Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Lars H. Ystroem"'
Publikováno v:
Applied Computing and Geosciences, Vol 20, Iss , Pp 100144- (2023)
Solute artificial neural network geothermometers offer the possibility to overcome the complexity given by the solute-mineral composition. Herein, we present a new concept, trained from high-quality hydrochemical data and verified by in-situ temperat
Externí odkaz:
https://doaj.org/article/6a807d5927604d4a85fb6dd4d06dec51
Publikováno v:
Geothermal Energy, Vol 8, Iss 1, Pp 1-21 (2020)
Abstract For successful geothermal reservoir exploration, accurate temperature estimation is essential. Since reservoir temperature estimation frequently involves high uncertainties when using conventional solute geothermometers, a new statistical ap
Externí odkaz:
https://doaj.org/article/61715bb1c97c4394bfa4b69d368db5f9
Publikováno v:
Geothermics, 105, Art.-Nr.: 102548
In this study, we introduce MulT_predict as a fully integrated solute multicomponent geothermometer, combining numerical optimisation processes for sensitive parameters to back-calculate to chemical reservoir conditions. This results in a state of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::967b4a7cd3b7add2c15cbc62e4423a3f
https://doi.org/10.2139/ssrn.4081037
https://doi.org/10.2139/ssrn.4081037