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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In an industry where methane leaks and carbon dioxide storage are increasingly important concerns, finding new ways to seal leaks is a valuable skill.
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Several options exist for large-scale hydrogen underground storage: lined caverns, salt domes, saline aquifers, and depleted oil/gas reservoirs. In this paper, a commercial reservoir simulator was used to model cyclic injection/withdrawal from saline aquifers and depleted oil/gas reservoirs. The results revealed the need to contain the stored volume with an integrated…
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The authors of this paper present an approach integrating characterization of paleo zones, parameterization of paleo-zone conductivity, and application of flow profiles in a history-matching study of a dual-porosity/dual-permeability model.
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The authors of this paper develop a robust history-matched reservoir simulation model capable of predicting polymerflooding performance in the first such pilot to enhance heavy oil recovery on Alaska’s North Slope.
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One of the more common characteristics of heavy oil reservoirs is a low primary recovery factor, which is mainly because of unfavorable mobility ratios between oil and water, negligible solution drives, and faster decline of reservoir pressures because of relatively low oil compressibility. Most of the technologies that apply to heavy oil reservoirs need to address th…
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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.
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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.