3d crs analysis: a new data-driven optimization strategy for the simultaneous estimate of the eight stacking parameters
Proceedings of 79th Annual Meeting and International Exposition of the Society of Exploration Geophysics-SEG, Houston - Texas, Volume 28 - 2009
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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.
Références BibTex
@InProceedings{BCTM09a,
author = {Bonomi, E. and Cristini, A. and Theis, D. and Marchetti, P.},
title = {3d crs analysis: a new data-driven optimization strategy for the simultaneous estimate of the eight stacking parameters},
booktitle = {Proceedings of 79th Annual Meeting and International Exposition of the Society of Exploration Geophysics-SEG, Houston - Texas},
volume = {28},
year = {2009},
keywords = {data-driven method, stacking parameters, conjugate-direction algorithms, hpc},
url = {https://publications.crs4.it/pubdocs/2009/BCTM09a},
}