Reservoir simulation
This study applies Monte Carlo simulation and an XGBoost regression model to assess the influence of various formations, geologic provinces, tectonic-plate types, and boundary conditions on hydrogen concentrations.
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.
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The authors of this paper define a work flow that constrains solutions that match models and field observations and obtains a more-representative model for forecasting and optimizing fracture behavior. -
The opening ceremony highlighted maximizing production sustainably to meet global demand, integration of simulation and optimization in a single platform with automation, and energy security.
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The authors of this paper describe a three-way coupled modeling approach that integrates dynamic, geochemistry, and geomechanics models to obtain cumulative effects of all three changes to evaluate future carbon dioxide storage.
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In this study, surfactants that can alter wettability or develop ultralow interfacial tension were identified through laboratory measurements for a target carbonate reservoir.
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The authors of this paper present an application of a Bayesian framework for uncertainty assessment and efficient history matching of a Permian CO2 enhanced oil recovery field for reliable production forecast.
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This paper presents results from evaluating the rate of thermal energy that can be extracted under various completion scenarios in end-of-life oil and gas wells using a transient flow simulator.
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This paper presents a numerical simulation work flow, with emphasis on hydraulic fracture simulation, that optimizes well spacing and completion design simultaneously.
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The authors discuss the development of a deep-learning model to identify errors in simulation-based performance prediction in unconventional reservoirs.
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The authors of this paper compare case studies from the Bakken and the STACK plays to conclude that mineralogy, petrophysics, and reservoir-condition differences between basins cause differences in the effect of fracture-driven interactions.
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The authors of this paper propose a novel approach to data-driven modeling for transient production of oil wells.
