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基于AVO反演的频变流体识别方法
引用本文:张震,印兴耀,郝前勇.基于AVO反演的频变流体识别方法[J].地球物理学报,2014,57(12):4171-4184.
作者姓名:张震  印兴耀  郝前勇
作者单位:1. 中国石油大学(华东)地球科学与技术学院, 青岛 266580;2. 中国石油化工股份有限公司华北分公司, 郑州 450006
基金项目:国家重点基础研究发展计划(973计划)项目(2013CB228604)和国家油气重大专项(2011ZX05030-004-002)联合资助.
摘    要:研究表明流体引起衰减与频散往往表现为频变AVO现象.一些频散地震属性,例如纵波频散,已经证实为可靠的碳氢指示因子.为了更有效地识别流体,基于f-μ-ρ近似构建了新的流体因子Df,即频变流体项.该属性的反演首先需要连续小波变换(CWT)谱分解得到不同频带地震数据,通过去相关与先验约束来保证反演结果可靠性.模型试算证实了频变反射系数近似公式的精度可靠性,Df可以识别出强衰减介质所引起的频散现象.实际数据试算中,Df可以较好地识别储层孔隙流体,尤其对于气层,具有较好的指示效果.该流体因子将Gassmann流体项的高孔隙流体敏感性与叠前数据丰富的振幅频率信息相结合,反演效果与岩石物理认识相符.此研究有助于利用衰减频散现象借助AVO反演实现流体识别.

关 键 词:频散属性  频变AVO  流体项  谱分解  先验信息  
收稿时间:2013-10-28

Frequency-dependent fluid identification method based on AVO inversion
ZHANG Zhen,YIN Xing-Yao,HAO Qian-Yong.Frequency-dependent fluid identification method based on AVO inversion[J].Chinese Journal of Geophysics,2014,57(12):4171-4184.
Authors:ZHANG Zhen  YIN Xing-Yao  HAO Qian-Yong
Institution:1. School of Geosciences, China University of Petroleum (Eastern China), Qingdao 266580, China;2. China Petroleum & Chemical Corporation, Huabei Branch, Zhengzhou 450006, China
Abstract:Researches suggest that fluid-sensitive dispersion generally leads to a frequency-dependent AVO response. Frequency-dependent seismic attributes, such as P-velocity dispersion, have proven to be practical carbon indicators in both poststack inversion and prestack inversion. In terms of more efficient fluid identification consideration, we propose a new fluid factor Df, the frequency-dependent fluid term, based on f-μ-ρ AVO approximation. The algorithm to estimate Df is based on CWT spectral decomposition and incorporates a priori information to enhance inversion stability. Model test demonstrates the accuracy of the frequency-dependent approximation, and the feasibility of Df to distinguish attenuative medium. Applications to real data show Df can characterize hydrocarbon especially gas clearly. The meaning of this study is that the constructed fluid factor, associating high sensitivity of Gassmann fluid term to pore fluid with sufficient amplitude and frequency information of prestack data, performs well as we expect from rock physics experience. And this may provide an insight into how to bridge the gap between conventional AVO and attenuation and dispersion of in-situ oil and gas.
Keywords:Dispersion attribute  Frequency-dependent AVO  Fluid term  Spectral decomposition  A priori information
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