Tensor-based method for representation, analysis, and reconstruction of seismic data

Abstract

Method for representing seismic data as a spatially varying, second-order tensor field (). The spatial relationships expressed in these tensors are exploited to link, classify, or separate neighborhoods (); or to infer global or relational properties among them, thereby suggesting geobodies despite a noisy background. The tensors may be decomposed into their fundamentals that may either be used directly as derivative datasets or attributes, or may be used to facilitate linkage, classification, or separation of neighborhoods or analysis of linkage patterns. Decomposition may be by eigenvalues, with the eigenvalues used to define attributes called ballness, plateness and stickness (). Alternatively, connections may be made between points in the data where the tensor has been computed, called tokens (), based on tensor voting and polarity. Or, the connections may be based on a distance measure between tokens.