Data & Analytics
With the latest addition, the Italian major’s computational capacity passes the exaflop threshold, making the firm the world’s leading company by computing power in the new TOP500 global ranking.
This case study describes how edge computing and industrial internet of things platforms were deployed to automate and optimize production operations across four distinct basins.
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
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The authors present an artificial-intelligence and machine-learning technology to obtain a high-level, comprehensive view of all equipment in a facility to detect and map corrosion. -
It appears to be possible to sense how fractures change during production using ultrasensitive fiber-optic strain measurements.
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This paper provides an alternative solution to identifying, classifying, and vertically distributing fractures and a lateral distribution method for reservoir modeling.
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The paper demonstrates the ability of deep-learning generative models to enable new shale-characterization methods.
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This paper describes a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.
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This third installment of the Digital Data Acquisition Technology Focus will focus on computer vision for improved data acquisition. Computer vision is defined as a field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos.
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SponsoredEach well drilled, stimulated, and completed represents a significant investment in time, resources, and expenses. From artificial lift system design to maintenance scheduling, maximize your investment by ensuring optimal flow and production throughout the life cycle.
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Integrating physics and machine learning combines the best of the two worlds, resulting in higher accuracy, better scalability, and cost efficiency.
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This paper describes the current challenges faced by energy companies, the implications of observable industry trends, the characteristics that potential cybersecurity solutions must meet, and how artificial intelligence (AI) and machine learning (ML) can meet these requirements.
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Totally automated drilling today looks like a robot doing all the heavy lifting on a drilling floor. By 2025, there may no longer be anything surprising about it.
