Sensitivity study using a genetic algorithm: inversion of amplitude variations with slowness |
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| Authors: | Ying Ji Satish C Singh Brian E Hornby |
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| Institution: | Bullard Laboratories, Department of Earth Sciences, University of Cambridge, Madingley Road, Cambridge CB3 0EZ, UK. ; ;Seismology Laboratories, I.P.G. Paris, France. |
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| Abstract: | A sensitivity study of elastic parameters in amplitude-variation-with-slowness (AVS) for small- and large-offset seismic data is presented. In order to handle the non-linearity associated with waveform or amplitude beyond the critical slowness, an inversion algorithm based on Bayes' theory is used. A genetic algorithm was used to obtain the a posteriori probability density (PPD) function. The sensitivity analysis is performed on synthetic data containing P-wave as well as converted S-wave reflections. Four different two-layer models, which represent the typical range of AVS responses associated with the gas-sands normally encountered in exploration, were used to examine how well the elastic parameters can be inverted for different parametrizations by comparing the PPD functions. The sensitivity study results suggest that including wide-angle data in the inversion can greatly enhance the quality of inversion. The converted S-wave reflections can provide valuable extra information that can be used to extract elastic parameters. The results with noisy data demonstrate that the contrast of density and three velocity ratios can be estimated robustly with wide-angle reflection data. |
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