MONITORING DEPTH VARIATIONS IN HYDROTHERMAL CELLS THROUGH MWT ANALYSIS OF SELF-POTENTIAL SIGNALS: INSIGHTS FROM THE 1993-2008 ERUPTIVE CYCLE OF PITON DE LA FOURNAISE VOLCANO, LA REUNION

Multi-scale wavelet tomography (MWT) is an analysis method based on dilation and isometric properties of the Poisson kernel and wavelet theory using a series of filters (analyzing wavelets). This study uses four first derivatives of the Poisson kernel applied to electrical potential field methods in order to determine the depth of the main hydrothermal cells that generate the measured potential-field anomaly.

The hydrothermal system of Piton de la Fournaise volcano, La Reunion, was studied over a 16 year period (1993-2008) based on 10 complete self-potential loops analyzed through multi-scale wavelet tomography. This study shows a correlation between magmatic and hydrothermal activity expressed through the vertical displacement of the center of activity of the main hydrothermal cells within the summit cone. Our results strongly support the existence of six main hydrothermal flow paths within the summit cone. During the 1993-2008 period, hydrothermal cells varied in depth over several hundred meters. Three distinct periods can be highlighted: 1) the 1993-1997 quiescence period shows large depth heterogeneity of the hydrothermal cells with most of the sources at relatively great depth; 2) the 1998 period is marked by the resumption of eruptive activity and the rise of all hydrothermal cells towards the surface; and 3) the 1999-2008 period is marked by a peak of eruptive activity and relatively stable depths of the hydrothermal cells restricted to near the surface.

By quantitatively determining the vertical displacement of hydrothermal fluids over 16 years, the MWT method allows us to demonstrate the correlation between volcanic activity and changes occurring within the hydrothermal systems. We thus obtain indirect information on the state of pressurization/depressurization of the volcano from the depth of the hydrothermal systems. When used in conjunction with long term volcano monitoring, this approach may help to enable detection of precursory signals corresponding to changes in volcanic activity.