GNGTS 2019 - Atti del 38° Convegno Nazionale

GNGTS 2019 S essione 3.1 575 metamorphic units and Pliocene granites. We applied the PSO to the MT profile depicted in Fig. 1. It is composed of 11 sites and the MT data have been acquired in 2004 (Manzella et al. , 2006). We performed the dimensionality analysis of the data set according to the WALDIM approach (Martì et al. , 2009) and obtained evidence of three-dimensionality at periods above 10 s. The strike analysis was carried out on the impedance tensor, phase tensor and Tipper matrix and outlined a strike direction of N130°E. As can be seen in Fig. 1, the investigated profile is orthogonal to this direction. Even though the dimensionality of this data set may suggest 3D interpretation as most appropriate, there are some conditions for the validity of 2D interpretation: inadequate spatial coverage (isolated profile) and the extreme complexity of 3D modeling (Ledo, 2005). A further reason of our 2D approach is to enrich the investigations of this area with the contribution of the stochastic inverse modeling. Manzella et al. (2006) inverted this profile using the non-linear conjugate gradient technique (Rodi and Mackie, 2001), adopting an external geological model as starting model. Our contribution is to overcome the geological bias on the solution by taking advantage of random initialization and adaptive global search. Some MT sites were affected by static shift due to local shallow heterogeneities that may provoke the telluric distortion of the impedance tensor. We corrected the static shift by performing the joint optimization (PSO) of time-domain electromagnetic (TDEM) and MT data of the same site (Santilano et al. 2018). We selected 8 MT sites, with static shift effects, for TDEM data acquisition. During a recent TDEM survey, carried out in February 2019 using a TEM-FAST48 instrument, the 8 soundings were acquired. The acquisition adopted a coincident-loop configuration for the transmitter and the receiver with the loop dimension of 50x50 or 100x100 m. Results. The resistivity model resulting from PSO is shown in Fig. 2. The period range of the data was between 0.003 and 993 s. The 2D mesh of the model was discretized to logarithmically increase towards the boundaries, with a total of 375 cells. The PSO input arguments were set as follows: the number of particles (i.e., the solutions explored) was 3400 because it should be about 9 times the number of unknowns (i.e., the model cells); the maximum number of iterations was about 4000; the boundaries of the search space of solution were 0.1 and 10000 Ωm. The final outcome is associated to a root-mean-square error of 4.18. The resistivity distribution of the subsurface presents a shallow conductive area below sites g2-a8, in line with the geology of the area (sedimentary deposits according to Romagnoli et al. 2010). In the first kilometer of depth below sites k4-j0, a high-resistivity region is imaged and justified by the formations of Fig. 1 – Map of the MT profile crossing the Travale geothermal area.