Geoelectrical image of the Sabalan geothermal reservoir from magnetotelluric studies

Abstract

The magnetotelluric (MT) survey of the Sabalan geothermal zone, which includes 22 stations along three traverse profiles across the main prospect zone, was conducted in 2007. The geophysical investigation utilized sharp boundary inversion of processed MT data due to the high contrast of electrical resistivity between embedded layers. This method was preferred to suppress the smeared-out impact of the smooth inversion algorithm on retrieving geological layering. The analysis of MT data led to the use of a 2D inversion algorithm to visualize the geothermal reservoir. Additionally, the geoelectrical strike of the main geothermal target was determined, showing some inconsistency across the profiles. The simulation of synthetic numerical models is conducted to evaluate the effectiveness of sharp boundary inversion compared to a smooth algorithm in sharp gradient mediums, specifically in terms of electrical characteristics, for plausible geothermal scenarios. The Finite Element method (FEM) was employed to construct these models, followed by running the 2D forward and inversion processes. The meshing and initial parameters of the modeling were set based on information obtained from prior geological and geophysical investigations. A sharp boundary inversion can be accurately implemented by introducing layering constraints along each profile surrounding the probable sought geothermal reservoir target. These layering constraints encompass the conductive cap, topsoil, and basement rocks, which are the key components of a plausible geothermal configuration. The results of the comparison indicate that the sharp boundary inversion technique effectively restored the boundary between neighboring layers that had significant differences in electrical resistivity. This was achieved when the smoothing algorithm failed to produce an accurate representation of the layered model. Ultimately, conceptual geological models were developed to illustrate the plausible structures corresponding to each profile, focusing on the sought geothermal reservoir targets. It can be deduced that many misunderstandings in the smoothing inversion algorithm will be omitted if the sharp boundary algorithm is used in highly electrical gradient structures. Based on the outcomes, a trachyandesite, andesite, and altered andesite reservoir exists at an elevation of 1600 to −2000 m. The reservoirs were recovered precisely with sharp and discriminable interfaces. Therefore, accurate interfaces led us to determine the conductive cap, heat source, and topsoil stacking as the main components of the geothermal system.