Reservoir simulation
In this work, a perturbed-chain statistical associating fluid theory equation of state has been developed to characterize heavy-oil-associated systems containing polar components and nonpolar components with respect to phase behavior and physical properties.
In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
This study presents a production-optimization method that uses a deep-learning-based proxy model for the prediction of state variables and well outputs to solve nonlinearly constrained optimization with geological uncertainty.
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SponsoredA Midland Basin case study on estimating production, drainage volume, and interference from multiple stacked wells. -
An ensemble-based 4D-seismic history-matching case is presented in the complete paper. Seismic data are reparameterized as distance to a 4D anomaly front and assimilated with production data.
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One unfortunate consequence of a base-case model, however, is the risk of an anchoring effect, in which case we may underestimate uncertainty. Essentially, the anchoring effect refers to our tendency to rely too heavily on the information offered, introducing a bias in the model-construction process
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In the complete paper, the authors propose a novel method to rapidly update the prediction S-curves given early production data without performing additional simulations or model updates after the data come in.
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The aim of this work is to present the effectiveness of a fully integrated approach for ensemble-based history matching on a complex real-field application.
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The complete paper presents a new three-phase relative permeability model for use in chemical-flooding simulators.
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The complete paper discusses the advancements in mud-displacement simulation that overcome the limitations of the previous-generation simulator and provide a more-realistic simulation in highly deviated and horizontal wells.
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Researchers: Models Overstate Technology Impact, Understate Location Impact for Unconventional WellsTwo researchers at the MIT Energy Initiative have found that current modeling overestimates the impact of new technology on unconventional well productivity and underestimates that of increasingly targeting reservoir “sweet spots.”
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Nearly a decade after an SPE meeting in Bruges set industry-inspiring benchmarks for reservoir modeling, the time has come to overcome a new set of challenges.
