A gas-bearing property identification method for deep reservoirs based on frequency-dependent AVO inversion

被引：0
|
作者：
Liu D. [1 ]
Li K. [2 ]
Yang D. [1 ]
Wei X. [1 ]
机构：
[1] Research Institute, CNOOC China Limited Shenzhen Branch, Shenzhen, 510240, Guangdong
[2] School of Geosciences, China University of Petroleum <East China>, Qingdao, 266580, Shandong
来源：
Natural Gas Industry | 2020年 / 40卷 / 01期
关键词：
Deep reservoir; Fluid identification; Frequency-dependent AVO inversion; Frequency-dependent fluid factor; Gas-bearing prediction; Gassmann fluid term; Spectral decomposition;
D O I：
10.3787/j.issn.1000-0976.2020.01.006
中图分类号：
学科分类号：
摘要：
During the propagation of seismic wave in underground hydrocarbon bearing reservoirs, the phenomena of seismic amplitude attenuation and elastic characteristic dispersion happen, which makes it difficult to identify the fluids in deep hydrocarbon bearing reservoirs based on seismic data. In this paper, the fluid sensitivity degrees of a variety of frequency-dependent elastic parameters were analyzed based on the Chapman theoretical model of fractured-porous microstructure attenuation. And accordingly, the dispersion degree of Gassmann fluid term was selected as an identification factor for the gas-bearing prediction of deep reservoirs. Then, combined with the frequency spectrum decomposition method which is used for continuous wavelet conversion, spectrum analysis was carried out on some seismic data stacked with angle to determine the reference frequency. Based on this, the inversion optimization method of prestack seismic frequency-dependent Gassmann fluid term based on the Bayes Cauchy constraint criterion was researched, and the inversion result of frequency-dependent Gassmann fluid term was used to guide reservoir fluid detection. Finally, this method was applied in P exploration area in one offshore basin of China to verify its role in gas-bearing prediction of deep reservoirs. And it is indicated that by virtue of this method, the frequency-dependent Gassmann fluid parameters based on prestack seismic data can be extracted reliably, and correspondingly the identification results of deep reservoir fluid are better consistent with the actual logging interpretation results. In conclusion, the frequency-dependent Gassmann fluid term is conducive to identifying deep reservoirs effectively and provides a new idea and method for the identification of deep gas layers. © 2020, Natural Gas Industry Journal Agency. All right reserved.
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页码：48 / 54
页数：6
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