Analytic potentials for the forward and inverse modeling of SP anomalies caused by subsurface fluid flow

Classical interpretation techniques developed primarily for gravity and mag netic data have been adapted to electric self-potential (SP) data. From a r ecently developed wavelet-based technique for potential field interpretatio n, we propose a novel approach for the forward and inverse modeling of SP a nomalies caused by subsurface fluid flow. We use analytic. signals and wave lets associated with the electric and fluid flow potentials. Fluid flow sin gularities have typical signatures in the wavelet-domain SP data that can b e used in the inversion scheme. For cases where electrokinetics is unambigu ously the origin of SP anomalies, our interpretation method provides key pa rameters of the subsurface fluid flow (e.g. position, geometry, flow rate). To illustrate the theory, we consider synthetic 2D flows for which analyti c solutions exist. and actual SP data acquired around the Vulcarolo fissure on Mount Etna that show sources between 3 to 18 m depths.