Data & Analytics
This article explores how AI is transforming oil and gas operations, including its real impact on methane reduction, predictive maintenance, energy efficiency, and whether it truly delivers measurable sustainability gains or just adds complexity.
AI is evolving into a practical tool that helps geoscientists and engineers work faster, evaluate more opportunities, and manage subsurface uncertainty.
Digital drilling technologies are enabling a shift toward more predictive, efficient, and sustainable operations.
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The report highlights the fast evolution of AI with better performance, bigger investment, and rising global optimism. But job concerns, education gaps, and environmental costs reveal a more complex picture. -
Integrating financial and HR expertise boosts profitability, reduces operational risks, and enhances long-term planning—empowering HR to tackle sector-specific challenges like budget constraints and talent shortages more effectively.
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The data include high-resolution spatial layers for environmental research, monitoring, and geospatial analysis.
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The energy-focused LLM project by Aramco Americas, SPE, and i2k Connect has entered the testing phase and is on track for licensing to operators later this year.
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Although 92% of energy companies say they plan on digital technology investments, only 27% currently retrain and reskill existing employees to meet the upcoming demand, according to a recent survey from Ernst & Young.
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The company is investing $1 billion to establish the Engineering and Innovation Excellence Center (ENGINE) in Bengaluru, India.
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The department was established in October with $3 million in funding from Anuradha and Vikas Sinha and aims to advance data science education, research, and career development.
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Yujing Du made history as she was named The University of Tulsa's first female petroleum engineering faculty member in January. In this Q&A, she discusses the role of petroleum engineering in the global energy transition, diversity in STEM, and strategies for supporting women in the energy sector.
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On long-term trends, most things in the world are getting better, but gradual improvements don't make the news.
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Subsurface modeling and history matching are critical steps for driving decisions. Generative artificial intelligence can support these efforts by incorporating various sources of information and allowing for low-dimensional parameterization for history matching.
