Monitoring crustal stress state frOm 4D sEismic iMaging

Introduction

Tectonically active crustal settings such as volcanic fields and seismogenic fault systems are characterized by evolving stress critical conditions that can be detected by continuously measuring isotropic and, more importantly, anisotropic elastic properties. This is because these observables are strongly sensitive to the opening of fractures and to the infiltration and migration of magma and crustal fluids, which are more prominent before major volcanic eruptions and earthquakes.

Project Overview

With this respect, the team members of the ERC StG 758199 NEWTON are currently finalizing a novel 4D seismic imaging technique that allows the automatic detection of relevant changes in the crustal isotropic and anisotropic structural patterns and, by inference, of the crustal stress state.

Methodology

The new seismic inversion strategy has been tested with synthetic and real seismic datasets from the Etna volcanic field, with results indicating that it can detect robust changes in seismic anisotropy related to variations in the crustal stress state preceding volcanic eruptions and local earthquakes.

Focus of MODEM Activities

Given the current limited capacity to determine the evolving plumbing system dynamics (which, in turn, hampers the forecasting of major paroxysmal events), the activities of MODEM will focus on the development and distribution to volcano observatories of an open-source software which will include the novel methodology for monitoring the crustal structure and stress state evolution in volcanic fields.

1. The software will be firstly validated and integrated with the monitoring apparatus of the Etna volcano.
2. Subsequently, it will be disseminated over other European and international volcano observatories.

Future Goals

As the monitoring system can be applied to any crustal setting, our future goal is to commercialize the software, providing a service to oil and geothermal companies interested in characterizing time-dependent fracturing patterns and fluid/brine/oil distribution in economically sensitive fields.