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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An 18-well numerical-simulation model was built to represent an operator’s Lower Shaunavon waterflood-pilot area. Numerical simulation was used, and a history match on the pilot area was performed. -
To optimize the development plan of a giant carbonate reservoir offshore Abu Dhabi to extend the production plateau and improve recovery, detailed sector models were used to facilitate the large number of required simulation runs.
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This paper proposes a framework based on proxies and rejection sampling (filtering) to perform multiple history-matching runs with a manageable number of reservoir simulations.
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The process of drilling a borehole is very complex, involving surface and downhole drilling systems that interact with the drilling fluid and the surrounding rocks.
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This article reviews methods used to understand the complexities associated with production from shale.
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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.
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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.
