Abstract: The 3-D visualization is a method of voxel-based seismic volume interpretation.The structural, stratigraphic and lithology features can be identified directly from the 3-D seismic volume.This 3-D scanning and tracing technology can be used to catch the main geology target quickly.Combined with well picks,the 3-D visualization can be used to solve the complicated geology problem.The self-organizing neural networks is a geology characterization method based on seismic trace shape.By correlating the waves of different seismic traces,the seismic facies distrbution can be got,with the well log facies,the seismic facies can be converted to sedimentary facies.These two methods had been used while the complicated lithology resrvoir in Intercampo Oilfield was studied,with the well logs,a very good result has been gained.

Key words: 3-D visualization, seismic facies, neural networks, reservoir prediction, method, application

摘要： 三维体可视化解释是通过采用各种不同的透明度参数,在三维空间内对三维地震数据体直接刻画地层的构造、岩性及沉积特征^[1]。这种三维立体扫描和追踪技术可使解释人员快速选定目标,结合精细的钻井标定,可帮助解释人员准确、快速的描述各种复杂的地质现象。自组织神经网络地震相分析是一种基于地震道形状的地质特征描述方法,主要通过对不同地震道的波形分析来获得地震相分布,结合测井相标定,可进一步将地震相转换成沉积相的三维空间分布。在对委内瑞拉英特甘博油田复杂岩性油藏的储层空间非均质性以及油水关系研究中,综合应用这两种基于三维场的地震体直接刻画方法,结合测井标定,取得了很好的应用效果。

关键词: 三维可视化, 地震相, 神经网络, 储层预测, 方法, 应用