Machine learning in subsurface geothermal energy: Two decades in review
This paper reviews the trends in applying machine learning to subsurface geothermal
resource development. The review is focused on the machine learning applications over the …
resource development. The review is focused on the machine learning applications over the …
Optimal design, operational controls, and data-driven machine learning in sustainable borehole heat exchanger coupled heat pumps: Key implementation challenges …
The integration of technologies has made it possible to develop optimal operating conditions
at reduced costs, which results in a more sustainable energy transition away from fossil fuels …
at reduced costs, which results in a more sustainable energy transition away from fossil fuels …
Physical laws meet machine intelligence: current developments and future directions
The advent of technology including big data has allowed machine learning technology to
strengthen its place in solving different science and engineering complex problems …
strengthen its place in solving different science and engineering complex problems …
A review of proxy modeling highlighting applications for reservoir engineering
Numerical models can be used for many purposes in oil and gas engineering, such as
production optimization and forecasting, uncertainty analysis, history matching, and risk …
production optimization and forecasting, uncertainty analysis, history matching, and risk …
[HTML][HTML] Deep learning based closed-loop well control optimization of geothermal reservoir with uncertain permeability
To maximize the economic benefits of geothermal energy production, it is essential to
optimize geothermal reservoir management strategies, in which geologic uncertainty should …
optimize geothermal reservoir management strategies, in which geologic uncertainty should …
Review of machine learning methods applied to enhanced geothermal systems
L Wang, Z Yu, Y Zhang, P Yao - Environmental Earth Sciences, 2023 - Springer
The objective of this study was to summarize the progress in the application of machine
learning (ML) to enhanced geothermal systems (EGSs), including the entire process of EGS …
learning (ML) to enhanced geothermal systems (EGSs), including the entire process of EGS …
Machine learning-based performance prediction for ground source heat pump systems
X Zhang, E Wang, L Liu, C Qi - Geothermics, 2022 - Elsevier
The coefficient of performance (COP) prediction of heat pump units and ground source heat
pump (GSHP) systems are required for effective evaluation, optimization, and fault diagnosis …
pump (GSHP) systems are required for effective evaluation, optimization, and fault diagnosis …
Heat transfer mechanism of cold-water pipe in ocean thermal energy conversion system
L Mao, C Wei, S Zeng, M Cai - Energy, 2023 - Elsevier
Ocean thermal energy is clean and renewable. In recent years, many scholars have focused
on improving the generation efficiency of the ocean thermal energy conversion system. To …
on improving the generation efficiency of the ocean thermal energy conversion system. To …
Deep learning reservoir porosity prediction method based on a spatiotemporal convolution bi-directional long short-term memory neural network model
J Wang, J Cao, S Yuan - Geomechanics for Energy and the Environment, 2022 - Elsevier
A relationship exists between petrophysical logs and reservoir porosity; however, obtaining
analytic solutions is challenging. In this study, we propose a novel method for porosity …
analytic solutions is challenging. In this study, we propose a novel method for porosity …
Probing geothermal heat source based on the fuzzy inference of heat process
Reconstructing the geothermal temperature field is the priority of geothermal better
utilization. The inverse heat transfer methodology provides a reliable mentality to explore …
utilization. The inverse heat transfer methodology provides a reliable mentality to explore …