Lithofacies classification of a geothermal reservoir in Denmark and its facies-dependent porosity estimation from seismic inversion

•A novel system combining ANN and HMM is proposed to classify lithofacies of a potential geothermal reservoir in Denmark.•Depositional rules and complex data distributions are considered at the same time.•The classified lithofacies are then used as constraints for the prediction of porosity.•Differe...

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Vydané v:	Geothermics Ročník 87; s. 101854
Hlavní autori:	Feng, Runhai, Balling, Niels, Grana, Dario
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.09.2020 Elsevier Science Ltd
Predmet:	Algorithms Artificial Neural Networks Classification Conditional probability Geothermal energy Geothermal power Geothermal reservoir characterization Lithofacies classification Markov chains Markov priors Neural networks Porosity Porosity prediction Properties (attributes) Reservoirs Rock properties Rocks Seismic inversion results Seismic surveys Spatial distribution Statistical analysis Workflow Denmark Geothermal reservoir characterization Markov priors Lithofacies classification Artificial Neural Networks Porosity prediction Seismic inversion results
ISSN:	0375-6505, 1879-3576
On-line prístup:	Získať plný text
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