GNGTS 2018 - 37° Convegno Nazionale

GNGTS 2018 S essione 3.1 573 ESTIMATION OF AN ACOUSTIC VELOCITY MODEL FOR THE CROP M12A SEISMIC LINE USING A GRADIENT-BASED FULL WAVEFORM INVERSION B. Galuzzi 1 , E.M. Stucchi 2 , A. Tognarelli 2 1 Department of Computer Science, University of Milan-Bicocca, Milano, Italy 2 Department of Earth Sciences, University of Pisa, Italy Introduction. This work deals with the application of a Full Waveform Inversion (FWI) (Virieux, et. al. 2009) (Fichtner, 2010) procedure to increase the resolution of an acoustic ve- locity model related to a part of the M12ACROP marine seismic profile (Scrocca, et al. , 2003). The CROP M12A seismic line was acquired during the Italian Deep Crust Project (CROP), aimed at investigating the structure of the deep crust in Italy. In (Tognarelli et al. , 2010) the re- corded data were re-processed to enhance the visibility and the resolution of the structures at the shallow depth up to 3-4 s two-way travel time. Nowadays, FWI represents an important tool to build a high-resolution velocity model of the subsurface from active seismic data. Such model is obtained as the global minimum of some misfit function, designed to measure the difference between the observed and the modelled data. In general, the misfit function is highly non-linear with the presence of many local minima due to the well-known cycle skipping effect (Pratt, 2008). Therefore, the optimization problem is solved by means of an iterative gradient-based method, starting from a model as close as possible to the global minimum of the objective func- tion. Besides, the application of FWI to real data requires dedicated specific operations aimed at improving the S/N ratio and obtaining observed data that can be reliably reproduced by a modelling algorithm (Galuzzi et al. , 2018). In this work, we present an application of acoustic FWI on a part of CROP M12A seis- mic profile. Specific processing operations are applied on both predicted and observed data to increase the robustness of the inversion procedure, thus improving the reliability of the final model estimation. The predicted data are obtained by solving the 2D acoustic wave equation, whereas in the local optimization procedure the steepest descent algorithm is employed. The misfit function used is based on the L 2 norm difference between the predicted and observed envelopes of the seismograms (Bozdag et al. , 2011). As the starting model, we used the model obtained by (Tognarelli et al. , 2010) through the Migration Velocity Analysis (MVA) and used for the post-stack depth migration of the data. To validate the FWI final model, we check the improvements on the flattening of the events in the common-image-gathers (CIGs) after pre- stack depth migration. The seismic data. The CROP M12A seismic dataset consists of 1500 marine seismic shots, acquired in the northern Tyrrhenian Sea, south of the Elba Island, employing an air-gun source. The direction of the acquisition is from South-West to North-East. The sources and the receiv- ers are located at 8 m and 14 m below the sea surface, respectively. The source-receiver offset varies from 125 m to 4625 m. The receiver interval is 25 m, the time sampling is 4 ms and the record length is 17 s even if, to study the structures located at shallow depth, a two-way travel time up to 3-4 s is enough (Tognarelli et al. , 2010). From the entire data set, we select only 100 shot gathers evenly distributed in 22 km towards the end of the line. In this part of the profile, the sea-bed is almost flat with a depth of about 90 m. Figure 1a shows the location of the M12A CROP profile. The red arrow indicates the part of the profile used for the inversion, whereas Figure 1b shows an example of a raw shot gather used in the inversion. The red polygon rep- resents the time window used to focus the inversion on the diving waves and on the shallow reflections of the data and is defined for each seismogram. Modelling. The synthetic data are obtained by means of an explicit, 2nd order in time, finite difference algorithm which is used to solve the 2D acoustic wave equation. The model dimensions are approximately 24.5 km in length and 2 km in depth. The modelling grid is made by 981x80 nodes, with a uniform grid size of dx=25m. The sea-bed is situated between the 3 rd and 4 th row of the grid. We put absorbing boundary conditions on the lateral and bottom sides