首页> 外文会议>Society of Petroleum Engineers/European Association of Geoscientists Engineers Reservoir Characterization Simulation Conference >Case History:Seismic Facies Analysis Based on 3D Multiattribute Volume Classification in Shadegan Oilfield-Asmari Reservoir,Iran
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Case History:Seismic Facies Analysis Based on 3D Multiattribute Volume Classification in Shadegan Oilfield-Asmari Reservoir,Iran

机译:案例历史:基于Shadegan Oilfield-Asmari水库的3D多元体积分类的地震相分析,伊朗

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Shadegan oilfield is located in Khuzestan province in southwest of Dezful embayment,southwest of Iran.The latest 3D surface seismic was carried out in 1999 over an area of 192 km2 in this field to resolve structural ambiguities,delineate exact dimensions of the field,estimate reservoir parameters and perform a seismic facies analysis over the field for producer zones of Asmari reservoir.Asmari reservoir in this filed consists of three producer zones including zones 2,5 and 6.This paper will discuss about facies analysis of these zones based on 3D seismic multiattribute volume classification.A sophisticated approach was undertaken to perform multiattribute seismic facies analysis in the Asmari reservoir for each zone.Many lithology sensitive attributes were extracted from the post-stacked 3D seismic data and some of them were rejected using a multidimensional correlation technique in order not to take part in classification algorithm and determining the optimum set of attributes to use in the classification.This helped with data redundancy problems inherent in multiattribute analysis and avoiding independent attributes by choosing an appropriate set of attributes for the classification.So,the seismic attributes used for the facies classification included Signal Envelope,Heterogeneity Seismic Amplitude,Integration Seismic Amplitude,Magnitude Seismic Amplitude and Volume Reflection Spectrum.The objective was to integrate the seismic attribute information through the use of an unsupervised clustering technique.Clustering techniques are widely recommended tools for classification issues.The k-means algorithm is widely accepted as the standard technique of detecting different classes automatically from the measured data.This algorithm provided a facies database that was used to estimate lithofacies over the whole field.Using the clustering technique,three major lithologies including sandstone,carbonate and shale have been classified and displayed for each producer zone.Classified facies were calibrated to drilled wells and the results were confirmed.
机译:Shadegan Oilfield位于伊朗西南部的德比斯特省施工组省。最新的3D表面地震是在1999年在192公里的一个面积,以解决结构模糊,描绘场的精确尺寸,估计水库。估算水库参数和对Asmari Reservoir.asmari水库的生产区的领域进行地震相分析,在本申请中,包括三个生产区,包括区域2,5和6.本文将讨论基于3D地震多目标的这些区域的相分析体积分类。在每个区域进行复杂的方法,在ASMARI水库中进行多元的地震相分析。从堆叠后的3D地震数据中提取了Many岩性敏感属性,并且其中一些是使用多维相关技术拒绝的参加分类算法并确定要使用的最佳属性集在分类中。这有助于通过为分类的适当的一组属性来帮助数据冗余问题,并避免独立属性。所以用于面部分类的地震属性包括信号包络,异质性地震幅度,集成地震幅度,幅度地震幅度和体积反射谱。目的是通过使用无监督的聚类技术来集成地震属性信息。CLUSTING技术是广泛推荐的分类问题的工具。K-MEASE算法被广泛接受为标准技术从测量的数据中自动检测不同的类。本算法提供了一种用于估计整个领域的Lithofacies的相块。为每个生产者区分类并显示包括砂岩,碳酸盐和页岩的三大岩性。 CL.被配置的相校准钻孔井,结果得到了证实。

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