【摘要】 地震资料气层检测的常用方法是沿目的层拾取选定时窗内的地震属性进行属性分析,但该方法用于薄层砂岩储层的油气检测则比较困难。为此,本文利用非线性随机反演方法精细刻画砂体的空间展布,得到储层顶、底层位信息;再沿层提取各种地震属性,时窗随储层厚薄变化;分别应用基于RS理论的属性优化方法和SOM神经网络模式识别方法进行气层检测。将该方法应用于川西拗陷洛带气田,符合率达85%以上。更多还原

【Abstract】 Common-used method for gas reservoir detection by using seismic data is to pick up seismic attributes in fixed windows along the objective horizons and carry out attributes analysis,in which the oil/gas detection for thin-layer sandstone reservoir is more difficult.For that reason,the paper uses nonlinear random inversion method to finely describe the spatial distribution of sand body,getting the information of top and bottom horizons in reservoir;then picks up various seismic attributes along the horizons and windows change with the thickness variation of reservoir;and finally carries out gas-bearing formation detection by using RS theory-based attribute optimized method and SOM neural network mode recognition method respectively.The method was used in Luodai gasfield of Chuanxi depression,resulting in 85% and above of matched rate.更多还原