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  • 标题:Subsurface Channel Detection Using Color Blending of Seismic Attribute Volumes
  • 本地全文:下载
  • 作者:Jianhua Cao ; Yang Yue ; Kunyu Zhang
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:12
  • 页码:157-170
  • DOI:10.14257/ijsip.2015.8.12.16
  • 出版社:SERSC
  • 摘要:Color is the critical factor in seismic data interpretation and geological targets visualization. And recently, ideas of color blending have brought the enlightenment in attribute combinations for reservoir characterization in petroleum engineering. In this paper, we present this approach of color blending in different color modes and its application in subsurface channel detection by using seismic attributes data. The color models include RGB model, CMY model and HSV model. We firstly calculate sensitive attributes from three dimensional seismic data, including envelop, coherence and spectral decomposition, etc. Then three types of normalized seismic attributes are set as input into the primary color channel of the color models respectively, and then mixed together to create one color blended volume in three dimensional visualization environment. The blended volume has plenty of geological information coming from the three input attributes, resulting in better resolution for channels than the single attribute. Applications in one survey of DQ oilfield show that channels are vividly imaged with special lighted color on the blended volume slices. The spatial distribution characteristics of channels, including the shapes and branches, are clearly depicted. And for the three blending methods, the RGB model is mostly preferred although the CMY model has almost similar performances in channel detection, while HSV model is slightly inferior in this case.
  • 关键词:Color blending; color models; channel detection; seismic attributes
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