Lithology and fluid prediction from seismic attributes using supervised Bayesian classification

Thierry Crozat. ( 2007 )
in: 27th gOcad Meeting, ASGA

Abstract

Traditional reservoir modeling combines data from various origins, which give different and complementary information. Well data give precise geological information about a very small part of the subsurface. On the other hand seismic data give information in 3D, but this information is at a lower vertical resolution and can not directly be linked to rock properties. If we want to combine these two sources of information to model a reservoir, we need to convert the seismic data into something more meaningful from a geological point of view. This paper presents a method and its implementation in the Gocad platform that can be used to make this conversion.

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    BibTeX Reference

    @inproceedings{CrozatRM2007,
     abstract = { Traditional reservoir modeling combines data from various origins, which give different and complementary information. Well data give precise geological information about a very small part of the subsurface. On the other hand seismic data give information in 3D, but this information is at a lower vertical resolution and can not directly be linked to rock properties. If we want to combine these two sources of information to model a reservoir, we need to convert the seismic data into something more meaningful from a geological point of view. This paper presents a method and its implementation in the Gocad platform that can be used to make this conversion. },
     author = { Crozat, Thierry },
     booktitle = { 27th gOcad Meeting },
     month = { "may" },
     publisher = { ASGA },
     title = { Lithology and fluid prediction from seismic attributes using supervised Bayesian classification },
     year = { 2007 }
    }