Data Publication

Magnetotelluric measurements in the Mérida Andes, western Venezuela

Ritter, Oliver | Cruces-Zabala, José | Weckmann, Ute | Tietze, Kristina | Schmitt, Reinhard | Schmitz, Michael

GFZ Data Services

(2021)

The 100 km wide Mérida Andes extend from the Colombian/Venezuelan border to the Caribbean coast. To the north and south, the Mérida Andes are bound by hydrocarbon-rich sedimentary basins. This mountain chain and its associated major strike-slip fault systems formed by the oblique convergence of the Caribbean with the South American Plate and the north-eastwards expulsion of the North Andean Block in western Venezuela. In 2013, the Integrated Geoscience of the Mérida Andes Project (the GIAME project) was initiated to image the Mérida Andes on a lithospheric scale and to develop a dynamic model of their evolution by integrating wide-angle seismic, magnetotelluric and potential field data. Magnetotelluric (MT) dataset was acquired in 2015 along a 240 km long profile across the Mérida Andes. MT studies of orogens often reveal complex resistivity structures, typically associated with active deformation and characterized by high electrical conductivity zones. Fluids in fault systems and fluids derived from remineralization reactions of hydrous minerals often characterise high conductivity in active tectonic regimes. Cruces-Zabala et al. (2020) identified conductive zones with up to 10 km depth for the Maracaibo Basin and 5 km for the Barinas - Apure Basin. The Mérida Andes are charaterized by high resistivity separated by several conductive anomalies that corelate spatialy to the fault systems at the surface. A conductive zone a great depth (>50km) was identified as a projection of the detachment surface of the Trujillo Block to the east. This data publication encompasses a detailed report in pdf format with a description of the project, information on the experimental setup, data collection, instrumentation used, recording configuration and data quality. The folder structure and content of the data repository are described in detail in Ritter et al. (2019). Time-series data are provided in EMERALD format (Ritter et al., 2015).

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