Characterization of a shale-gas reservoir based on a seismic AVO inversion for VTI media and quantitative seismic interpretation

Interpretation:1-40 (forthcoming)

Abstract
The Lower Silurian shale-gas formation in the south of Sichuan Basin represents strong VTI feature. Successful characterization of shale-gas formation requires handling the great influence of anisotropy in the seismic wave propagation. Seismic 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, shear modulus proportional to the anellipticity parameter, and the approximated horizontal P-wave velocity, 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 shale-gas reservoir. 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.
Keywords No keywords specified (fix it)
Categories No categories specified
(categorize this paper)
DOI 10.1190/int-2019-0050.1
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

Our Archive


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 44,462
External links

Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library

References found in this work BETA

No references found.

Add more references

Citations of this work BETA

No citations found.

Add more citations

Similar books and articles

Analytics

Added to PP index
2019-10-04

Total views
1 ( #1,361,429 of 2,273,203 )

Recent downloads (6 months)
1 ( #826,598 of 2,273,203 )

How can I increase my downloads?

Downloads

Sorry, there are not enough data points to plot this chart.

My notes

Sign in to use this feature