Prediction of gas hydrate saturation throughout the seismic section in Krishna Godavari basin using multivariate linear regression and multi-layer feed forward neural network approach
dc.contributor.author | Singh, Y. | |
dc.contributor.author | Nair, R.R. | |
dc.contributor.author | Singh, H. | |
dc.contributor.author | Datta, P. | |
dc.contributor.author | Jaiswal, P. | |
dc.contributor.author | Dewangan, P. | |
dc.contributor.author | Ramprasad, T. | |
dc.date.accessioned | 2016-06-14T06:56:00Z | |
dc.date.available | 2016-06-14T06:56:00Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Arabian Journal of Geosciences, vol.9(5); 2016; no.415 doi.:10.1007/s12517-016-2434-6 | |
dc.identifier.uri | http://drs.nio.org/drs/handle/2264/4977 | |
dc.description.abstract | Stepwise linear regression, multi-layer feed forward neural (MLFN) network method was used to predict the 2D distribution of P-wave velocity, resistivity, porosity, and gas hydrate saturation throughout seismic section NGHP-01 in the Krishna-Godavari basin. Log prediction process, with uncertainties based on root mean square error properties, was implemented by way of a multi-layer feed forward neural network. The log properties were merged with seismic data by applying a non-linear transform to the seismic attributes. Gas hydrate saturation estimates show an average saturation of 41 % between common depth point (CDP) 600 and 700 and an average saturation of 35 % for CDP 300-400 and 700-800, respectively. High gas hydrate saturation corresponds to high P-wave velocity and high resistivity except in a few spots, which could be due to local variation of permeability, temperature, fractures, etc | |
dc.language.iso | en | |
dc.publisher | Springer | |
dc.rights | An edited version of this paper was published by Springer. This paper is for R & D purpose and Copyright [2016] Springer. | |
dc.subject | GEOLOGY AND GEOPHYSICS | |
dc.subject | CHEMISTRY AND BIOGEOCHEMISTRY | |
dc.subject | AQUATIC RESOURCES | |
dc.subject | GEOLOGY AND GEOPHYSICS | |
dc.title | Prediction of gas hydrate saturation throughout the seismic section in Krishna Godavari basin using multivariate linear regression and multi-layer feed forward neural network approach | |
dc.type | Journal Article |
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