Browsing SINTEF Open by Author "Bellout, Mathias"
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Collaborative optimization by shared objective function data
Angga, I Gusti Agung Gede; Bellout, Mathias; Bergmo, Per Eirik Strand; Slotte, Per Arne; Berg, Carl Fredrik (Peer reviewed; Journal article, 2022)This article presents a collaborative algorithmic framework that is effective for solving a multi-task optimization scenario where the evaluation of their objectives consists of two parts: The first part involves a common ... -
Derivative-free trust region optimization for robust well control under geological uncertainty
Silva, Thiago Lima; Bellout, Mathias; Giuliani, Caio M.; Camponogara, Eduardo; Pavlov, Alexey (Peer reviewed; Journal article, 2022)A Derivative-Free Trust-Region (DFTR) algorithm is proposed to solve the robust well control optimization problem under geological uncertainty. Derivative-Free (DF) methods are often a practical alternative when gradients ... -
Effect of CO2 tax on energy use in oil production: waterflooding optimization under different emission costs
Angga, I Gusti Agung Gede; Bellout, Mathias; Kristoffersen, Brage Strand; Bergmo, Per Eirik Strand; Slotte, Per Arne; Berg, Carl Fredrik (Peer reviewed; Journal article, 2022)Tackling emissions from hydrocarbon production is a necessity because hydrocarbon production will last for a prolonged time. As a popular hydrocarbon production method, waterflooding operation is energy-intensive and ... -
Efficient well placement optimization under uncertainty using a virtual drilling procedure
Kristoffersen, Brage Strand; Silva, Thiago Lima; Bellout, Mathias; Berg, Carl Fredrik (Peer reviewed; Journal article, 2021)An Automatic Well Planner (AWP) is used to efficiently adjust pre-determined well paths to honor near-well properties and increase overall production. AWP replicates modern geosteering decision-making where adjustments to ... -
Reduced well path parameterization for optimization problems through machine learning
Kristoffersen, Brage Strand; Bellout, Mathias; Silva, Thiago Lima; Berg, Carl Fredrik (Peer reviewed; Journal article, 2021)In this work we apply a recently developed machine learning routine for automatic well planning to simplify well parameterization in reservoir simulation models. This reduced-order parameterization is shown to be beneficial ...