Probabilistic 3-D time-lapse inversion of magnetotelluric data: application to an enhanced geothermal system

Détails

ID Serval
serval:BIB_092C971C8ADD
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Probabilistic 3-D time-lapse inversion of magnetotelluric data: application to an enhanced geothermal system
Périodique
Geophysical Journal International
Auteur(s)
Rosas-Carbajal M., Linde N., Peacock J., Zyserman F.I., Kalscheuer T., Thiel S.
ISSN
0956-540X (Print)
1365-246X (Electronic)
Statut éditorial
Publié
Date de publication
2015
Volume
203
Pages
1946-1960
Langue
anglais
Résumé
Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved. We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.
Création de la notice
27/06/2016 10:01
Dernière modification de la notice
20/08/2019 12:31
Données d'usage