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      Estimation of porosity and gas hydrate saturation by inverting 2D seismic data using very fast simulated Annealing in the Krishna Godavari offshore basin, India

      1 , 1
      Geophysical Prospecting
      Wiley

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          ABSTRACT

          Gas hydrate saturation and porosity are the two essential parameters for characterizing a gas hydrate reservoir. Generally, porosities determined at the well locations are interpolated and extrapolated over the seismic volume, which is not so appropriate to get an estimate of gas hydrate saturation. Here, we propose a method to predict both porosity and gas hydrate saturation directly by inverting seismic data using a global optimization technique known as Very Fast Simulated Annealing. Acoustic impedance, as a function of water saturation and porosity, is defined by a second‐degree polynomial equation used as a forward problem. These are used as the primary model parameters. Acoustic impedance derived from these values is then used to compute synthetic seismograms that are compared against observed traces. We demonstrate our approach on a 23.5 km two‐dimensional seismic line crossing four wells in the Krishna Godavari Basin, eastern Indian offshore. First, the proposed method is tested on well log data and then applied on post‐stack seismic data. The posterior probability density function and the correlation matrix between the model parameters (gas hydrate saturation and porosity) are calculated to measure the associated uncertainty in prediction. Inversion results illustrate that the approach can be efficiently used for the prediction of porosity and gas hydrate saturation directly from the seismic data.

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          Most cited references58

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                Author and article information

                Contributors
                Journal
                Geophysical Prospecting
                Geophysical Prospecting
                Wiley
                0016-8025
                1365-2478
                February 2022
                December 15 2021
                February 2022
                : 70
                : 2
                : 388-399
                Affiliations
                [1 ] CSIR ‐ National Geophysical Research Institute Uppal Road Hyderabad 500007 India
                Article
                10.1111/1365-2478.13167
                e302cf4b-5acd-458e-ac14-8b3e0f51b9de
                © 2022

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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