Characterization of a shale-gas reservoir based on a seismic amplitude variation with offset inversion for transverse isotropy with vertical axis of symmetry media and quantitative seismic interpretation

Zhang, Feng; Wang, Lin; Li, Xiang-Yang. 2020 Characterization of a shale-gas reservoir based on a seismic amplitude variation with offset inversion for transverse isotropy with vertical axis of symmetry media and quantitative seismic interpretation. Interpretation, 8 (1). SA11-SA23. 10.1190/INT-2019-0050.1

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Official URL: http://dx.doi.org/10.1190/INT-2019-0050.1

Abstract/Summary

The Lower Silurian shale-gas formation in the south of the Sichuan Basin represents a strong transverse isotropy with vertical axis of symmetry (VTI) feature. Successful characterization of shale-gas formation requires handling the great influence of anisotropy in the seismic wave propagation. Seismic amplitude variation with offset (AVO) inversion for VTI media using PP-waves only is a difficult issue because more than three parameters need to be estimated and such an inverse problem is highly ill posed. We have applied an AVO inversion method for VTI media based on a modified approximation of the PP-wave reflection coefficient. This approximation consists of only three model parameters: the acoustic impedance (attribute A), shear modulus proportional to the anellipticity parameter (attribute B), and the approximated horizontal P-wave velocity (attribute C), which can be well-inverted and have great interpretation capability in shale-gas reservoir characterization. A statistical-rock-physics method was then applied to the inverted attributes for quantitative interpretation of the shale-gas reservoir. A Markov random field is combined with Bayesian rule to improve the continuity and accuracy of the interpretation results. Shales can be successfully discriminated from surrounding formations by using the attribute pair A-C, and the organic-rich gas-bearing shale can be successfully identified by using the attribute pair C-B . Comparison between the prediction results and well logs demonstrates the feasibility of the inversion and quantitative interpretation approaches.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1190/INT-2019-0050.1
ISSN:	2324-8858
Date made live:	14 Apr 2020 13:29 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/527476

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1190/INT-2019-0050.1

ISSN:

2324-8858

Date made live:

14 Apr 2020 13:29 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/527476