Carbonate fractured gas reservoir prediction based on P-wave azimuthal anisotropy and dispersion

Cao, Zhanning; Li, Xiang-Yang; Liu, Jun; Qin, Xilin; Sun, Shaohan; Li, Zongjie; Cao, Zhanyuan. 2018 Carbonate fractured gas reservoir prediction based on P-wave azimuthal anisotropy and dispersion. Journal of Geophysics and Engineering, 15 (5). 2139-2149.

Full text not available from this repository. (Request a copy)


Carbonate fractured gas reservoir detection is very significant for the process of oil-gas exploration. It is difficult to characterize the reservoirs properly by traditional post-stack seismic attributes, because of the complexity of mineralogical composition and fluid type. Based on rock physics, it becomes possible to effectively solve this problem. In this paper, we combine seismic azimuthal anisotropy analysis and P-wave (primary wave) dispersion inversion based on the appropriate rock physics model in order to provide a method for carbonate fractured gas reservoir prediction. Firstly, referring to the geology and logging data of a carbonate fractured reservoir in the S area of Tarim basin in western China, we introduce the Voigt–Reuss–Hill theory into the Chapman model and set up an appropriate model which includes the influences of lithology and physical and fluid properties. Then, through seismic forward modeling and inversion based on this model, we find that attenuation azimuthal anisotropy is very sensitive to fracture density, and P-wave dispersion is closely linked to fluid type. By comprehensive analysis of these two attributes, we can characterize the reservoirs well. Finally, both attributes were applied to analysis of seismic field data for carbonate gas reservoir discrimination in the S area of the Tarim basin. The results show that zones with strong attenuation anisotropy and intense P-wave dispersion are likely to be favorable gas reservoirs. This is consistent with trial production data, hence demonstrating the great advantages of our method in carbonate gas exploration.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 1742-2132
Date made live: 09 Oct 2018 15:02 +0 (UTC)

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...