[图书][B] Design and analysis of simulation experiments
JPC Kleijnen - 2018 - Springer
This contribution summarizes the design and analysis of experiments with computerized
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …
Fast evaluation of pressure and saturation predictions with a deep learning surrogate flow model
E Maldonado-Cruz, MJ Pyrcz - Journal of Petroleum Science and …, 2022 - Elsevier
Numerical models for flow through porous media are essential for forecasting subsurface
fluid flow response to support optimal decision-making to develop subsurface resources …
fluid flow response to support optimal decision-making to develop subsurface resources …
Robust optimisation of water flooding using an experimental design-based surrogate model: A case study of a Niger-Delta oil reservoir
Reservoir simulations are often applied in oil field development to predict and optimise the
performance of the production process and improve the decision-making process. This …
performance of the production process and improve the decision-making process. This …
Optimizing the Value of a CO2 Water-Alternating-Gas Injection Project under Geological and Economic Uncertainties
P Ogbeiwi, KD Stephen - SPE Journal, 2024 - onepetro.org
The numerical simulations required for the robust optimization (RO) of the alternating
injection of water and CO2 in hydrocarbon reservoirs are computationally expensive due to …
injection of water and CO2 in hydrocarbon reservoirs are computationally expensive due to …
Robust optimization of subsurface flow using polynomial chaos and response surface surrogates
This study employs an inclusive framework for surrogate model-based optimization in the
presence of parametric and spatial uncertainties. The framework is applied to optimize water …
presence of parametric and spatial uncertainties. The framework is applied to optimize water …
Optimal well-placement using probabilistic learning
A new method based on manifold sampling is presented for formulating and solving the
optimal well-placement problem in an uncertain reservoir. The method addresses the …
optimal well-placement problem in an uncertain reservoir. The method addresses the …
A novel surrogate-assisted evolutionary algorithm applied to partition-based ensemble learning
We propose a novel surrogate-assisted Evolutionary Algorithm for solving expensive
combinatorial optimization problems. We integrate a surrogate model, which is used for …
combinatorial optimization problems. We integrate a surrogate model, which is used for …
Robust optimization of well location to enhance hysteretical trapping of CO2: Assessment of various uncertainty quantification methods and utilization of mixed …
The paper aims to solve a robust optimization problem (optimization in presence of
uncertainty) for finding the optimal locations of a number of CO2 injection wells for …
uncertainty) for finding the optimal locations of a number of CO2 injection wells for …
Application of Polynomial Chaos Expansion to Optimize Injection‐Production Parameters under Uncertainty
L Zhang, ZP Li, H Li, CD Adenutsi… - Mathematical …, 2020 - Wiley Online Library
The optimization of oil field development scheme considering the uncertainty of reservoir
model is a challenging and difficult problem in reservoir engineering design. The most …
model is a challenging and difficult problem in reservoir engineering design. The most …
Stochastic pix2vid: A new spatiotemporal deep learning method for image-to-video synthesis in geologic CO storage prediction
Numerical simulation of multiphase flow in porous media is an important step in
understanding the dynamic behavior of geologic CO 2 storage (GCS). Scaling up GCS …
understanding the dynamic behavior of geologic CO 2 storage (GCS). Scaling up GCS …