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Pre-stack inversion of angle gathers using a hybrid evolutionary algorithm
PUNEET SARASWAT1 ,
MRINAL K. SEN2,3
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1
Department of Applied Geophysics, Indian School of Mines, Dhanbad, Jharkhand, India 826004.,
2
Institute of Geophysics, University of Texas at Austin, 10100 Burnet Road, Building 19, Austin, TX 78758, U.S.A.,
3
CSIR - National Geophysical Research Institute, Uppal Road, Hyderabad, India 500006.,
JSE 2012, 21(2), 177–200;
Submitted: 24 August 2011 | Accepted: 21 February 2012 | Published: 1 May 2012
© 2012 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract
Saraswat, P. and Sen, M.K., 2012. Pre-stack inversion of angle gathers using a hybrid evolutionary algorithm. Journal of Seismic Exploration, 21: 177-200. Inversion of pre-and post-stack seismic data for acoustic and shear impedances is a highly non-linear and ill-posed problem. A deterministic inversion of band-limited seismic data produces smooth models that are devoid of high frequency variations observed in well logs. The objective of this paper is two-fold, i.e., to develop an efficient scheme to explore and exploit the model space, and to efficiently sample broadband models statistically. We demonstrate that the use of starting models from fractal based a priori pdfs helps us to derive elastic models of very high resolution. We also introduce a new hybrid inversion algorithm that takes advantage of both deterministic and stochastic methodologies. A deterministic inversion based on conjugate gradient (CG) method produces smooth models while a stand-alone stochastic method based on differential evolution (DE) produces high-resolution models of nearly the same accuracy. A hybrid algorithm that uses CG solution as a starting model converges much faster than a standalone DE to very good solutions. We demonstrate our results with application to a field seismic dataset. The hybrid algorithm can also be used to sample the most significant parts of the model space rapidly resulting in estimates of uncertainty.
Keywords
global optimization
pre-stack
inversion
differential evolution
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