Digital Transformation
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.
In this interview, Sushma Bhan, energy data, AI leader, and technical director of the SPE Data Science and Engineering Analytics Technical Section, shares lessons from 3 decades at Shell, discussing digital transformation, the future of AI in upstream operations, leadership development, and career advice for the next generation of energy professionals.
Discover how AI and machine learning are transforming oil and gas field development by reducing subsurface uncertainty, optimizing development decisions, and maximizing long-term reservoir value from concept selection through production.
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As upstream operators move beyond isolated experiments, the hardest part of the AI journey is not building a model, it is making it stick. -
How 7 decades of AI research, including the emergence of agentic AI, are reshaping oil, gas, renewables, and the grid.
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In an industry that rarely slows down, memory can be a powerful engineering tool. Not in terms of nostalgia, but in perspective. Many of the activities that constituted daily operations have been so deeply transformed that new generations of engineers may never have experienced them before.
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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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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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Agentic AI could help upstream oil and gas operations reduce emissions by enabling real-time methane detection, optimizing flaring and energy use, and improving carbon capture efficiency.
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This article examines how domain experts can use no-code ML platforms to explore decision-relevant problems, validate hypotheses, quickly build prototypes, and engage more effectively with data science teams when solutions transition toward production.
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AI-driven analytics and digital platforms are reshaping offshore operations, enabling smarter, faster decision-making.
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