Metodi avanzati di analisi di serie storiche per dati magnetotellurici

Responsabili di progetto

Luciano Telesca, Chienchih Chen

Accordo

TAIWAN - NSTC - National Science and Technology Council

Bando

CNR/NSC 2012-2013

Dipartimento

ICT

Area tematica

Ingegneria, ICT e tecnologie per l'energia e i trasporti

Stato del progetto

Nuovo

Proposta di ricerca

The Magnetotelluric (MT) method uses natural geomagnetic field that is characterized by signals with strong temporally variable amplitude in a wide frequency range (0.0001-10000 Hz) (Cagniard 1953). These electromagnetic fluctuations induce electric currents in the Earth, which produce secondary electromagnetic fields that can be used as source for probing the electrical resistivity structure of the Earth. The MT method allows to estimate the resistivity of the subsurface at different depths of resolution, by means of two important parameters: 1) the skin depth, which accounts for the attenuation of the electromagnetic signals in the Earth; and 2) the impedance tensor, which relates the magnetic and electric fields (Kaufman and Keller, 1981). In recent years, the MT method proved to be an effective method for studying the Earth subsurface. Besides classical applications like crustal studies (Bai et al., 2008), characterization of upper mantle and lithosphere-astenosphere boundary (Schmoldt et al., 2008), faults imaging (Tank et al., 2005) etc., this method found applications in the continuous monitoring of seismic active areas (Eisel and Egbert, 2001), in order to detect earthquake-related anomalous temporal patterns of the MT response. In fact, thanks to its high investigation depth, the MT method is able to reveal resistivity variations in the subsoil at seismogenic depths, due to modifications of the local stress field connected to porosity variations caused by cracks (Byerlee, 1993, Patella et al., 1997). On that account, MT method can be very effective to monitor the presence of fluids within fault zones reaching seismogenic depth.
The MT method uses primary time-varying fields generated by temporal variations in the ionosphere and magnetosphere, and by lightning discharges.  One key assumption of this method is that this external source is a plane wave at surface of conductive earth.  However, this assumption fails in the presence of inhomogeneous source fields generated, for instance, by highly localized ionospheric resonance.  Non-planar source excitations constitute a source of external noise that enhances time-variant perturbations of the MT impedance tensor.  Additionally, electrical noise is also present, generated by electric storms, seawater currents and man-made sources, such as electrified (DC) railway and tram lines.  Recent advances in instrumentation allows acquisition of high quality MT time series, which require equally advanced data analysis techniques in order to fully exploit this increasing quality.
Therefore the intended activities, which aim at developing and applying robust and advanced method for the analysis of MT data, include:  a)  creating of a common MT database available for both teams;  b) developing of pre-processing techniques (e.g., extraction of night-time and day-time subperiods of measurements, identification of spike-like variations, automatic identification of outliers and/or data gaps);  c) developing of wavelet-based methods and "tipper vectors" method to identify source effects;  d) developing and integration of advanced nonlinear time series tools, combining fractal, multifractal, entropic, information-based and wavelet methods for the analysis of MT data;  e) facilitating exchange visits of scientists as required to enhance the collaborative activities and generate research outputs;  g) supporting methodologically and technologically possible Ph.D students or young researchers;  h) creating a webpage for the project to facilitate coordinating results and enhance visibility of the collaboration.
We propose to analyze to develop and apply advanced techniques to process MT data to obtain the most reliable information about the geological and tectonic environment. In this project, by means of tools abovementioned for time series analysis, we will analyze the observed stationary MT time series both in Taiwan and in Italy to understand the intrinsic dynamics of these signals. An important aspect that Taiwanese NSC just launched in early 2011 is the integrated geophysical monitoring platform for earthquake prediction. About ten stationary MT monitoring sites will be established in this coming year and advanced time series analysis tools will be eager for promisingly detecting the enigmatic seismic electrical signals. The methodology tested in this project could be also readily applied to other time series of geophysical fields gathered. We therefore expect the fruitful offspring of this project under the CNR-NSC bilateral agreement.
The project combines the expertise of the two involved institutions in investigating MT data and the cooperation between them offers a real synergistic advantage of exchange of data, statistical/mathematical methodologies and, in general, all the know-how concerning MT.  In particular, the Italian team has been involved in MT monitoring activity since 2007 in Southern Italy, Morocco and Greece.  NCU's team has extensive experience in the analysis and processing of MT time series in Taiwan. Such experience is also shown by the quantity and quality of papers published in highly qualified peer-reviewed journals.
The expected results and deliverables of the project are:  1) Tools for the robust processing of MT data.  2) Intermediate and final reports on the performed activities and obtained results.  3) Papers and abstracts submitted to international journals and conferences respectively with the acknowledgement of the CNR-NSC bilateral agreement.  4) Webpage dedicated to the project (description, teams, data and results).  5) Seminars jointly organized in Italy and Taiwan focused on the topics of the project.

Obiettivi della ricerca

The specific objectives of the project are: 1) to investigate the time dynamics of the MT signal, by means of advanced statistical time series tools (spectral, fractal, multifractal, entropic, information-based, wavelet, and other nonlinear tools) and get information about the dynamics of the MT signal in terms of correlation structures, persistence, scaling, crossover phenomena, trends, periodicity, organization, degree of order/disorder; 2) to obtain the most complete picture of geophysical mechanisms of MT response; 3) to investigate the relationship between the MT signals and tectonics and geology of the monitored area; 4) to identify and quantify the source effects in the MT response; 5) to disseminate preliminary and final results of the project in international conferences, publications, and in a project-oriented internet website; 6) to foster young researchers and Ph.D students of both the involved institutions in the application of the developed MT signal processing tools.

Ultimo aggiornamento: 03/05/2024