Search results for: “\"machine learning\"”
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Machine Learning to Optimise Rod Pumps
This data-file summarises progress using machine learning to maximise production from mature wells, by detecting errors and optimising production. There is potential to lower global decline rates by c100kbpd per annum for over a decade, and increase each well’s NPV by $0.1M.
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Explaining Shale: Can Machine Learning Capture Complexity?
Machine learning predicts 78% of the variance in shale well productivity, suggesting $1M/well savings and 19-97% resource uplifts. This data-file presents the correlation matrix between 22 inter-related variables which co-vary with well productivity. The complexity requires “big data” approaches. We see upside from Machine Learning in shale.
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The cutting edge of shale technology?
This data-file reviews 950 technical papers from the shale industry in 2018-2020, to identify the cutting edge of shale technology. The trends show an incredible uptick in completion design, frac fluids, EOR and machine learning. Each paper is summarized and categorized. The file also shows which companies and services have a technology edge.
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Copper companies: a screen of leading producers?
This data-file is a screen of the world’s largest copper companies, across c15 miners and producers that produce half of the global market, averaging 0.9MTpa each, deriving 35% of their EBITDA from copper, at 35% EBITDA margins, with a reserve life of 27-years. Summary details are given for each copper company, and their recent AI…
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Semiconductors: outlook in energy transition?
Semiconductors are an energy technology. And they are transforming the future global energy complex, across AI, solar, electric vehicles, LEDs and other new energies. This short article summarizes our outlook for semiconductors in energy transition, and resultant opportunities across our work.
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AI: industrial applications by company?
This data-file tabulates industrial companies deploying AI, based on their patent filings. 200 leading industrial companies have filed 40,000 AI/ML-related patents in 2022-24, with 65% now developing their own AIs in house. Examples are summarized. We will continue adding to and expanding this data-file over time.
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AI energy: industrial demand and the Jevons effect?
Increasingly efficient AI should unlock ever more widespread and more sophisticated uses of AI. This is shown by reviewing 40,000 patents from 200 industrial companies. This 15-page report summarizes notable companies, patent filings, and updates our 2030 forecasts for AI energy.
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Companies mitigating radar interference of wind turbines?
Wind turbines create clutter and blind spots on radar systems, interfering with air traffic control, ocean monitoring and risks to national security and defence. These themes increasingly matter. Hence this data-file screens a dozen companies mitigating the radar interference of wind turbines, from large listed providers of next-gen radar systems, to start-ups developing nano-scale stealth…
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