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This paper focuses on the vital task of identifying bypassed oil and locating the remaining oil in mature fields, emphasizing the significance of these activities in sustaining efficient oilfield exploitation.

This paper tests several commercial large language models for information-retrieval tasks for drilling data using zero-shot, in-context learning.

In this paper, a dynamic multiphase-flow simulator is used to evaluate the effectiveness and suitability of using a subsea capping stack to respond to a CO₂ well blowout.

In this study, artificial-intelligence techniques are used to estimate and predict well status in offshore areas using a combination of surface and subsurface parameters.

Geothermal energy in the US has historically been concentrated in the West due to favorable geology, but emerging technologies have expanded the possibilities.

The objective of this paper is to outline the importance of new standards for studying hydraulic sealability of barrier materials, with an emphasis on interface analysis.

The authors of this paper describe how deployment of dual-casing cement-bond-logging technology has provided critical insights in real time for decision-making on remedial jobs.

Given the diversity of coiled tubing well-intervention data, many acquisition labels are often missing or inaccurate. The authors of this paper present a multimodal framework that automatically identifies job type and technologies used during an acquisition.

This paper presents an overview of the operator’s Marlim and Voador fields revitalization project, highlighting features and main achievements in the context of Campos Basin redevelopment.