Integrated inversion of ground deformation and magnetic data at Etna volcano using a genetic algorithm technique

G Ganci G Ganci,L Fortuna L Fortuna,C Del Negro C Del Negro,G Currenti G Currenti

doi:10.4401/ag-3082

G Ganci G Ganci, L Fortuna L Fortuna + Show 2 more

Open Access

https://doi.org/10.4401/ag-3082

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Abstract

Geodetic and magnetic investigations have been playing an increasingly important role in studies on Mt. Etna eruptive processes. During ascent, magma interacts with surrounding rocks and fluids, and inevitably crustal deformation and disturbances in the local magnetic field are produced. These effects are generally interpreted separately from each other and consistency of interpretations obtained from different methods is qualitatively checked only a posteriori. In order to make the estimation of source parameters more robust we propose an integrated inversion from deformation and magnetic data that leads to the best possible understanding of the underlying geophysical process. The inversion problem was formulated following a global optimization approach based on the use of genetic algorithms. The proposed modeling inversion technique was applied on field data sets recorded during the onset of the 2002-2003 Etna flank eruption. The deformation pattern and the magnetic anomalies were consistent with a piezomagnetic effect caused by a dyke intrusion propagating along the NE direction.

Highlights

We investigate the ability of an inversion procedure based on Genetic Algorithms (GAs) for the estimation of the volcanic source parameters from available data
The forward models used by the GA provide a mathematical formulation that relates magnetic anomalies, displacements and stress/strain fields associated to a particular volcanic source
The main geophysical mechanisms leading to magnetic anomalies in active volcanic areas have been investigated: i) piezomagnetic processes related to stress-induced changes in rock magnetization, ii) electrokinetic effects arising from fluid flow within the volcano edifice in the presence of an electric double layer at the solid-liquid interface, and iii) thermal demagnetization or remagnetization phenomena

Summary

Introduction

Investigations on the geophysical models have revealed that they are highly non-linear and, as a consequence, the function to be minimized exhibits inherent discontinuities and multiple local minima In such a case, techniques based on gradient methods or linearization of the optimization problem are hardly effective. That entails the need for global optimization methods In this regard, we investigate the ability of an inversion procedure based on Genetic Algorithms (GAs) for the estimation of the volcanic source parameters from available data (magnetic and ground deformation). The GAs are considered due to their capability of performing a much broader search over the parameter space with a greater likelihood of finding the global optimal solution even in presence of local minima in the objective function (Goldberg, 1989) This modelling inversion technique was applied on field data sets recorded during the onset of the 2002 Etna eruption. In order to provide better constraints on the intrusion mechanism, we investigate joint inversion of magnetic and deformation data during the period encompassing the opening of the eruptive fissures on the NE flank in 2002-2003

The inversion technique

The objective function

Forward modelling

The 2002 Etna flank eruption

Conclusions