history matching
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The authors of this paper propose a hybrid approach that combines physics with data-driven approaches for efficient and accurate forecasting of the performance of unconventional wells under codevelopment.
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This paper describes a full-field and near-wellbore poromechanics coupling scheme used to model productivity-index degradation against time.
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This paper develops a deep-learning work flow that can predict the changes in carbon dioxide mineralization over time and space in saline aquifers, offering a more-efficient approach compared with traditional physics-based simulations.
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This study presents a novel approach to screen thermally stable surfactants at high pressures and high temperatures for the explicit purpose of wettability alteration in the operator’s Eagle Ford acreage.
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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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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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This paper presents an automated calibration process, probabilistic infill well ranking, and location optimization for a major heavy oil field in Colombia with original oil in place of more than 5 million STB.
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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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The paper describes an approach to history matching and forecasting that does not require a reservoir simulation model, is data driven, and includes a physics model based on material balance.
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