Technology
Founding dean of Missouri S&T’s Kummer College, James D. Sterling, sat down with Joshua Schlegel, associate professor and associate chair of nuclear engineering and radiation science, to discuss why nuclear power is making a comeback and what its resurgence means for the future of energy.
In this interview, Purohit explains why ultrasonic technology is rising as a dominant solution for gas-flow applications and how engineering teams can approach measurement as a tool not just for accountability but also for operational excellence.
Microgrids are no longer niche innovations—they have become a foundational component of modern energy infrastructure. Realizing their full potential will require targeted policy reform, clearer regulatory frameworks, and greater access to innovative financing models.
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Register today for the SPE AI Hackathon taking place 7–9 May in Dubai. -
This article provides an overview of risk-based measurement, monitoring, and verification (MMV) for efficient, long-term CO2 storage.
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This article provides a mirror between the past and the present of well intervention technologies, including R&D to advance to downhole robots and autonomous intervention methods.
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Explore upcoming successors in energy storage technologies in Part 2 of this series.
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Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.
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These seven open-source simulators are available for free use and are among the best available in the industry.
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Dan Jeavons, Shell’s VP of computational science and digital innovation, discussed the findings in MIT’s recent report on digital technology’s impact on a net-zero emissions future with Aman Srivastava, TWA deputy editor in chief.
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The free online calculators will provide industry professionals with the opportunity to make energy processes more efficient.
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In this article, energy storage technologies are introduced as “the talk of the town” by depicting them in the form of family trees.
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Join Rodolfo Camacho and Silviu Livescu as they address some of the challenges in the application of data analytics, artificial intelligence, and machine learning (DA/AI/ML) to several reservoir engineering problems and answer some of the questions related to DA/AI/ML applications in reservoir modeling and performance prediction.
