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Effect of co-operative fuzzy c-means clustering on estimates of three parameters AVA inversion

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Abstract

We determine the degree of variation of model fitness, to a true model based on amplitude variation with angle (AVA) methodology for a synthetic gas hydrate model, using co-operative fuzzy c-means clustering, constrained to a rock physics model. When a homogeneous starting model is used, with only traditional least squares optimization scheme for inversion, the variance of the parameters is found to be comparatively high. In this co-operative methodology, the output from the least squares inversion is fed as an input to the fuzzy scheme. Tests with co-operative inversion using fuzzy c-means with damped least squares technique and constraints derived from empirical relationship based on rock properties model show improved stability, model fitness and variance for all the three parameters in comparison with the standard inversion alone.

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Authors and Affiliations

  1. Department of Geology and Geophysics, Indian Institute of Technology, Kharagpur, 721 302, India

    Rajesh R. Nair & Suresh Ch Kandpal

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  1. Rajesh R. Nair
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  2. Suresh Ch Kandpal
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Correspondence to Rajesh R. Nair.

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Nair, R.R., Kandpal, S.C. Effect of co-operative fuzzy c-means clustering on estimates of three parameters AVA inversion. J Earth Syst Sci 119, 137–145 (2010). https://doi.org/10.1007/s12040-010-0013-x

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  • DOI: https://doi.org/10.1007/s12040-010-0013-x

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