Data & Analytics
This article from Murphy Oil outlines a modernization effort that resulted in increased scenario simulation capacity by five to 10 times.
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This paper presents the large-scale deployment and operational integration of an advanced, automated rheometer in the Ghawar gas field, one of the world’s most prolific and technically complex hydrocarbon developments.
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The Regulators’ Pioneer Fund has provided the North Sea Transition Authority with funding for two data work streams—a data viewer and an AI chatbot—to facilitate access to the vast amounts of North Sea data. -
Industry experts dissected the challenges in deploying artificial intelligence across the energy sector during a special session at SPE’s Annual Technical Conference and Exhibition.
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AI is transforming the field of cybersecurity, offering new possibilities and challenges for both defenders and attackers, but AI also can introduce new vulnerabilities and risks and raise new ethical, legal, and social issues for cybersecurity.
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The freely accessible online platform is the latest in a series of maps designed to reveal the continent’s untapped geothermal potential.
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The companies say they plan to use AI to unlock value from terabytes of data upstream and across FPSO operations.
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This paper proposes how the strengths of cloud computing can become key enablers for oil and gas organizations in helping them enhance their overall security posture and manage risks within operational-technology environments.
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The technology to desalinate and reuse produced water for cooling AI data centers in the Permian Basin exists, but addressing cost challenges remains critical to widespread adoption.
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This paper presents a case study highlighting the demonstration, refinement, and implementation of a machine-learning algorithm to optimize multiple electrical-submersible-pump wells in the Permian Basin.
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This paper presents a closed-loop iterative well-by-well gas lift optimization workflow deployed to more than 1,300 operator wells in the Permian Basin.
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This paper explores the use of machine learning in predicting pump statuses, offering probabilistic assessments for each dynacard, automating real-time analysis, and facilitating early detection of pump damage.
