| Title | Depth-average Estimation of 1D Subsurface Resistivity from MT Data in Los Humeros Geothermal Field, Mexico |
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| Authors | José M ROMO-JONES, Thalia AVILES, Claudia ARANGO-GALVÃN, Diego RUIZ-AGUILAR, Jose Luis SALAS, ÃsdÃs BENEDIKTSDÓTTIR, Gylfi Páll HERSIR |
| Year | 2020 |
| Conference | World Geothermal Congress |
| Keywords | Geothermal, Mexico, Los Humeros, electrical conductivity, magnetotellurics, 1D inversion, GEMEX |
| Abstract | Generally, the first stage in the interpretation of magnetotelluric data consists of the construction of 1D resistivity models, i.e., subsurface resistivity versus depth profiles. A commonly used approach is to estimate 1D models with minimal structural complexity, frequently applying a data inversion scheme that uses the Occam´s razor principle. This type of algorithms uses the measured data (apparent resistivity and phase) to produce a simple distribution of the subsurface resistivity versus depth. As the solution is not unique, a given model is just one of a whole class of models that may fit the measurements equally well. Besides the instability inherent in the inverse problem, the construction of models is based on measured data that are both inaccurate and insufficient. Therefore, it is worthwhile to have some procedure to make statistical inferences about the goodness of the models, in terms of their variance and depth-resolution. In this paper, we apply a known simple method to estimate depth averages of the subsurface resistivity as well as their uncertainty and resolution. This approach uses only the apparent resistivity data and makes no other assumption. We applied this scheme to magnetotelluric data measured in Los Humeros geothermal field, in Mexico, within the frame of the GEMex project. Our estimations are shown together with the minimal-structure Occam-type models obtained from the same data set, in such a way that we can appreciate the 1D resistivity model along with the variance of the subsurface resistivity at different depths. This abstract presents results of the GEMex Project, funded by the Mexican Energy Sustainability Fund CONACYT-SENER, Project 2015-04-268074 and by the European Union’s Horizon 2020 research and innovation programe under grant agreement No. 727550. More information can be found on the GEMex Website: http://www.gemex-h2020.eu. |