Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation

<p dir="ltr">The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO<sub>2</sub> storage in a depleted reservoir or a saline aquifer. To simulate such reactive transfer processes, geochemical e...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Dominique Guérillot (14150973) (author)
مؤلفون آخرون: Jérémie Bruyelle (14158887) (author)
منشور في: 2019
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author Dominique Guérillot (14150973)
author2 Jérémie Bruyelle (14158887)
author2_role author
author_facet Dominique Guérillot (14150973)
Jérémie Bruyelle (14158887)
author_role author
dc.creator.none.fl_str_mv Dominique Guérillot (14150973)
Jérémie Bruyelle (14158887)
dc.date.none.fl_str_mv 2019-11-28T00:00:00Z
dc.identifier.none.fl_str_mv 10.1007/s10596-019-09861-4
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Geochemical_equilibrium_determination_using_an_artificial_neural_network_in_compositional_reservoir_flow_simulation/21597213
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Mathematical sciences
Numerical and computational mathematics
Reservoir simulation
Compositional
Heterogeneity
CO2 storage
Chemically reacting flows
Artificial neural network
dc.title.none.fl_str_mv Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO<sub>2</sub> storage in a depleted reservoir or a saline aquifer. To simulate such reactive transfer processes, geochemical equations (equilibrium and kinetics equations) are coupled with compositional flows in porous media in order to represent, for example, precipitation/dissolution phenomena. The aim of the decoupled approach proposed consists in replacing the geochemical equilibrium solver with a substitute method to bypass the huge consuming time required to balance the geochemical system while keeping an accurate equilibrium calculation. This paper focuses on the use of artificial neural networks (ANN) to determine the geochemical equilibrium instead of solving geochemical equations system. To illustrate the proposed workflow, a 3D case study of CO<sub>2</sub> storage in geological formation is presented.</p><h2>Other Information</h2><p dir="ltr">Published in: Computational Geosciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s10596-019-09861-4" target="_blank">http://dx.doi.org/10.1007/s10596-019-09861-4</a></p>
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network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/21597213
publishDate 2019
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spelling Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulationDominique Guérillot (14150973)Jérémie Bruyelle (14158887)Mathematical sciencesNumerical and computational mathematicsReservoir simulationCompositionalHeterogeneityCO2 storageChemically reacting flowsArtificial neural network<p dir="ltr">The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO<sub>2</sub> storage in a depleted reservoir or a saline aquifer. To simulate such reactive transfer processes, geochemical equations (equilibrium and kinetics equations) are coupled with compositional flows in porous media in order to represent, for example, precipitation/dissolution phenomena. The aim of the decoupled approach proposed consists in replacing the geochemical equilibrium solver with a substitute method to bypass the huge consuming time required to balance the geochemical system while keeping an accurate equilibrium calculation. This paper focuses on the use of artificial neural networks (ANN) to determine the geochemical equilibrium instead of solving geochemical equations system. To illustrate the proposed workflow, a 3D case study of CO<sub>2</sub> storage in geological formation is presented.</p><h2>Other Information</h2><p dir="ltr">Published in: Computational Geosciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s10596-019-09861-4" target="_blank">http://dx.doi.org/10.1007/s10596-019-09861-4</a></p>2019-11-28T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s10596-019-09861-4https://figshare.com/articles/journal_contribution/Geochemical_equilibrium_determination_using_an_artificial_neural_network_in_compositional_reservoir_flow_simulation/21597213CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/215972132019-11-28T00:00:00Z
spellingShingle Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
Dominique Guérillot (14150973)
Mathematical sciences
Numerical and computational mathematics
Reservoir simulation
Compositional
Heterogeneity
CO2 storage
Chemically reacting flows
Artificial neural network
status_str publishedVersion
title Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
title_full Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
title_fullStr Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
title_full_unstemmed Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
title_short Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
title_sort Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation
topic Mathematical sciences
Numerical and computational mathematics
Reservoir simulation
Compositional
Heterogeneity
CO2 storage
Chemically reacting flows
Artificial neural network