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Please use this identifier to cite or link to this item: http://repositorio.ufba.br/ri/handle/ri/18102

Title: Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm
Other Titles: IEEE Geoscience and Remote Sensing Letters
Authors: Conti, Cassio Rodrigo
Roisenberg, Mauro
Schwedersky Neto, Guenther
Porsani, Milton José
Keywords: Acoustic impedance;Ant colony optimization (ACO);Fast deconvolution;Reservoir characterization;Seismic inversion
Issue Date: 2013
Abstract: This letter presents ACOBBR - V, a new computationally efficient ant-colony-optimization-based algorithm, tailored for continuous-domain problems. The ACOBBR - V algorithm is well suited for application in seismic inversion problems, owing to its intrinsic features, such as heuristics in generating the initial solution population and its facility to deal with multiobjective optimization problems. Here, we show how the ACOBBR - V algorithm can be applied in two methodologies to obtain 3-D impedance maps from poststack seismic amplitude data. The first methodology pertains to the traditional method of forward convolution of a reflectivity model with the estimated wavelet, where ACOBBR - V is used to guess the appropriate wavelet as the reflectivity model. In the second methodology, we propose an even faster inversion algorithm based on inverse filter optimization, where ACOBBR - V optimizes the inverse filter that is deconvolved with the seismic traces and results in a reflectivity model similar to that found in well logs. This modeled inverse filter is then deconvolved with the entire 3-D seismic volume. In experiments, both the methodologies are applied to a synthetic 3-D seismic volume. The results validate their feasibility and the suitability of ACOBBR - V as an optimization algorithm. The results also show that the second methodology has the advantages of a much higher convergence speed and effectiveness as a seismic inversion tool.
Description: Texto completo: acesso restrito. p.1119-1123
URI: http://repositorio.ufba.br/ri/handle/ri/18102
ISSN: 1545-598X
Appears in Collections:Artigos Publicados em Periódicos (IGEO)

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