&D, dramatically reduce operating costs, and overcome the disruptions of tomorrow.
To learn more about how AI capabilities are helping EOG companies streamline energy discovery, extraction, and consumption, follow me on Twitter at @Bill_Mannel. I also invite you to follow @HPE_HPC and @NvidiaAI for up-to-the-minute HPC & AI news and updates.
Bill Mannel is vice president and general manager of HPC & AI Segment Solutions at Hewlett Packard Enterprise.