地震多属性RGBA颜色融合技术的应用研究
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摘要
利用数学工具和计算机图形能力将众多的地震属性映射为低维数的数据进行解释,可以提高地震属性分析的效率。地震多属性PCA-RGBA颜色融合技术是一种基于视觉的属性分析方法,其原理是,将多个地震属性通过主成分分析(PCA)技术进行降维,并将主分量按特征值由大到小排序,取前3个(或4个)主分量利用RGBA(Red-Green-Blue-Alpha)颜色融合原理获得一张融合图;再结合实际地质资料,在融合图像上依据颜色的区域性和突变异常等视觉特征,进行地质目标解释。在渤海SZ油田,应用该方法对常规地震属性数据进行了处理,在辅助断层识别、油藏流体时移变化区域判定等方面获得了良好的效果。
By using mathematical tools and computer graphic technology, many seismic attributes can be mapped to low-dimensional data for interpretation,and then improve the efficiency of seismic attribute analysis.Seismic multi-attributes PCA-RGBA color blending is a vision -based attribute analysis method.Firstly,seismic attributes are transformed to low-dimension by Principal Component Analysis (PCA) technology,and the principal components are arranged in terms of eigenvalues from big to small,the first three(or four) principal components are processed by RGBA(Red-Green-Blue-Alpha) color blending to obtain a blending map.Then,combing with the actual geologic data,geologic targets are interpreted by the vision characteristics(regional and abnormally changed of color) on blending map.Conventional seismic attributes of Bohai SZ oilfield were processed by the method;good results have been achieved in aiding for fault recognition and identifying the characteristics of reservoir fluid variation in time-lapse data.
By using mathematical tools and computer graphic technology, many seismic attributes can be mapped to low-dimensional data for interpretation,and then improve the efficiency of seismic attribute analysis.Seismic multi-attributes PCA-RGBA color blending is a vision -based attribute analysis method.Firstly,seismic attributes are transformed to low-dimension by Principal Component Analysis (PCA) technology,and the principal components are arranged in terms of eigenvalues from big to small,the first three(or four) principal components are processed by RGBA(Red-Green-Blue-Alpha) color blending to obtain a blending map.Then,combing with the actual geologic data,geologic targets are interpreted by the vision characteristics(regional and abnormally changed of color) on blending map.Conventional seismic attributes of Bohai SZ oilfield were processed by the method;good results have been achieved in aiding for fault recognition and identifying the characteristics of reservoir fluid variation in time-lapse data.
引文
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[11]魏艳,尹成,丁峰,等.地震多属性综合分析的应用研究[J].石油物探,2007,46(1):42-47
[12]Zhang J M,Zhao W,Huang X,et al.Feasibility study using simulation model for offshore field SZ36-1[J].Applied Geophysics,2006,3(2):105-111
[2]Wallet B C,Marfurt K J.A grand tour of multispectral components:a tutorial[J].The Leading Edge, 2008,27(3):334-341
[3]凌云,葸晓宇,孙德胜,等.薄储层叠后反演影响因素分析与地震属性解释研究[J].石油物探,2008,47 (6):531-558
[4]王濮,金振奎,李国发,等.薄层生物碎屑灰岩的地震属性检测[J].石油物探,2007,46(4):390-393
[5]张建宁,于建国.地震属性应用中的不确定性分析[J].石油物探,2006,45(4):373-379
[6]Balch A H.Color sonograms:a new dimension in seismic data interpretation[J].Geophysics,1971,36 (6):1074-1098
[7]Guo H,Lewis S,Marfurt K J.Mapping multiple attributes to three- and four-component color models—a tutorial[J].Geophysics,2008,73(3 ): W7-W19
[8]Onstott G E.Processing and display of offset-dependent reflectivity in reflection seismograms[D]. Austin,USA:University of Texas,1984
[9]Liu J L,Marfurt K J.Multicolor display of spectral attributes[J].The Leading Edge,2007,26(3): 268-271
[10]Guo H,Marfurt K J,Liu J L,et al.Principal components analysis of spectral components[J].Expanded Abstracts of 76~(th) Annual Internat SEG Mtg,2006, 988-992
[11]魏艳,尹成,丁峰,等.地震多属性综合分析的应用研究[J].石油物探,2007,46(1):42-47
[12]Zhang J M,Zhao W,Huang X,et al.Feasibility study using simulation model for offshore field SZ36-1[J].Applied Geophysics,2006,3(2):105-111
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