Reservoir
In a study that applied alternative carbon carrier technology to enhanced oil recovery (EOR) scenarios, researchers at The University of Texas at Austin found that the new method recovered up to 19.5% more oil and stored up to 17.5% more carbon than conventional EOR methods.
This study assesses the advantages, constraints, and necessary enhancements of both passive and active electromagnetic techniques in the context of carbon capture and storage.
This paper presents a novel workflow with multiobjective optimization techniques to assess the integration of pressure-management methodologies for permanent geological carbon dioxide storage in saline aquifers.
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The deal significantly expands the company’s position in the Bakken Shale play of North Dakota.
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The integration of artificial intelligence/machine learning with traditional workflows marks a turning point, unleashing the immense potential of these proven techniques to address our everyday challenges in reservoir simulation.
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The honor recognizes recipients for their lasting and significant contributions in the field of IOR.
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Unconventional reservoirs bear a unique perplexity in that, at every scale, they are different from their conventional counterparts and even one another. This month’s selection of papers is all about those differences.
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This paper highlights an approach of using active hydrogen to stimulate hard-to-recover formations from candidate-well selection through pilot execution and evaluation.
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The authors of this paper review the advantages of machine learning in complex compositional reservoir simulations to determine fluid properties such as critical temperature and saturation pressure.
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This work presents an integrated multiphase flow model for downhole pressure predictions that produces relatively more-accurate downhole pressure predictions under wide flowing conditions while maintaining a simple form.
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This study describes a technique combining borehole acoustic reflection imaging with production logging in a horizontal well experiencing high water cut with the aim of enabling a mitigation plan.
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The aim of this study is to address and discuss the reservoir engineering aspects of geological hydrogen storage.
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This paper details how the reservoir modeling workflow can be accelerated, and uncertainty reduced, even for challenging greenfield prospects by constructing multiple small fit-for-purpose integrated adaptive models.