Reservoir simulation
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
Modeling solubility trapping at reservoir scale remains a key challenge for carbon storage projects. This study introduces a novel sub-grid convective mixing model, implemented in the Open Porous Media Flow simulator and applied to the SPE11 benchmark, that enables accurate prediction of carbon dioxide dissolution trapping in geological storage using computationally e…
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.
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The paper presents a model for shale gas production in which CO2 is injected by huff ’n’ puff into a hydraulic fracture surrounded by a shale matrix. -
This study explores pitfalls experienced when using capacitance/resistance modeling as a plug-and-play technique for waterflood optimization and discusses workarounds and mitigations to improve its reliability.
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This paper analyzes several configurations of convolutional neural networks suited for predicting upscaled fracture permeabilities and shape factors required to close a dual porosity/dual permeability model.
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The authors write that simple and straightforward observations on outcrops can be used to build 3D models that mimic geological relationships accurately.
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This paper presents an integrated work flow to model mechanical properties at sufficiently high resolution to honor accurately rock fabric and its effects on height and complexity and, thus, production.
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This paper presents a comprehensive comparison of two modeling-based approaches of fluid tracking for condensate allocation and gas usage.
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The authors develop a representative geostatistically based 3D model that preserves geological elements and eliminates uncertainty of reservoir properties and volumetric estimates for a Libyan field.
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The authors examine a theory that low resistivity in a Chinese reservoir is caused by bound water trapped in clay minerals and develop an improved model for production prediction of offset wells.
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In reviewing the long list of papers this year, it has become apparent to me that the hot topic in reservoir simulation these days is the application of data analytics or machine learning to numerical simulation and with it quite often the promise of data-driven work flows—code for needing to think about the physics less.
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The authors describe the process of building multiple scenario-based models to optimize development planning in preparation for the upcoming production phase of the Ichthys field offshore Australia.
