Probabilistic three-dimensional time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system

ROSAS CARBAJAL, MARINA; LINDE, NIKLAS; J. PEACOCK; FABIO. I. ZYSERMAN; T. KALSCHEUER; S. THIEL

GEOPHYSICAL JOURNAL INTERNATIONAL

WILEY-BLACKWELL PUBLISHING, INC

Lugar: Londres; Año: 2015 vol. 203 p. 1943 - 1960

0956-540X

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 magnetotelluricdata 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 toa 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 plumesthat 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.