Reservoir simulation
The authors propose a deep-learning-based approach enabling near-real-time CO2-plume visualization and rapid data assimilation incorporating multiple geological realizations for predicting future CO2 plume evolution and area-of-review determination.
In this study, forward simulation is executed by a commercial reservoir simulator while external code is developed for backward calculations.
In this study, the authors propose the use of a deep-learning reduced-order surrogate model that can lower computational costs significantly while still maintaining high accuracy for data assimilation or history-matching problems.
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Looking back through previous editions of this article, I note that, in 2011, I wrote, “there’s a growing tendency in some quarters to use very simple models.” That may be true, but there is also a growing tendency among vendors to offer models with more and more features. -
Large volumes of gas can be produced at high rates with conventional horizontal- or vertical-well configurations for long periods of time from some methane-hydrate accumulations by means of depressurization-induced dissociation.
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This paper describes an all-in-one system that combines nodal-analysis and numerical-simulation models to calculate the effect of intelligent-completion components—such as swell packers, internal control valves, and inflow-control devices—on lateral production profiles.
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The Kitan oil field consists of three subsea intelligent wells. The intelligent completions were modeled in detail using commercial dynamic-simulation software to establish a sound and safe operating procedure for the well cleanup and well test.
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