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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In this paper, a case study is described in which a software solution enabled prescriptive optimization of well delivery using a physics-informed machine-learning approach for predictive identification and characterization of well-construction risks.
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Drilling experts recently shared candid views on what will be required for their segment of the upstream business to move to the next stage of development.
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This month’s column highlights how artificial intelligence is influencing SPE programming, publications, and new tools, while also transforming day‑to‑day operations across our industry. The column explores energy supply implications and practical field applications, showing how SPE is helping members turn AI into a tool for progress.
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The companies also agreed to collaborate on new AI models to unlock further insights from S&P Global Energy’s upstream data.
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As AI drives record heat loads in data centers, immersion liquid cooling is gaining momentum, and energy companies are lining up to support it.
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Artificial intelligence is prompting oil and gas companies to redefine roles, rethink trust, and rework operations, experts said during CERAWeek.
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The gap between machine learning research and effective deployment in the oil and gas industry is an alignment challenge between research questions and real decisions, between model design and operational constraints, and between innovation and the people expected to use it.
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Technology and partnerships remain important, while phased approaches may supplant lengthy appraisal programs, experts said during CERAWeek.
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CERAWeek panelists see AI as a way to leverage data and people in interpreting data for exploration, but a cultural shift at companies may still be needed.
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This paper describes an approach to creating a digital, interconnected workspace that aligns sensor data with operational context to place the completions engineer back into a central role.