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Operators are turning to new gas-lift and nanoparticle-fluid technologies to drive up production rates.

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.

Only about one-third of Africa’s discovered hydrocarbon resources have reached commercialization.

This work presents the development of fast predictive models and optimization methodologies to evaluate the potential of carbon-dioxide EOR and storage operations quickly in mature oil fields.

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.

This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively.

This paper presents a novel application of artificial intelligence in computer vision for automating blowout-preventer pressure-chart-data extraction, demonstrating significant efficiency gains and a high return on investment.

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.

This paper assesses the technical feasibility of geological carbon storage in the operator’s Brazilian brownfields, focusing on mature oil fields and associated saline aquifers.

SPE technical papers synopsized in each monthly issue of JPT are available for download for SPE members for 2 months.