GNGTS 2013 - Atti del 32° Convegno Nazionale

Kennett B.L.N.; 1978: Some aspects of non-linearity in inversion. Geophys. J. R. Astr. Soc., 55, 373-391. Mitchell M.; 1996: An introduction to genetic algorithms . MIT Press. Sambridge M.; 1999a: Geophysical inversion with a neighborhood algorithm-- II. Searching a parameter space. Geoph. J. Int. 138, 479-494. Sambridge M.; 1999b: Geophysical inversion with a neighborhood algorithm-- II. Appraising the ensemble. Geoph. J. Int. 138, 727-746. Sen M. K. and Stoffa P. L.; 1992: Rapid sampling of model space using genetic algorithms: examples from seismic waveform inversion. Geophysical journal International, 108, 281-292. Tarantola A.; 1986: A strategy for nonlinear elastic inversion of seismic reflection data. Geophysics, 51 ,10, 1893-1903. Voronoi M. G.; 1908: Nouvelles applications des paramètres continus à la théorie des formes quadratiques. J. reine Angew. Math., 134, 198-287. Chebyshev array forming for near surface investigations A. Tognarelli 1 , E. Stucchi 2 1 Earth Sciences Department, University of Pisa, Italy 2 Earth Sciences Department, University of Milan, Italy Introduction. In recent years, reflection seismics has increasingly been extended to near surface investigations to help in better delineate the subsurface properties, in particular the shallow layers geometry. The applications of shallow reflection surveys range from hydrogeological prospecting (Pugin et al. , 2009; Ge et al. , 2010), environmental and engineering problems (Miller and Steeples, 1994; Shtivelman, 2003), landslide characterization (Malemhir et al. , 2013; Stucchi et al. , in press) to mention but just a few. The generally limited availability of recording hardware when compared to oil or mining exploration, and the often poor performance of the energy sources, are two problems that add to the known difficulties inherent to the near surface exploration (Steeples and Miller, 1998). It is quite common to employ recording equipment using only 24 or 48 active channels, with single vertical or horizontal geophone (for P- or S-wave survey), and simple energy sources such as the sledgehammer or the weight drop. This results in a poor depth penetration of the seismic signal and in a severe source related noise contamination (ground roll and air blast) of the acquired data. However, it may be possible to turn these hardware weaknesses into potential advantages. In fact, the relative facility of striking blows with the sledgehammer and the flexibility aptitude of 24-48 channel short spreads allow the geophysicist to acquire a plentiful quantity of data and to leave to the processing lab the task to appropriately stack them to increase the signal-to-noise (S/N) ratio. This corresponds to performing source and/or receiver array simulations, where the output can be optimized on the basis of specific criteria such as noise attenuation or resolution. Indeed, contrarily to what happens in the field where the arrays would be fixed along the entire profile, the simulation of arrays in the processing can be time and space variant and their responses can be changed according to the changing characteristics of the data. In our work we demonstrate how effective spatial filters can be easily obtained by properly mixing and weighting different traces and how this turns out in a fair improvement in the data quality. The optimal weights are computed by means of Chebyshev polynomials (Carlini and Mazzotti, 1989; Holzman, 1963), where “optimal” is intended as more efficient and uniform noise attenuation in the array filter stop-band region compared to the un-weighted array. The real data pertain to a reflection survey carried out to delineate the subsurface structure of a huge landslide located in the Northern Apennine, Italy (Stucchi et al. , in press). A 10 kg sledgehammer and a 48 channels single geophone spread were used as the energy source and the recording devices in the production phase. Field acquisition. The spread configuration was designed on the basis of synthetic traveltimes (Zelt and Smith, 1992) computed on a three layers model built from previous geophysical and geotechnical data (Federici et al. , 2002). Tests were carried out in the first days 66 GNGTS 2013 S essione 3.1