Data & Analytics
SLB's and Baker Hughes' partnerships with NVIDIA and Google Cloud, respectively, will develop advanced AI-enabled power optimization and sustainability solutions for the global data center sector.
ExxonMobil's Jason Gahr uses the five stages of grief to explain how the upstream industry should respond to the rise of AI.
Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
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This paper delves into the evolving landscape of drilling automation, emphasizing the imperative for these systems to go beyond novelty and deliver quantifiable financial value. -
This paper presents a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight-reservoir forecasting.
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This paper describes a new application that leverages advanced machine-learning techniques in conjunction with metocean forecasts to predict vessel motions and thruster loads.
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New and evolving artificial lift technology is helping operators improve production rates.
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Data analytics practitioners in the industry have reexamined existing workflows and realized the substantial benefits that artificial intelligence brings, including increased efficiency and expedited turnaround times.
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This paper proposes a holistic, automatic, and real-time characterization of cuttings/cavings, including their volume, size distribution, and shape/morphology, while integrating 3D data with high-resolution images to pursue this objective for use in the real-time assessment of hole cleaning sufficiency and wellbore stability and, consequently, for the prediction, prev…
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Collaboration and technology will help the industry meet its toughest challenges, experts said during the opening session at ATCE.
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In this exclusive Q&A, Giovanni Cristofoli, senior vice president of bp Solutions, shares insights into how his team is redefining operational strategies and fostering agility to bridge competitive gaps and enhance efficiency. Highlights include the integration of digital tools, data science, and a unified approach to tackling complex problems.
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Accuracy, complexity, costs, and skills availability may make it difficult to get the most out of digital twins and even potentially misrepresent or miss actual changes in the status of systems or facilities.
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The new contract extends a decadelong relationship and expands the use of AI and digital twins.
