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Magma storage quantified under Aluto volcano, Ethiopia, using probabilistic tomography
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Rift volcanoes worldwide present significant hazards to people from eruptions but also provide resources such as geothermal energy. Aluto volcano in the Ethiopian rift is a hotspot for geothermal power exploitations, despite significant periods of deformation in the last 15 years. Various geophysical imaging methods have been applied to Aluto to obtain a detailed 3D image of the hydrothermal reservoir and the location, geometry, and size of possible magma bodies. However, the models give a single or narrow range of answers without the possibility for the exploration of uncertainties arising from the data and assumptions.Here we address this current limitation for the seismic data by performing a fully nonlinearized joint inversion of local seismic P- and S-wave travel times, and surface wave dispersion data between 0.5 Hz and 2 Hz from empirical Green's functions, for the location of earthquakes and the velocity of the subsurface. The combination of data types helps reduce the range of permitted models. We use a reversible-jump Markov chain Monte Carlo approach to incorporate prior information and, from our data, retrieve the posterior probability of earthquake parameters and seismic velocity in a Bayesian sense. This provides rigorous distributions of the covariance of the earthquake and velocity parameters.Our 3D seismic models display areas of elevated Vp/Vs ratio at 2-6 km depth under the caldera, interpreted as areas of partial melt. The hydrothermal reservoir shows in our results as lower Vp/Vs. This is in good agreement with the previous resistivity models from the magnetotelluric study of Samrock et al. 2020. However, while Samrock et al. observed two zones of partial melt, our model suggests that the lower and upper melt zones are connected. To go one step further, we developed a workflow to link seismic velocities to melt fraction estimates by combining the posterior distributions of seismic velocity and thermodynamic modeling. We conclude that the melt fraction under Aluto is between 3 and 7 % at 5 km depths, and the melt volume is approximately 0.37 km3.
Title: Magma storage quantified under Aluto volcano, Ethiopia, using probabilistic tomography
Description:
Rift volcanoes worldwide present significant hazards to people from eruptions but also provide resources such as geothermal energy.
Aluto volcano in the Ethiopian rift is a hotspot for geothermal power exploitations, despite significant periods of deformation in the last 15 years.
Various geophysical imaging methods have been applied to Aluto to obtain a detailed 3D image of the hydrothermal reservoir and the location, geometry, and size of possible magma bodies.
However, the models give a single or narrow range of answers without the possibility for the exploration of uncertainties arising from the data and assumptions.
Here we address this current limitation for the seismic data by performing a fully nonlinearized joint inversion of local seismic P- and S-wave travel times, and surface wave dispersion data between 0.
5 Hz and 2 Hz from empirical Green's functions, for the location of earthquakes and the velocity of the subsurface.
The combination of data types helps reduce the range of permitted models.
We use a reversible-jump Markov chain Monte Carlo approach to incorporate prior information and, from our data, retrieve the posterior probability of earthquake parameters and seismic velocity in a Bayesian sense.
This provides rigorous distributions of the covariance of the earthquake and velocity parameters.
Our 3D seismic models display areas of elevated Vp/Vs ratio at 2-6 km depth under the caldera, interpreted as areas of partial melt.
The hydrothermal reservoir shows in our results as lower Vp/Vs.
This is in good agreement with the previous resistivity models from the magnetotelluric study of Samrock et al.
2020.
However, while Samrock et al.
observed two zones of partial melt, our model suggests that the lower and upper melt zones are connected.
To go one step further, we developed a workflow to link seismic velocities to melt fraction estimates by combining the posterior distributions of seismic velocity and thermodynamic modeling.
We conclude that the melt fraction under Aluto is between 3 and 7 % at 5 km depths, and the melt volume is approximately 0.
37 km3.
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