【摘要】 奇异值分解是基于矩阵的数学运算方法来优化压缩地震属性集,地震属性集空间维数一般较高,因此有必要对相关地震属性集进行压缩,从而揭示数据集所表征的储层特征,可用于识别有意义的地质目标。采用奇异值分解方法对苏里格气田东区致密砂岩石盒子组盒8段含气储层沿层属性集进行了优化压缩。实际应用结果表明:奇异值分解优化后的各分量比优化压缩前的单属性预测致密含气砂岩效果更好。更多还原

【Abstract】 Singular value decomposition(SVD) uses matrix-based mathematical operation to optimize and compress seismic attribute set,which usually has higher spatial dimension and it is necessary to be compressed to reveal reservoir characteristics and identify significant geological target. SVD method has been applied to optimize and compress the along-horizon attribute set of the tight sandstone gas reservoir in the He 8 member of the Shihezi formation in the east of Sulige gas field. The application result indicates that the SVD optimized components can better predict tight sandstone gas reservoir than single attribute before compression.更多还原