FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387525629> ?p ?o ?g. }

• W4387525629 endingPage "21" @default.
• W4387525629 startingPage "1" @default.
• W4387525629 abstract "Summary In well control (production) optimization, the computational cost of conducting a full-physics flow simulation on a 3D, rich grid-based model poses a significant challenge. This challenge is exacerbated in a robust optimization (RO) setting, where flow simulation must be repeated for numerous geological realizations, rendering RO impractical for many field-scale cases. In this paper, we introduce and discuss a new optimization workflow that addresses this issue by providing computational efficiency, i.e., achieving a near-global optimum of the predefined objective function with minimal forward model (flow-simulation) evaluations. In this workflow, referred to as “Bayesian optimization (BO),” the objective function for samples of decision (control) variables is first computed using a proper design experiment. Then, given the samples, a Gaussian process regression (GPR) is trained to mimic the surface of the objective function as a surrogate model. While balancing the dilemma to select the next control variable between high mean, low uncertainty (exploitation) and low mean, high uncertainty (exploration), a new control variable is selected, and flow simulation is run for this new point. Later, the GPR is updated, given the output of the flow simulation. This process continues sequentially until the termination criteria are satisfied. To validate the workflow and obtain a better insight into the detailed steps, we first optimized a 1D problem. The workflow is then implemented for a 3D synthetic reservoir model to perform RO in a realistic field scenario (8-dimensional and 45-dimensional optimization problems). The workflow is compared with two other commonly used gradient-free algorithms in the literature: particle swarm optimization (PSO) and genetic algorithm (GA). The main contributions are (1) developing a new optimization workflow to address the computational cost of flow simulation in RO, (2) demonstrating the effectiveness of the workflow on a 3D grid-based model, (3) investigating the robustness of the workflow against randomness in initiation samples and discussing the results, and (4) comparing the workflow with other optimization algorithms, showing that it achieves same near-optimal results while requiring only a fraction of the computational time." @default.
• W4387525629 created "2023-10-12" @default.
• W4387525629 creator A5021398723 @default.
• W4387525629 creator A5077092071 @default.
• W4387525629 creator A5093041902 @default.
• W4387525629 date "2023-10-01" @default.
• W4387525629 modified "2023-10-12" @default.
• W4387525629 title "Reservoir Production Management With Bayesian Optimization: Achieving Robust Results in a Fraction of the Time" @default.
• W4387525629 cites W1510052597 @default.
• W4387525629 cites W1659842140 @default.
• W4387525629 cites W1983495669 @default.
• W4387525629 cites W1993899643 @default.
• W4387525629 cites W2000359198 @default.
• W4387525629 cites W2024458338 @default.
• W4387525629 cites W2051554019 @default.
• W4387525629 cites W2054875385 @default.
• W4387525629 cites W2060992645 @default.
• W4387525629 cites W2071503854 @default.
• W4387525629 cites W2118600027 @default.
• W4387525629 cites W2131374225 @default.
• W4387525629 cites W2157164625 @default.
• W4387525629 cites W2171149164 @default.
• W4387525629 cites W2192203593 @default.
• W4387525629 cites W2297102182 @default.
• W4387525629 cites W2325836425 @default.
• W4387525629 cites W2501741252 @default.
• W4387525629 cites W2505264304 @default.
• W4387525629 cites W2520800810 @default.
• W4387525629 cites W2691272432 @default.
• W4387525629 cites W2794574709 @default.
• W4387525629 cites W2894825953 @default.
• W4387525629 cites W2971636509 @default.
• W4387525629 cites W2980004100 @default.
• W4387525629 cites W2981894749 @default.
• W4387525629 cites W3097803813 @default.
• W4387525629 cites W3105775121 @default.
• W4387525629 cites W3109065714 @default.
• W4387525629 cites W4242053123 @default.
• W4387525629 cites W4287448254 @default.
• W4387525629 cites W614342786 @default.
• W4387525629 doi "https://doi.org/10.2118/217985-pa" @default.
• W4387525629 hasPublicationYear "2023" @default.
• W4387525629 type Work @default.
• W4387525629 citedByCount "0" @default.
• W4387525629 crossrefType "journal-article" @default.
• W4387525629 hasAuthorship W4387525629A5021398723 @default.
• W4387525629 hasAuthorship W4387525629A5077092071 @default.
• W4387525629 hasAuthorship W4387525629A5093041902 @default.
• W4387525629 hasConcept C119857082 @default.
• W4387525629 hasConcept C126255220 @default.
• W4387525629 hasConcept C127413603 @default.
• W4387525629 hasConcept C131675550 @default.
• W4387525629 hasConcept C177212765 @default.
• W4387525629 hasConcept C2778049539 @default.
• W4387525629 hasConcept C2778668878 @default.
• W4387525629 hasConcept C33923547 @default.
• W4387525629 hasConcept C41008148 @default.
• W4387525629 hasConcept C77088390 @default.
• W4387525629 hasConcept C78762247 @default.
• W4387525629 hasConceptScore W4387525629C119857082 @default.
• W4387525629 hasConceptScore W4387525629C126255220 @default.
• W4387525629 hasConceptScore W4387525629C127413603 @default.
• W4387525629 hasConceptScore W4387525629C131675550 @default.
• W4387525629 hasConceptScore W4387525629C177212765 @default.
• W4387525629 hasConceptScore W4387525629C2778049539 @default.
• W4387525629 hasConceptScore W4387525629C2778668878 @default.
• W4387525629 hasConceptScore W4387525629C33923547 @default.
• W4387525629 hasConceptScore W4387525629C41008148 @default.
• W4387525629 hasConceptScore W4387525629C77088390 @default.
• W4387525629 hasConceptScore W4387525629C78762247 @default.
• W4387525629 hasLocation W43875256291 @default.
• W4387525629 hasOpenAccess W4387525629 @default.
• W4387525629 hasPrimaryLocation W43875256291 @default.
• W4387525629 hasRelatedWork W188202134 @default.
• W4387525629 hasRelatedWork W1981780420 @default.
• W4387525629 hasRelatedWork W2182707996 @default.
• W4387525629 hasRelatedWork W2950792054 @default.
• W4387525629 hasRelatedWork W2964988449 @default.
• W4387525629 hasRelatedWork W3187720583 @default.
• W4387525629 hasRelatedWork W4237912051 @default.
• W4387525629 hasRelatedWork W4292081304 @default.
• W4387525629 hasRelatedWork W4380627621 @default.
• W4387525629 hasRelatedWork W45233828 @default.
• W4387525629 isParatext "false" @default.
• W4387525629 isRetracted "false" @default.
• W4387525629 workType "article" @default.