AI/machine learning
The deals, with a potential value exceeding $3.7 billion, are aimed at strengthening Saudi Aramco’s supply chains and expanding its use of industrial artificial intelligence.
This work applies fuzzy logic, a well-established artificial-intelligence technique, to quantitatively assess connectivity between injectors and producers in a giant presalt field in the Santos Basin of Brazil.
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
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Blending smart-proxy models with data-driven models to create hybrid models is not always the best idea for physics- and engineering-related applications. -
Equinor is working on a natural language processing tool that could combine data sources and help planners anticipate the issues that affect onsite operational safety.
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Even the most powerful computers are still no match for the human brain when it comes to pattern recognition, risk management, and other similarly complex tasks. A new approach, however, could enable parallel computation with light, simulating the way neurons respond in the human brain.
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Artificial intelligence tools present many opportunities for the energy industry, and, as technological concepts leave the realm of science fiction, companies have started to grasp what is possible. What roles do culture and ethics play in helping companies understand the digital revolution?
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This paper highlights the results of a test campaign for a tool designed to predict the short-term trends of energy-efficiency indices and optimal management of a production plant.
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Recently, AI researchers from Microsoft open-sourced the Decentralized & Collaborative AI on Blockchain project that enables the implementation of decentralized machine-learning models based on blockchain technologies.
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Baker Hughes is still a GE company, but it has partnered with a second company for artificial intelligence expertise, C3.ai. The deal is expected to speed the integration of AI into oilfield operations by the company which also markets GE’s device analytics platform, Predix.
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Baker Hughes, a GE company, (BHGE) and C3.ai announced a joint venture agreement that brings together BHGE’s fullstream oil and gas expertise with C3.ai’s unique artificial-intelligence software suite to deliver digital transformation technologies and drive productivity for the oil and gas industry.
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Researchers at the University of Massachusetts, Amherst, performed a life-cycle assessment for training several common large AI models. They found that the process can emit more than 626,000 lbm of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car.
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Random Forest and Neural Network are the two widely used machine-learning algorithms. What is the difference between the two approaches? When should one use Neural Network or Random Forest?
