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.
AI and machine learning are transforming drilling execution, detecting downhole problems earlier, automating reporting, and closing the loop between the wellbore and the well plan through real-time geosteering.
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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. -
As upstream operators move beyond isolated experiments, the hardest part of the AI journey is not building a model, it is making it stick.
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Rodriguez reflects on engineering growth, systems thinking, and how strong technical foundations remain valuable across evolving industries.
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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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Machine learning is transforming equipment reliability by enabling predictive maintenance, improving safety, and reducing costly downtime across drilling, production, pipelines, and CCUS operations.
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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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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.
