Drilling
More than 900 drilling and well professionals from 30+ countries gathered at APDT 2026 in Bali to explore how AI, automation, and advanced well technologies are driving safer, smarter, and more efficient drilling across Asia Pacific.
As managed pressure drilling gains traction, its principles are influencing a wider range of well-construction activities.
This paper presents laboratory-testing methods and evaluation criteria designed to improve understanding of both the origin and extent of formation damage associated with CO2 injection.
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Everywhere you look these days, there is talk of how advances in big data, artificial intelligence, and machine learning will revolutionize virtually every aspect of our lives. This month, we will look at how researchers in the drilling domain are using this potential to improve well construction. -
In this paper, the authors propose a regression machine-learning model to predict stick/slip severity index using sequences of surface measurements.
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By boosting gas supplies to Egypt’s home market, Cairo can return its focus to developing an LNG export hub.
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This selection of cutting-edge articles spotlights how experimental concepts are now driving cost-saving strategies in unconventional development. It’s a reminder that innovation often comes from creative thinking, not just new tools or tech partnerships.
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The new wells at Zohr are key to a plan to return Egypt’s gas production back to “pre-crisis” levels by June 2025.
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The Libyan National Oil Company plans to tender 22 onshore/offshore exploration blocks in 2025 as it works to rebuild credibility with foreign oil producers.
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This paper investigates the effect of calcium oxide as an expansive agent on the performance of geopolymer-based sealing materials, with successful application in oil and gas wells at shallow depths.
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Operator TotalEnergies and rig owner Vantage Drilling form joint venture to purchase the Tungsten Explorer.
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The decision invokes a 1953 law that will make it difficult for incoming US President Donald Trump to reverse.
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This paper tests several commercial large language models for information-retrieval tasks for drilling data using zero-shot, in-context learning.
