Deep convolutional encoder‐decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media
Surrogate strategies are used widely for uncertainty quantification of groundwater models in
order to improve computational efficiency. However, their application to dynamic multiphase …
order to improve computational efficiency. However, their application to dynamic multiphase …
Recent developments in fast and scalable inverse modeling and data assimilation methods in hydrology
The last twenty years have brought significant advances in hydrology and hydrogeology,
especially in the area of data availability and predictive modeling capabilities. Remote …
especially in the area of data availability and predictive modeling capabilities. Remote …
[HTML][HTML] AI enhanced data assimilation and uncertainty quantification applied to Geological Carbon Storage
This study investigates the integration of machine learning (ML) and data assimilation (DA)
techniques, focusing on implementing surrogate models for Geological Carbon Storage …
techniques, focusing on implementing surrogate models for Geological Carbon Storage …
Hydrogeophysical characterization of nonstationary DNAPL source zones by integrating a convolutional variational autoencoder and ensemble smoother
Detailed characterization of dense nonaqueous phase liquid (DNAPL) source zone
architecture (SZA) is essential for designing efficient remediation strategies. However, it is …
architecture (SZA) is essential for designing efficient remediation strategies. However, it is …
Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection
Time-lapse electrical resistivity tomography (ERT) measurements provide
indirectobservations of hydrological processes in the Earth's shallow subsurface at high …
indirectobservations of hydrological processes in the Earth's shallow subsurface at high …
Integrating deep learning-based data assimilation and hydrogeophysical data for improved monitoring of DNAPL source zones during remediation
Data assimilation techniques allow the integration of multi-source data with physical
modeling of dense nonaqueous phase liquid (DNAPL) source zones to monitor their …
modeling of dense nonaqueous phase liquid (DNAPL) source zones to monitor their …
Deep learning-based geological parameterization for history matching CO2 plume migration in complex aquifers
History matching is crucial for reliable numerical simulation of geological carbon storage
(GCS) in deep subsurface aquifers. This study focuses on inferring highly complex aquifer …
(GCS) in deep subsurface aquifers. This study focuses on inferring highly complex aquifer …
Comparison of heat demand prediction using wavelet analysis and neural network for a district heating network
S Kováč, G Micha'čonok, I Halenár, P Važan - Energies, 2021 - mdpi.com
Short-Term Load Prediction (STLP) is an important part of energy planning. STLP is based
on the analysis of historical data such as outdoor temperature, heat load, heat consumer …
on the analysis of historical data such as outdoor temperature, heat load, heat consumer …
Dynamic Processes of CO2 Storage in the Field: 1. Multiscale and Multipath Channeling of CO2 Flow in the Hierarchical Fluvial Reservoir at Cranfield, Mississippi
A consistent picture of dynamic channeling, invasion, spreading, and breakthrough (CISB) of
supercritical CO2 in the hierarchical fluvial reservoir at Cranfield, Mississippi is presented …
supercritical CO2 in the hierarchical fluvial reservoir at Cranfield, Mississippi is presented …
Wavelet-based Kalman smoothing method for uncertain parameters processing: Applications in oil well-testing data denoising and prediction
X Feng, Q Feng, S Li, X Hou, M Zhang, S Liu - Sensors, 2020 - mdpi.com
The low-distortion processing of well-testing geological parameters is a key way to provide
decision-making support for oil and gas field development. However, the classical …
decision-making support for oil and gas field development. However, the classical …