GNGTS 2015 - Atti del 34° Convegno Nazionale

126 GNGTS 2015 S essione 3.3 Conclusions. A single-pass surface related multiple estimation method has been described for OBS data: no generation of intermediate new datasets is needed, and no model information other than water layer description is required. Results obtained on synthetic data demonstrate that the proposed technique can achieve the task of estimating both source-side and receiver-side surface related multiples, without requiring additional surface data (both recorded or simulated), and favorably compares to conventional multi-step approaches that involve OBS geometry transformations (i.e. datuming). The minimization of I/Ooverburden is obtained accepting an increased computational cost, as a higher dimensionality of multiple contribution gathers is required (as two unknown control points are involved instead of one single downward reflection point). Thus, the viability of the algorithm implies a careful implementation that contributes to reduce the increased computational costs in respect to standard 3D SRME approach. Moreover, the same computational kernel can be adapted to separate up-going and down-going wavefields, without the need of multicomponent data. Acknowledgments. The authors would like to thank Nicola Bienati (Eni Upstream and Technical Services) for fruitful discussions and valuable suggestions and Laura Fioretti and Sathya Costagliola (Aresys) for support in data processing. References Berkhout, A.J., and Verschuur, D.J., 1997, Estimation of multiple scattering by iterative inversion, Part I: Theoretical considerations: Geophysics, 62, 1586-1595. Bienati, N., Mazzucchelli, P., Codazzi, M., 2012, 3D-SRMEAntialiasing in the Multiple Contribution Gather Domain: 74 th Conference & Exhibition, EAGE, Expanded Abstracts, Y009. Costagliola, S., Codazzi, M., Mazzucchelli, P., Bienati, N., 2015, Improving Multiple Removal by Cooperative Matched Filtering: 77th Conference and Exhibition, EAGE, Expanded Abstracts, Th P4 14. Fioretti, L., Mazzucchelli, P., Bienati, N., 2015, Stagewise Conjugate Gradient Pursuit for Seismic Trace Interpolation, 77th Conference and Exhibition, EAGE, Expanded Abstracts, We N112 05. Jin, H., Wang, P., 2012, Model-Based Water-Layer Demultiple (MWD) for Shallow Water: From Streamer to OBS: 82th Annual International Meeting, SEG, Expanded Abstracts, 1-5. Ma, J., Sen, M. K., Chen, X., Liu, Y., 2010, OBC Multiple Attenuation Technique Using SRME Theory: 80th Annual International Meeting, SEG, Expanded Abstracts, 3473-3477. Moore, I., Dragoset, B., 2008, General surface multiple prediction: a flexible 3D SRME algorithm, First Break, Volume 26, 89-100. Pica, A., Manin, M. , Granger, P.Y., Marin, D., Suaudeau, E., David, B., Poulain, G., Herrmann, P. h., 2006, 3D SRME on OBS Data Using Waveform Multiple Modelling: 76th Annual International Meeting, SEG, Expanded Abstracts, 2659-2663. Verschuur, D. J., Neumann, E.I., 1999, Integration of OBS data and surface data for OBS multiple removal: 69th Annual International Meeting, SEG, Expanded Abstracts, 1350-1353. Automatic V RMS Builder S. Costagliola, P. Mazzucchelli Aresys, Milano, Italy Introduction. Velocity analysis plays an important role in seismic imaging. In general, the problem of estimating velocity from seismic data is an ill-posed inversion problem, in the sense that the data do not contain all the necessary information to define a velocity function with arbitrary variations with depth and along the horizontal directions (Biondi, 2006). Therefore, for the velocity updates derived with this procedure to be accurate, the current migration velocity must be close to the correct one, or the reflectors cannot be steeply dipping and the velocity have strong lateral variations.