Reservoir simulation
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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This paper describes a modeling technique by which hydraulic fractures are represented as part of the well model rather than as any form of refinement in the simulation grid. -
Multiwell modeling of shale plays is not performed frequently. In projects in which a main objective is well spacing or completion optimization, a comprehensive multiwell reservoir-simulation study is required.
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Shale gas is fast becoming a source of energy of paramount significance for the coming years. Although commercial production has been achieved in numerous plays throughout the world, the actual physics involved is poorly understood.
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As the development of shale oil and gas becomes increasingly significant, so does the need for modeling tools for their accurate and timely forecasting.
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Initializing a reservoir simulator requires populating a 3D dynamic-grid-cell model with subsurface data and fit-for-purpose interrelational algorithms. In practice, these prerequisites rarely are satisfied fully.
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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.
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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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