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    • 32. 发明授权
    • Seismic anomaly detection using double-windowed statistical analysis
    • 使用双窗口统计分析的地震异常检测
    • US09261615B2
    • 2016-02-16
    • US13860313
    • 2013-04-10
    • Krishnan Kumaran
    • Krishnan Kumaran
    • G01V1/30G01V1/00
    • G01V1/30G01V1/00G01V1/301
    • Method for identifying geologic features from seismic data (11) using seismic anomaly detection by a double-windowed statistical analysis. Subtle features that may be obscured using a single window on the data are made identifiable using two moving windows of user-selected size and shape: a pattern window located within a sampling window larger than the pattern window (12). If Gaussian statistics are assumed, the statistical analysis may be performed by computing mean and covariance matrices for the data within the pattern window in its various positions within the sampling window (13). Then a specific measure of degree of anomaly for each voxel such as a residue value may be computed for each sampling window using its own mean and covariance matrix (14), and finally the resulting residue volume may be analyzed, with or without thresholding, for physical features indicative of hydrocarbon potential (15).
    • 使用双窗口统计分析的地震异常检测方法从地震数据(11)中识别地质特征。 使用用户选择的尺寸和形状的两个移动窗口可以识别可以使用数据上的单个窗口遮蔽的细微特征:位于大于图案窗口(12)的采样窗口内的图案窗口。 如果假设高斯统计量,则可以通过在采样窗口(13)内的各个位置中计算模式窗口内的数据的平均值和协方差矩阵来执行统计分析。 然后,可以使用其自身的平均和协方差矩阵(14)为每个采样窗口计算每个体素的异常程度(例如残差值)的特定度量,最后可以分析具有或不具有阈值的所得残留体积 表明碳氢化合物潜力的物理特征(15)。