Productivity prediction of a multilateral-well geothermal system based on a long short-term memory and multi-layer perceptron combinational neural network-Reference-Cited by-同舟云学术

Productivity prediction of a multilateral-well geothermal system based on a long short-term memory and multi-layer perceptron combinational neural network

Published:2021-01 Issue: Volume:282 Page:116046
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Shi Yu,Song Xianzhi,Song Guofeng

Funder

National Natural Science Foundation of China

Ministry of Education of the People's Republic of China

Ministry of Science and Technology of the People's Republic of China

Beijing Municipal Commission of Education

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference32 articles.

1. Numerical simulation of heat extraction performance in enhanced geothermal system with multilateral wells;Song;Appl Energy,2018

2. Study on wellbore fluid flow and heat transfer of a multilateral-well CO2 enhanced geothermal system;Shi;Appl Energy,2019

3. Numerical investigation on heat extraction performance of a multilateral-well enhanced geothermal system with a discrete fracture network;Shi;Fuel,2019

4. Numerical study on heat extraction performance of a multilateral-well enhanced geothermal system considering complex hydraulic and natural fractures;Shi;Renew Energy,2019

5. Halldora G, Roland NH. Prediction modeling for geothermal reservoirs using deep learning. In: Proceedings of the 45th Workshop on Geothermal Reservoir Engineering, February 10–12, 2020, Stanford University, California.

Cited by 85 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Theoretical analysis of using multiple borehole heat exchangers for production of heating and cooling energy in shallow geothermal reservoirs with underground water flow;Applied Thermal Engineering;2024-10

2. Advancing fractured geothermal system modeling with artificial neural network and bidirectional gated recurrent unit;Applied Energy;2024-10

3. A comparative study on ensemble soft-computing methods for geothermal power production potential forecasting;Energy;2024-09

4. Medicine distribution pattern detection in pharmaceutical supply chains: a new Kth-proximity density-distance-based method;International Journal of Pharmaceutical and Healthcare Marketing;2024-08-22

5. Machine-learning-assisted long-term G functions for bidirectional aquifer thermal energy storage system operation;Energy;2024-08