Field/project development
Equinor and its partners’ investment in the Troll West Increased Gas Recovery North (TWIN) project aims to unlock around 11 Bcm of additional natural gas from the Troll field, with first production targeted as early as 2028.
The Coral Norte FLNG is to be the mirror image of the Coral Sul unit, which shipped its first cargo in 2022 after it was put into service in Area 4 offshore Mozambique.
In the fourth development phase, a planned tieback would connect resources from two North Sea discoveries to existing infrastructure at the Johan Sverdrup field, pending project sanction.
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While often associated with smaller discoveries, subsea tiebacks are playing a growing role in contributing to the broader energy mix. -
AI‑driven data center growth is straining US power grids and accelerating interest in enhanced geothermal systems as a scalable, low‑carbon solution.
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The following three papers show challenges and potential solutions across various stages of the deepwater well-development cycle from a variety of deepwater basins across the world.
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The authors describe a study on key technologies for intelligent risk monitoring of workover operations.
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This paper establishes that the use of a dual-gradient fluid column during the running of large casing in an extreme-reach deepwater well is an effective method to overcome drag and enable the casing to reach total depth.
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The authors write that by replacing outdated, labor-intensive processes with an integrated, cloud-based platform, companies can streamline planning, improve accuracy, and foster better coordination across teams and vendors.
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The authors write that deployment of artificial-intelligence-based high-gas/oil ratio well-control technology enabled stabilization of well performance and maintenance of optimal production conditions.
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This paper presents the first global application of autonomous drilling in deepwater and the journey to reach optimal drilling parameters, integrating proprietary tools from the project’s business partners.
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In this paper, a case study is described in which a software solution enabled prescriptive optimization of well delivery using a physics-informed machine-learning approach for predictive identification and characterization of well-construction risks.
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The paper describes the revalidation of a deepwater prospect that resulted in a no-drill decision.
