[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective

A Entezari, A Aslani, R Zahedi, Y Noorollahi - Energy Strategy Reviews, 2023 - Elsevier
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …

A review on applications of time-lapse electrical resistivity tomography over the last 30 years: Perspectives for mining waste monitoring

A Dimech, LZ Cheng, M Chouteau, J Chambers… - Surveys in …, 2022 - Springer
Mining operations generate large amounts of wastes which are usually stored into large-
scale storage facilities which pose major environmental concerns and must be properly …

Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network

Y Wang, Y Wang, Y Huang, J Yang, Y Ma, H Yu… - Applied Energy, 2019 - Elsevier
The energy network is a hub center connecting the energy supply side and the energy
demand side, which has high flexibility. At the same time, energy hub is the key to coupling …

Bayesian evidential learning of soil-rock interface identification using boreholes

HQ Yang, J Chu, X Qi, S Wu, K Chiam - Computers and Geotechnics, 2023 - Elsevier
Identification of the soil-rock interface of geological profiles has been a challenging task for
underground construction because of lack of sufficient borehole data. Traditional spatial …

[HTML][HTML] Advancing measurements and representations of subsurface heterogeneity and dynamic processes: towards 4D hydrogeology

T Hermans, P Goderniaux, D Jougnot… - Hydrology and Earth …, 2023 - hess.copernicus.org
Essentially all hydrogeological processes are strongly influenced by the subsurface spatial
heterogeneity and the temporal variation of environmental conditions, hydraulic properties …

A Monte Carlo-based framework for assessing the value of information and development risk in geothermal exploration

ND Athens, JK Caers - Applied Energy, 2019 - Elsevier
The exploration and development of geothermal energy resources carries considerable
financial risk. Due to the cost of drilling, there is often large uncertainty in the prediction of …

[HTML][HTML] Controls on flood managed aquifer recharge through a heterogeneous vadose zone: hydrologic modeling at a site characterized with surface geophysics

Z Perzan, G Osterman, K Maher - Hydrology and Earth System …, 2023 - hess.copernicus.org
In water-stressed regions of the world, managed aquifer recharge (MAR), the process of
intentionally recharging depleted aquifers, is an essential tool for combating groundwater …

Modeling Water Flow and Solute Transport in Unsaturated Soils Using Physics‐Informed Neural Networks Trained With Geoelectrical Data

P Haruzi, Z Moreno - Water Resources Research, 2023 - Wiley Online Library
Accurate modeling of water flow and solute transport in unsaturated soils is of significant
importance for precision agriculture, environmental protection and aquifer management …

Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1. 0)

Z Yin, S Strebelle, J Caers - Geoscientific Model Development, 2020 - gmd.copernicus.org
Geological uncertainty quantification is critical to subsurface modeling and prediction, such
as groundwater, oil or gas, and geothermal resources, and needs to be continuously …

Comparing well and geophysical data for temperature monitoring within a Bayesian experimental design framework

R Thibaut, N Compaire, N Lesparre… - Water Resources …, 2022 - Wiley Online Library
Temperature logs are an important tool in the geothermal industry. Temperature
measurements from boreholes are used for exploration, system design, and monitoring. The …