[HTML][HTML] Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review
Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive
solute transport behaviors in geological formations across scales. From micro pores to …
solute transport behaviors in geological formations across scales. From micro pores to …
Subsurface sedimentary structure identification using deep learning: A review
The reliable identification of subsurface sedimentary structures (ie, geologic heterogeneity)
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
Machine-learning predictions of solubility and residual trap** indexes of carbon dioxide from global geological storage sites
Ongoing anthropogenic carbon dioxide (CO 2) emissions to the atmosphere cause severe
air pollution that leads to complex changes in the climate, which pose threats to human life …
air pollution that leads to complex changes in the climate, which pose threats to human life …
Application of artificial neural network for predicting the performance of CO2 enhanced oil recovery and storage in residual oil zones
Abstract Residual Oil Zones (ROZs) become potential formations for Carbon Capture,
Utilization, and Storage (CCUS). Although the growing attention in ROZs, there is a lack of …
Utilization, and Storage (CCUS). Although the growing attention in ROZs, there is a lack of …
Reactive chemical transport simulations of geologic carbon sequestration: Methods and applications
Z Dai, L Xu, T ** in deep saline aquifers using optimized long short-term memory
A sustainable environment by decreasing fossil fuel utilization and anthropogenic
greenhouse gases is a globally main goal due to climate change and serious air pollution …
greenhouse gases is a globally main goal due to climate change and serious air pollution …
Predicting CO2 Plume Migration in Heterogeneous Formations Using Conditional Deep Convolutional Generative Adversarial Network
Numerical simulation of flow and transport in heterogeneous formations has long been
studied, especially for uncertainty quantification and risk assessment. The high …
studied, especially for uncertainty quantification and risk assessment. The high …
Combined machine-learning and optimization models for predicting carbon dioxide trap** indexes in deep geological formations
Emissions of carbon dioxide (CO 2) are a major source of atmospheric pollution contributing
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
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 …