Data & Analytics
2026 TWA Energy Influencer Muhammad Karimi shares how he transformed academic research into a globally deployed energy technology, offering insights on innovation, entrepreneurship, oilfield digitalization, and the energy transition.
Discover how AI leader Fatai Anifowose transformed skepticism into innovation, sharing insights on artificial intelligence in energy, leadership, continuous learning, and the skills shaping the future of the industry.
Utkarsh Sinha, 2026 TWA Energy Influencer, is driving innovation at the intersection of reservoir physics and AI, combining research, patents, and industry leadership to develop practical machine learning solutions that improve reservoir and production engineering decision-making.
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Machine learning is transforming equipment reliability by enabling predictive maintenance, improving safety, and reducing costly downtime across drilling, production, pipelines, and CCUS operations. -
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.
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AI is evolving into a practical tool that helps geoscientists and engineers work faster, evaluate more opportunities, and manage subsurface uncertainty.
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Digital drilling technologies are enabling a shift toward more predictive, efficient, and sustainable operations.
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Breakthroughs in energy, similar to those seen in AI, require coordinated progress across multiple fields and the resolution of structural bottlenecks. As a result, a successful energy transition depends on integrated advances in infrastructure, policy, technology, and investment rather than isolated efforts.
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The Genesis Mission is a US Department of Energy initiative that integrates AI, national labs, and cross-sector collaboration to accelerate scientific discovery, strengthen energy innovation, and enhance national security.
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This commentary by the chair of the SPE Data Science and Engineering Analytics Technical Section examines how AI is reshaping petroleum engineering careers, highlighting growing risks to entry‑level training, judgment development, and the future pipeline of subject-matter experts in high‑consequence industries.
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Lean Six Sigma, through its DMAIC framework, offers a data‑driven approach for reducing waste and variation in oil and gas operations and is explored here as a practical solution for improving drill-bit inventory and lease management despite limited industry adoption.
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The 2-day event will explore the evolving role of quantum computing in oil and gas applications.
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The event, taking place on 2 April, will explore the theme "Beyond Automation: AI as the Catalyst Reshaping the Oil and Gas Industry."
