基于Ricker子波匹配追踪算法在薄互层砂体储层预测中的应用
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摘要
我国东部大多数中、新生代陆相含油盆地大都以薄层砂、泥岩沉积为主,地层岩性和厚度横向变化均较大,而这些地层的厚度远低于常规地震勘探的垂向分辨率。为解决薄互层储层预测问题,笔者综合分析了短时傅里叶变换、连续小波变换和匹配追踪算法的优缺点,通过实验模型及实际资料分析,得到以下结论:与短时傅氏变换与连续小波变换相比,基于Ricker子波匹配追踪算法的频谱分解技术在分析薄互层储层时具有更高的时频分辨率,能够更客观地刻画地质体;从平湖油气田地震、测井数据分析,基于Ric-ker子波匹配追踪算法更有效地刻画出储层的空间形态,并且与实钻数据储层的分布吻合效果好。
In Eastern China,the vast majority of Mesozoic and Cenozoic continental oil basins are dominated by thin-layer sand and shale depositing,the lithology and thickness of the stratums varies largely in the transverse direction,and the thicknesses of these stratums are far less than the vertical resolution of conventional seismic exploration.In order to predict thin inter-bedded reservoir effectively,this paper analyzed both the advantage and disadvantage of common time-frequency methods such as STFT,CWT,MPD,and analyzed experimental model and oilfield material,and the conclusions can be obtained: Compared with STFT and CWT,the MPD based on Ricker wavelet has a better resolution in analyzing thin interbeded reservoirs,and it can describe geology cube more objectively.According to seismic data and well log data from Pinghu oilfield,the MPD based on Ricker wavelet can describe the reservoir space more effectively,and it fits the distribution of reservoir with the actual well log data.
引文
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