Testing page for app
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As the announcement of carbon sequestration projects becomes the norm, it’s time we look at what we know from a technical angle about how these projects need to be run based on the industry’s experience with enhanced oil recovery.
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The paper describes the experience of using a machine-learning model prepared by the ensemble method to prevent stuck-pipe events during well construction in extended-reach wells.
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With aggressive net-zero goals hanging overhead, countries are looking to fast-track low-carbon energy projects, and many are including nuclear in the mix.
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Drilling automation champions met to identify where this emerging technology needs to be by the end of the decade. What they ended up agreeing on most was that the business models used today are largely incompatible with the technology of the future.
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Artificial intelligence and machine learning, which can effectively mine deep insight from a large amount of drilling operational data and synthetic forward modeling data, are starting to shape the design and operations of extended-reach and complex wells.
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Teaser: This paper is intended to provide considerations for operators in developing campaigns to frame scope of work for subsea-blowout-preventer and rig-contracting strategy.
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Managed-pressure drilling has been associated as a technology used only on problematic wells and only as a last resort. However, when integrated at the beginning of operations as part of a comprehensive well plan, it becomes a performance-enhancing solution for any type of well classification, including development, directional, multilaterals, and horizontals.
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This paper describes a successful U-turn trajectory test in South Texas that has created new economic project opportunities for the company and increased optionality within challenged lease spaces across the field.
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Operator purchases outstanding interest in shallow water producing properties