Pre-stack-texture-based reservoir characteristics and seismic facies analysis  

基于叠前纹理的储层特征和地震相分析（英文）

作　　者：宋承云[1] 刘致宁 蔡涵鹏[2] 钱峰[1] 胡光岷[2] 

机构地区：[1]电子科技大学通信与信息工程学院,成都610000 [2]电子科技大学资源与环境学院,成都610000

出　　处：《Applied Geophysics》2016年第1期69-79,219,共12页应用地球物理（英文版）

基　　金：supported by the Scientific Research Staring Foundation of University of Electronic Science and Technology of China(No.ZYGX2015KYQD049)

摘　　要：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.地震纹理属性与地震相和储层特征密切相关,广泛地应用在地震资料的解释中。传统的地震纹理属性基于叠后数据提取,受叠加作用的影响,易造成地层特征信息的损失,不利于复杂储层的描述。本文提出叠前纹理属性,其不仅可以精细地刻画不同反射点波形的横向连续性,也能体现AVO、各向异性和介质的均质性。基于叠前纹理属性丰富的地层特征表达能力,结合SOM聚类算法,形成了利用叠前数据进行地震相分析的方法。该方法应用于中国某工区宽方位地震资料,通过对比证实了叠前纹理属性描述地层横向变化的优越性,并能揭示各向异性特征及非均质性特征,基于叠前纹理的分类结果能有效区分不同的地震反射模式,为地震相分析提供了可靠的依据。

关 键 词：Pre-stack texture attributes reservoir characteristic seismic facies analysis SOM clustering gray level co-occurrence matrix 

分 类 号：P618.13[天文地球—矿床学] P631.4[天文地球—地质学]