CRS4 Libro, Contributo in un libro

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https://hdl.handle.net/11050/56

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Mostra il contenuto di CRS4 Libro, Contributo in un libro per Autore "Bonomi, Ernesto"

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    3d crs analysis: a new data-driven optimization strategy for the simultaneous estimate of the eight stacking parameters
    (Curran Associates, 2009) Bonomi, Ernesto; Cristini, Antonio Maria; Theis, Daniela; Marchetti, Paolo
    We devised a data-driven strategy for the simultaneous estimate of the eight CRS traveltime attributes, solving a global non-linear minimization problem without the need of computing gradients. The essential elements in this Eni research and development activity are the following: a conjugate-direction method supported by well known convergence properties and an iterative line-search implementing the strong Wolfe-Powell rule for the control of the steplength. The resulting algorithm can reach very good solutions in presence of many local minima.
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    3D spectral reverse time migration with no-wraparound absorbing conditions
    (SEG, 1998) Bonomi, Ernesto; Brieger, Leesa; Nardone, Carlo; Pieroni, Enrico
    Comparative studies of methods of reverse time migration (RTM) show that spectral methods for calculating the Laplacian impose the least stringent demands on discretization stepsize; thus with spectral methods, the grid refinements often required by other methods can be avoided. Implemented with absorbing boundary conditions, which are energy-tuned to give good absorption at the boundaries, these spectral methods can be used effectively for migration, without suffering the problems of wraparound which have traditionally plagued them (Furumyra and Takenaka, 1995).
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    Acceleration of the anisotropic PSPI imaging algorithm with dataflow engines
    (Curran Associates, 2013-06) Tomas, Carlo; Cazzola, Luca; Oriato, Diego; Pell, Oliver; Theis, Daniela; Satta, Guido; Bonomi, Ernesto
    Although time-domain depth migration techniques have been successfully ported to run on modern hardware accelerators, their ultimate obstacle is the I/O overhead present during the imaging step. Frequency-domain depth migration algorithms overcome this limitation and can exploit the full potential of new computing technologies. In particular, our implementation of Phase Shift Plus Interpolation (PSPI) method is characterized by fast running time, good quality results under low signal-to-noise ratio conditions and excellent results for steep dips. We provide a novel computational dataflow scheme to perform acceleration of PSPI on a generic dataflow engine. We present speedup results obtained on the state-of-the-art dataflow technology for synthetic VTI datasets. Our measurements indicate that a dataflow approach can achieve high speedups despite larger and larger computational domains, increased complexity of the anisotropic approach and the I/O overhead during angle-gathers calculation.