Abstract

Volcano-hosted high-temperature geothermal reservoirs are powerful resources for green electricity generation. In regions where such resources are available, geothermal energy often provides a large share of a country’s total power generation capacity. Sustainable geothermal energy utilization depends on the successful siting of geothermal wells, which in turn depends on prior geophysical subsurface imaging and reservoir characterization. Electromagnetic resistivity imaging methods have proven to be a key tool for characterizing magma-driven geothermal systems because resistivity is sensitive to the presence of melt and clays that form through hydrothermal alteration. Special emphasis is often given to the “clay cap,” which forms on top of hydrothermal reservoirs along the flow paths of convecting geothermal fluids. As an example, the Aluto-Langano volcanic geothermal field in Ethiopia is covered with 178 densely spaced magnetotelluric (MT) stations. The 3D electrical conductivity model derived from the MT data images the magma body that acts as a heat source of the geothermal system, controlling geothermal convection and formation of alteration zones (commonly referred to as clay cap) atop the geothermal reservoir. Detailed 3D imaging of the clay cap topography can provide direct insight into hydrothermal flow patterns and help identify potential “upflow” zones. At Aluto all productive geothermal wells are drilled into zones of clay cap thinning and updoming, which is indicative of underlying hydrothermal upflow zones. In contrast, nonproductive wells are drilled into zones of clay cap thickening and lowering, which is an indicator for underlying “outflow” zones and cooling. This observation is linked to fundamental characteristics of volcano-hosted systems and can likely be adapted to other geothermal fields where sufficiently detailed MT surveys are available. Therefore, high-resolution 3D electromagnetic imaging of hydrothermal alteration products (clay caps) can be used to infer the hydrothermal flow patterns in geothermal reservoirs and contribute to derisking geothermal drilling projects.

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