Abstract: An apparatus and method for analyzing known data, storing the known data in a pattern database (“PDB”) as a template is provided. Additional methods are provided for comparing new data against the templates in the PDB. The data is stored in such a way as to facilitate the visual recognition of desired patterns or indicia indicating the presence of a desired or undesired feature within the new data. The apparatus and method is applicable to a variety of applications where large amounts of information are generated, and/or if the data exhibits fractal or chaotic attributes.

Abstract: A method and apparatus are provided to process spatial data including seismic data. Given a spatial dataset of n dimensions, a data-driven partitioning of the dataset is effected into topographically contiguous regions using feature specific indices. Then on each region, a set of features is calculated according to a computer process, wherein the features are considered sufficiently descriptive of the region. Thereupon, two or more regions which are topographically contiguous are grouped together and the associated features are assembled in an analytical structure to be input to a classifier.

Abstract: Given a spatial dataset of n dimensions, a data-driven partitioning of the dataset is effected into topographically contiguous regions using feature specific indices (for example, by examining the change in polarity of the impedance of seismic data). Then on each region, a set of features (which may be mathematical functions) is calculated (e.g., mean value of all data in the region), wherein the features are considered sufficiently descriptive of the region. Thereupon, two or more regions which are topographically contiguous are grouped together and the associated features are assembled in a structure (e.g., a vector or a matrix) to be input to a classifier.

Abstract: Given a spatial dataset of n dimensions, a data-driven partitioning of the dataset is effected into topographically contiguous regions using feature specific indices (for example, by examining the change in polarity of the impedance of seismic data). Then on each region, a set of features (which may be mathematical functions) is calculated (e.g., mean value of all data in the region), wherein the features are considered sufficiently descriptive of the region. Thereupon, two or more regions which are topographically contiguous are grouped together and the associated features are assembled in a structure (e.g., a vector or a matrix) to be input to a classifier.