Application of oil–water discrimination technology in fractured reservoirs using the differences between fast and slow shear-waves

Luo, Cong; Li, Xiangyang; Huang, Guangtan. 2017 Application of oil–water discrimination technology in fractured reservoirs using the differences between fast and slow shear-waves. Journal of Geophysics and Engineering, 14 (4). 723-738. https://doi.org/10.1088/1742-2140/aa664f

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Official URL: https://doi.org/10.1088/1742-2140/aa664f

Abstract/Summary

Oil–water discrimination is of great significance in the design and adjustment of development projects in oil fields. For fractured reservoirs, based on anisotropic S-wave splitting information, it becomes possible to effectively solve such problems which are difficult to deal with in traditional longitudinal wave exploration, due to the similar bulk modulus and density of these two fluids. In this paper, by analyzing the anisotropic character of the Chapman model (2009 Geophysics 74 97–103), the velocity and reflection coefficient differences between the fast and slow S-wave caused by fluid substitution have been verified. Then, through a wave field response analysis of the theoretical model, we found that water saturation causes a longer time delay, a larger time delay gradient and a lower amplitude difference between the fast and slow S-wave, while the oil case corresponds to a lower time delay, a lower gradient and a higher amplitude difference. Therefore, a new class attribute has been proposed regarding the amplitude energy of the fast and slow shear wave, used for oil–water distinction. This new attribute, as well as that of the time delay gradient, were both applied to the 3D3C seismic data of carbonate fractured reservoirs in the Luojia area of the Shengli oil field in China. The results show that the predictions of the energy attributes are more consistent with the well information than the time delay gradient attribute, hence demonstrating the great advantages and potential of this new attribute in oil–water recognition.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1088/1742-2140/aa664f
ISSN:	1742-2132
Date made live:	05 Dec 2017 11:23 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/518570

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1088/1742-2140/aa664f

ISSN:

1742-2132

Date made live:

05 Dec 2017 11:23 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/518570