Towards a robust parameterization for conditioning facies models using deep variational autoencoders and ensemble smoother
SWA Canchumuni, AA Emerick… - Computers & Geosciences, 2019 - Elsevier
Ensemble-based methods have been applied with remarkable success for data assimilation
in geosciences. However, they sometimes fail to preserve the geological realism of the …
in geosciences. However, they sometimes fail to preserve the geological realism of the …
An integrated inversion framework for heterogeneous aquifer structure identification with single-sample generative adversarial network
Generating reasonable heterogeneous aquifer structures is essential for understanding the
physicochemical processes controlling groundwater flow and solute transport better. The …
physicochemical processes controlling groundwater flow and solute transport better. The …
Ensemble-based data assimilation in reservoir characterization: A review
This paper presents a review of ensemble-based data assimilation for strongly nonlinear
problems on the characterization of heterogeneous reservoirs with different production …
problems on the characterization of heterogeneous reservoirs with different production …
Machine learning assisted history matching for a deepwater lobe system
High exploration costs resulting in sparse datasets and complicated geological structures in
deepwater depositional systems make the reservoir characterization extremely difficult. To …
deepwater depositional systems make the reservoir characterization extremely difficult. To …
Efficient assessment of reservoir uncertainty using distance-based clustering: a review
This paper presents a review of 71 research papers related to a distance-based clustering
(DBC) technique for efficiently assessing reservoir uncertainty. The key to DBC is to select a …
(DBC) technique for efficiently assessing reservoir uncertainty. The key to DBC is to select a …
Characterization of the non-Gaussian hydraulic conductivity field via deep learning-based inversion of hydraulic-head and self-potential data
Accurate characterization of the spatial heterogeneity of hydraulic properties such as
hydraulic conductivity (K) is essential for understanding groundwater flow and contaminant …
hydraulic conductivity (K) is essential for understanding groundwater flow and contaminant …
A deep learning‐based data assimilation approach to characterizing coastal aquifers amid non‐linearity and non‐Gaussianity challenges
Seawater intrusion (SI) poses a substantial threat to water security in coastal regions, where
numerical models play a pivotal role in supporting groundwater management and …
numerical models play a pivotal role in supporting groundwater management and …
Geological model sampling using PCA-assisted support vector machine for reliable channel reservoir characterization
History matching is a crucial procedure for predicting reservoir performances and making
decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it …
decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it …
Characterization of three-dimensional channel reservoirs using ensemble Kalman filter assisted by principal component analysis
Abstracts Ensemble-based analyses are useful to compare equiprobable scenarios of the
reservoir models. However, they require a large suite of reservoir models to cover high …
reservoir models. However, they require a large suite of reservoir models to cover high …
Feature extraction using a deep learning algorithm for uncertainty quantification of channelized reservoirs
Reservoir models are generated by geostatistics using available static data. However, there
is inherent uncertainty in the reservoir models due to limited information. A number of …
is inherent uncertainty in the reservoir models due to limited information. A number of …