Reservoir
This paper discusses the effect of injected-polymer viscosity on various aspects of a project, from recovery to surface facilities, including both theoretical arguments and practical field experience—which do not always align.
This paper provides details of a pilot study conducted on multiple wells, showcasing the potential of a novel biotechnology in Bakken enhanced oil recovery.
The authors of this paper describe a method of stimulating a multizone hydrocarbon-producing well wherein a tool is deployed downhole by wireline to generate acid vapor at a target depth, allowing each interval to be treated uniquely.
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The deal significantly expands the company’s position in the Bakken Shale play of North Dakota. -
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.
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The authors investigate the utility of applying unconventional technology to low- or variably producing carbonate reservoirs to increase estimated ultimate recovery and decrease development-scale variability.
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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.
