Manara - Qatar Research Repository
Browse

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

Download (3.61 MB)
journal contribution
posted on 2022-11-22, 21:13 authored by Dominique Guérillot, Jérémie Bruyelle

The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO2 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 CO2 storage in geological formation is presented.

Other Information

Published in: Computational Geosciences
License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s10596-019-09861-4

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Springer Nature

Publication Year

  • 2019

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Texas A&M University at Qatar

Usage metrics

    Texas A&M University at Qatar

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC