Machine learning for creation of generalized lumped parameter tank models of low temperature geothermal reservoir systems

•Automating generation of tank models. The subject material should be of interest to reservoir engineers and operators of geothermal systems who are concerned with use of efficient modelling methods, optimal production planning and introduction of machine learning techniques to the geothermal sector...

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Veröffentlicht in:	Geothermics Jg. 70; S. 62 - 84
Hauptverfasser:	Li, Y., Júlíusson, E., Pálsson, H., Stefánsson, H., Valfells, Á.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.11.2017 Elsevier Science Ltd
Schlagworte:	Algorithms Artificial intelligence Cluster analysis Clustering Complexity analysis Complexity reduction algorithm Geothermal power Geothermal reservoir modeling Information criterion K-means clustering algorithm Learning algorithms Low temperature Lumped-parameter models Machine learning Mathematical models Model accuracy Model selection Parameters Physical properties Production planning Recursive methods Reservoirs Switch-back method Tanks Thermal energy Vector quantization Complexity reduction algorithm Lumped-parameter models Complexity analysis Geothermal reservoir modeling Information criterion Model selection Machine learning K-means clustering algorithm Switch-back method
ISSN:	0375-6505, 1879-3576
Online-Zugang:	Volltext
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