Digital Transformation
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.
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.
AI-driven analytics and digital platforms are reshaping offshore operations, enabling smarter, faster decision-making.
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Rajiv Nischal, head of ONGC’s Institute of Production Engineering and Ocean Technology (IPEOT), shares the company's latest developments in technology, sustainability, safety, and more. -
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.
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David Nnamdi, SPE, speaks about his work as a data scientist and engineer, his development of Sequestrix, an open-source CO2 transport network optimization tool, and where he sees data science and AI’s role in the future of sustainable energy.
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AI is beginning to transform well management by helping engineers predict electrical submersible pump failures before they happen, optimize drawdown more efficiently, and generate reliable forecasts even when data is scarce or noisy.
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The oil and gas industry's shift to smart fields—driven by automation, AI, and real-time data—requires petroleum engineers to master digital technologies alongside traditional skills.
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Tiger Skid, a custom-built cyber-physical training and testing platform, simulates real-world energy systems and industrial processes vulnerable to cyber-physical attacks.
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As the energy sector rapidly evolves to address climate change, tools such as the En-ROADS Climate Solutions Simulator are essential for young professionals seeking to understand the complexities of the transition and make informed, impactful decisions.
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Artificial intelligence is transforming—not replacing—petroleum engineering. As AI-driven, data-centric methods replace traditional deterministic models, engineers must adapt by acquiring skills in data science, algorithmic thinking, and software tools. The industry’s evolution raises a critical question: Will petroleum engineers evolve with these changes or risk beco…
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Digital transformation in the oil and gas industry is likened to a major home renovation—requiring a clear vision, skilled collaboration, patience, and investment in lasting solutions. Though the process is challenging, the end goal is an improved, future-ready operation.
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Students at the Melbourne, Australia, university took home first place at the 32nd US-based Intelligent Ground Vehicle Competition.
