Asset Management
The companies' combined technologies enable real-time control of well placement, hydraulics, and rig operations.
CERAWeek panelists see AI as a way to leverage data and people in interpreting data for exploration, but a cultural shift at companies may still be needed.
In this study, forward simulation is executed by a commercial reservoir simulator while external code is developed for backward calculations.
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Following a US military operation to arrest Venezuela’s president, analysts say there is no easy fix for the country’s beleaguered upstream sector. -
The platform brings the field’s installed production capacity to 1.5 million BOPD.
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This paper describes a data-driven well-management strategy that optimizes condensate recovery while preserving well productivity.
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This study identifies critical knowledge gaps in wellbore integrity and underscores areas that require further investigation, providing insights into how wellbores must evolve to meet the technical demands of the energy transition.
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This study illustrates the new capabilities, tailored for carbon-dioxide storage applications, of a modeling framework that provides a quantitative, risk-based assessment of the long-term integrity of legacy plugged and abandoned wells.
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This paper addresses the difficulty in adjusting late-stage production in waterflooded reservoirs and proposes an integrated well-network-design mode for carbon-dioxide enhanced oil recovery and storage.
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Only about one-third of Africa’s discovered hydrocarbon resources have reached commercialization.
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This article is the sixth and final Q&A in a series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this final edition, Matthew T. Balhoff, SPE, of The University of Texas at Austin shares his views on the future of upstream education.
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This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively.
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The authors of this paper apply a deep-learning model for multivariate forecasting of oil production and carbon-dioxide-sequestration efficiency across a range of water-alternating-gas scenarios using field data from six legacy carbon-dioxide enhanced-oil-recovery projects.
