期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Pre-stack-texture-based reservoir characteristics and seismic facies analysis 被引量:5
1
作者 宋承云 刘致宁 +2 位作者 蔡涵鹏 钱峰 胡光岷 《Applied Geophysics》 SCIE CSCD 2016年第1期69-79,219,共12页
Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation.However,information is mislaid in the stacking process when tradit... Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation.However,information is mislaid in the stacking process when traditional texture attributes are extracted from poststack data,which is detrimental to complex reservoir description.In this study,pre-stack texture attributes are introduced,these attributes can not only capable of precisely depicting the lateral continuity of waveforms between different reflection points but also reflect amplitude versus offset,anisotropy,and heterogeneity in the medium.Due to its strong ability to represent stratigraphies,a pre-stack-data-based seismic facies analysis method is proposed using the selforganizing map algorithm.This method is tested on wide azimuth seismic data from China,and the advantages of pre-stack texture attributes in the description of stratum lateral changes are verified,in addition to the method's ability to reveal anisotropy and heterogeneity characteristics.The pre-stack texture classification results effectively distinguish different seismic reflection patterns,thereby providing reliable evidence for use in seismic facies analysis. 展开更多
关键词 pre-stack texture attributes reservoir characteristic seismic facies analysis SOM clustering gray level co-occurrence matrix
在线阅读 下载PDF
Study on attribute characterization for reservoir dynamic monitoring by seismic 被引量:1
2
作者 CHEN XiaoHong1,3,LI JingYe2,3 & ZHAO Wei4 1 Key Lab of Geophysical Exploration of CNPC,China Petroleum University,Beijing 102249,China 2 Basin & Reservoir Research Center,China Petroleum University,Beijing 102249,China +1 位作者 3 State Key Laboratory of Petroleum Resource and Prospecting,China University of Petroleum,Beijing 102249,China 4 Research Center of CNOOC,Beijing 100027,China 《Science China Earth Sciences》 SCIE EI CAS 2008年第S2期218-225,共8页
Study on characterizing reservoir parameters dynamic variations by time-lapse seismic attributes is the theoretical basis for effectively distinguishing reservoir parameters variations and conducting time-lapse seismi... Study on characterizing reservoir parameters dynamic variations by time-lapse seismic attributes is the theoretical basis for effectively distinguishing reservoir parameters variations and conducting time-lapse seismic interpretation,and it is also a key step for time-lapse seismic application in real oil fields. Based on the rock physical model of unconsolidated sandstone,the different effects of oil saturation and effective pressure variations on seismic P-wave and S-wave velocities are calculated and analyzed. Using numerical simulation on decoupled wave equations,the responses of seismic amplitude with different offsets to reservoir oil saturation variations are analyzed,pre-stack time-lapse seismic attributes differences for oil saturation and effective pressure variations of P-P wave and P-S converted wave are calculated,and time-lapse seismic AVO (Amplitude Versus Offset) response rules of P-P wave and P-S converted wave to effective pressure and oil saturation variations are compared. The theoretical modeling study shows that it is feasible to distinguish different reservoir parameters dynamic variations by pre-stack time-lapse seismic information,including pre-stack time-lapse seismic attributes and AVO information,which has great potential in improving time-lapse seismic interpreta-tion precision. It also shows that the time-lapse seismic response mechanism study on objective oil fields is especially important in establishing effective time-lapse seismic data process and interpreta-tion scheme. 展开更多
关键词 TIME-LAPSE SEISMIC dynamic monitoring rock physical model pre-stack attribute Amplitude Versus OFFSET (AVO)
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部